# COMPSCI/ECE/EMA/EP/ME 759: High Performance Computing for Applications in Engineering | UW–Madison [View on UW Courses](https://uwcourses.com/courses/COMPSCI_ECE_EMA_EP_ME_759) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07 ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T19:50:42.743001+00:00 ### courses 8951 ### current instructors 5754 ### limited false ### terms * 1272 * 1264 * 1262 * 1254 * 1252 * 1244 * 1242 * 1234 * 1232 * 1224 * 1222 * 1212 * 1204 * 1202 * 1194 * 1192 * 1184 * 1182 * 1174 * 1172 * 1164 * 1162 * 1154 * 1152 * 1144 * 1142 * 1134 * 1132 * 1124 * 1122 * 1114 * 1112 * 1104 * 1102 * 1094 * 1092 * 1084 * 1082 * 1074 * 1072 ### term 1272 ### departments | subject | count | | --------- | ----- | | AAE | 90 | | ABT | 20 | | ACCTIS | 36 | | ACTSCI | 14 | | AFAERO | 10 | | AFRICAN | 87 | | AFROAMER | 71 | | AGROECOL | 21 | | AMERIND | 53 | | ANAT\&PHY | 7 | | ANATOMY | 2 | | ANESTHES | 8 | | ANSCI | 57 | | ANTHRO | 95 | | ART | 125 | | ARTED | 10 | | ARTHIST | 121 | | ASIALANG | 129 | | ASIAN | 109 | | ASIANAM | 28 | | ASTRON | 38 | | ATMOCN | 69 | | BIOCHEM | 51 | | BIOCORE | 10 | | BIOLOGY | 14 | | BIOMDSCI | 18 | | BME | 66 | | BMI | 41 | | BMOLCHEM | 10 | | BOTANY | 69 | | BSE | 44 | | C\&ESOC | 73 | | CBE | 48 | | CHEM | 101 | | CHICLA | 52 | | CIVENGR | 133 | | CLASSICS | 47 | | CNP | 10 | | CNSRSCI | 50 | | COMARTS | 137 | | COMPBIO | 15 | | COMPLIT | 11 | | COMPSCI | 138 | | COUNPSY | 78 | | CRB | 19 | | CS\&D | 71 | | CSCS | 40 | | CURRIC | 193 | | DANCE | 93 | | DERM | 8 | | DS | 88 | | DYSCI | 35 | | ECE | 155 | | ECON | 145 | | EDPOL | 114 | | EDPSYCH | 97 | | ELPA | 70 | | EMA | 53 | | EMERMED | 17 | | ENGL | 206 | | ENTOM | 40 | | ENVIRST | 148 | | EP | 15 | | EPD | 67 | | ESL | 16 | | F\&WECOL | 60 | | FAMMED | 22 | | FINANCE | 50 | | FOLKLORE | 40 | | FOODSCI | 43 | | FRENCH | 63 | | GEN\&WS | 145 | | GENBUS | 72 | | GENECSLR | 17 | | GENETICS | 60 | | GEOG | 113 | | GEOSCI | 83 | | GERMAN | 82 | | GLE | 48 | | GNS | 38 | | GREEK | 27 | | HDFS | 41 | | HEBR-BIB | 13 | | HEBR-MOD | 10 | | HISTORY | 233 | | HISTSCI | 56 | | HONCOL | 13 | | ILS | 43 | | INFOSYS | 9 | | INTEGART | 7 | | INTEGSCI | 22 | | INTER-AG | 18 | | INTER-HE | 11 | | INTER-LS | 22 | | INTEREGR | 16 | | INTLBUS | 21 | | INTLST | 50 | | ISYE | 83 | | ITALIAN | 53 | | JEWISH | 56 | | JOURN | 88 | | KINES | 128 | | LACIS | 26 | | LANDARC | 61 | | LATIN | 24 | | LAW | 120 | | LEGALST | 48 | | LINGUIS | 35 | | LIS | 89 | | LITTRANS | 78 | | LSC | 52 | | M\&ENVTOX | 7 | | MARKETNG | 62 | | MATH | 153 | | MDGENET | 8 | | ME | 130 | | MEDHIST | 43 | | MEDICINE | 60 | | MEDIEVAL | 32 | | MEDPHYS | 39 | | MEDSC-M | 29 | | MEDSC-V | 41 | | MHR | 68 | | MICROBIO | 45 | | MILSCI | 16 | | MM\&I | 22 | | MOLBIOL | 6 | | MS\&E | 59 | | MUSIC | 165 | | MUSPERF | 126 | | NAVSCI | 20 | | NE | 44 | | NEURODPT | 11 | | NEUROL | 7 | | NEURSURG | 4 | | NTP | 11 | | NURSING | 111 | | NUTRSCI | 65 | | OBS\&GYN | 18 | | OCCTHER | 39 | | ONCOLOGY | 14 | | OPHTHALM | 5 | | OTM | 43 | | PATH | 34 | | PATH-BIO | 29 | | PEDIAT | 26 | | PHARMACY | 31 | | PHILOS | 77 | | PHMCOL-M | 11 | | PHMPRAC | 45 | | PHMSCI | 60 | | PHYASST | 37 | | PHYSICS | 88 | | PHYSIOL | 3 | | PHYTHER | 37 | | PLANTSCI | 52 | | PLPATH | 35 | | POLISCI | 192 | | POPHLTH | 58 | | PORTUG | 33 | | PSYCH | 101 | | PSYCHIAT | 22 | | PUBAFFR | 54 | | PUBLHLTH | 23 | | RADIOL | 11 | | REALEST | 41 | | RELIGST | 90 | | RHABMED | 9 | | RMI | 24 | | RP\&SE | 102 | | S\&APHM | 17 | | SCANDST | 73 | | SLAVIC | 89 | | SOC | 149 | | SOCWORK | 87 | | SOILSCI | 46 | | SPANISH | 83 | | SRMED | 21 | | STAT | 94 | | STDYABRD | 52 | | STS | 8 | | SURGERY | 25 | | SURGSCI | 33 | | THEATRE | 91 | | URBRPL | 60 | | UROLOGY | 5 | | ZOOLOGY | 89 | ## course ### run id 20260907T155543-ce3781c4 ### semester 1272 ### observed at 2026-09-07 15:55:43.033547+00:00 ### record version id 8a275bf787a8a314b5a3ef26abf304b6dc67cc2a641709b6843256eb2c75ac44 ### course id COMPSCI/ECE/EMA/EP/ME 759 ### course uid course\_63e805b33518ff3fd8dc0a39 ### catalog version id 318f305a11567e7e6549b819a6a5329196c7c0e3d8f25e7f54f8851ecb74c16f ### course number 759 ### subjects * COMPSCI * ECE * EMA * EP * ME ### title HIGH PERFORMANCE COMPUTING FOR APPLICATIONS IN ENGINEERING ### description An overview of hardware and software solutions that enable the use of advanced computing in tackling computationally intensive Engineering problems. Hands-on learning promoted through programming assignments that leverage emerging hardware architectures and use parallel computing programming languages. Students are strongly encourage to have completed COMP SCI 367 orCOMP SCI 400or to have equivalent experience. ### requirements text Graduate/professional standing ### credits min 3 ### credits max 3 ### credit offering ids * 1272:266:023880 * 1272:320:023880 * 1272:346:023880 * 1272:347:023880 * 1272:612:023880 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 71ad01e1772a5dc2d550a582317fe78ccaee20c37738e54a5484648f6ab85df7 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Covers hardware and software solutions for advanced computing in engineering, with hands-on parallel programming assignments. ### llm topics * Hardware and software solutions for advanced computing * Parallel computing programming languages * Emerging hardware architectures ### llm skills * Parallel computing programming using emerging hardware architectures. * Applying advanced computing solutions to engineering problems. ### llm assumed background * Programming fundamentals including data structures, algorithms, and professional coding standards. ### llm search phrases * high performance computing engineering * parallel computing programming languages * advanced computing hardware software solutions * computationally intensive engineering problems ### llm requirements status valid ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash f7eccb54344e2387f2a4348390133f4c8949b6184376d6a76e4a56a88435f1c1 #### course id COMPSCI/ECE/EMA/EP/ME 759 #### current instructors ```json [ { "instructor_uid": "instructor_6b538cd1085236661960506e", "message": "No course-specific reviews available", "name": "Tsung-Wei Huang", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" } ], "text": "Recent recorded grades — Fall 2024: 3.99 GPA, 100.0% A/AB (n=69 letter grades); Spring 2025: 3.98 GPA, 100.0% A/AB (n=112 letter grades)." } ] } ] ``` #### difficulty workload Historical reviews of Dan Negrut: Reviewers note the class involves significant work, particularly weekly programming assignments, but consider them doable with effort. ```json { "citations": [ { "instructor_name": "Dan Negrut", "review_date": "2018-01-23 11:31:56 +0000 UTC", "review_id": "9e4da8adb27e73b85824e275", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI5NDkxOTU4", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2021-05-20 21:08:39 +0000 UTC", "review_id": "21b1eb9bccf4291655ebd781", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM0ODM0MDA2", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews of Dan Negrut: Tsung-Wei Huang is the current instructor, but all provided reviews describe Dan Negrut. Negrut is praised for his engaging lectures, deep knowledge of parallel computing, and lenient grading. Reviewers highlight his care for students and well-designed assignments. ```json { "citations": [ { "instructor_name": "Dan Negrut", "review_date": "2015-11-23 21:56:04 +0000 UTC", "review_id": "1faa357776fe5e565e204fc3", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI1NDc4ODY0", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2017-12-09 18:05:23 +0000 UTC", "review_id": "133b8672ef24400e61ecb568", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI5MTExMTQz", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2018-01-23 11:31:56 +0000 UTC", "review_id": "9e4da8adb27e73b85824e275", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI5NDkxOTU4", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2020-05-13 13:47:50 +0000 UTC", "review_id": "c41a0cf96b845bcfe0c90dbf", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTMzMjgzNDg1", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2021-05-20 21:08:39 +0000 UTC", "review_id": "21b1eb9bccf4291655ebd781", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM0ODM0MDA2", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2021-12-23 02:31:45 +0000 UTC", "review_id": "bb1200f60f4ff2ea167fe3dc", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM1NjM4MjU0", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2022-11-21 08:12:13 +0000 UTC", "review_id": "6eec454b834b36d236d32f7f", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM2ODcyNzky", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2022-12-19 03:59:11 +0000 UTC", "review_id": "f27596d8906c9616cdd54dd5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM3MTg0NTIx", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2023-11-21 05:00:11 +0000 UTC", "review_id": "a51f2c436eb2344e70155484", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM4NDI0ODY0", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2024-03-19 05:40:57 +0000 UTC", "review_id": "aa18e5d9f49866787f13f0ed", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM5MDYyODM2", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" } ] } ``` #### offered true #### profile hash 672f506f2fc2f46a071b9777f4a92cc197b2ccdeef25590e9285146d8c7e7f90 #### quick take Historical reviews for Dan Negrut describe a well-made curriculum focused on High Performance Computing with CUDA and OpenMP, offering a great learning experience. ```json { "citations": [ { "instructor_name": "Dan Negrut", "review_date": "2017-12-09 18:05:23 +0000 UTC", "review_id": "133b8672ef24400e61ecb568", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI5MTExMTQz", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2018-01-23 11:31:56 +0000 UTC", "review_id": "9e4da8adb27e73b85824e275", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTI5NDkxOTU4", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" } ] } ``` Recent recorded grades — Fall 2024: 3.99 GPA, 100.0% A/AB (n=69 letter grades); Spring 2025: 3.98 GPA, 100.0% A/AB (n=112 letter grades); Spring 2026: 3.97 GPA, 100.0% A/AB (n=102 letter grades). ```json { "citations": [ { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience Historical reviews of Dan Negrut: Students value the well-designed lectures and homework, noting the availability of recordings and opportunities to explore parallel computing in the final project. ```json { "citations": [ { "instructor_name": "Dan Negrut", "review_date": "2023-11-21 05:00:11 +0000 UTC", "review_id": "a51f2c436eb2344e70155484", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM4NDI0ODY0", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" }, { "instructor_name": "Dan Negrut", "review_date": "2024-03-19 05:40:57 +0000 UTC", "review_id": "aa18e5d9f49866787f13f0ed", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:812301", "source_review_id": "UmF0aW5nLTM5MDYyODM2", "source_url": "https://www.ratemyprofessors.com/professor/812301", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history DAN NEGRUT is recorded teaching in Fall 2013, Fall 2015, Fall 2017, Spring 2019, Spring 2020, Fall 2022, Fall 2023, Spring 2026. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1142", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1162", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1182", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 3, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1182", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1194", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 3, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1194", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1204", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 3, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1204", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1264", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 3, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1264", "type": "grade" } ] } ``` TSUNG-WEI HUANG is recorded teaching in Fall 2024, Spring 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "source_record": { "entity_id": "3b838d97-977e-3e8f-b80b-a07085e8b244", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": "Graduate/professional standing", "course": null, "evidence": "Graduate/professional standing", "id": "n0", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors | instructor\_uid | source | source\_instructor\_id | identity\_basis | identity\_status | name | email | first\_observed\_at | last\_observed\_at | instructor\_url | | ------------------------------------ | ---------- | ---------------------- | --------------- | ------------------ | --------------- | ------------------------- | -------------------------------- | -------------------------------- | ----------------------------- | | instructor\_6b538cd1085236661960506e | enrollment | thuang295 | netid | source\_identified | Tsung-Wei Huang | TSUNG-WEI.HUANG\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/TSUNG-WEI\_HUANG | ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:266:023880", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1272", "source_course_id": "023880", "source_subject_id": "266", "title": "High Performance Computing for Applications in Engineering", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:320:023880", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1272", "source_course_id": "023880", "source_subject_id": "320", "title": "High Performance Computing for Applications in Engineering", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:346:023880", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1272", "source_course_id": "023880", "source_subject_id": "346", "title": "High Performance Computing for Applications in Engineering", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:347:023880", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1272", "source_course_id": "023880", "source_subject_id": "347", "title": "High Performance Computing for Applications in Engineering", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:612:023880", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1272", "source_course_id": "023880", "source_subject_id": "612", "title": "High Performance Computing for Applications in Engineering", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:36237", "term_id": "1272", "source_section_id": "36237", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 110, "enrolled": 55, "waitlisted": 6, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:35928", "term_id": "1272", "source_section_id": "35928", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 130, "enrolled": 54, "waitlisted": 1, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:36235", "term_id": "1272", "source_section_id": "36235", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 110, "enrolled": 1, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:36236", "term_id": "1272", "source_section_id": "36236", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 110, "enrolled": 5, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:36234", "term_id": "1272", "source_section_id": "36234", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 110, "enrolled": 4, "waitlisted": 1, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" } ] ``` ### grade instructors ```json [ { "instructor_uid": "instructor_2a89e605adc37d459f748897", "source": "madgrades", "source_instructor_id": "4002508", "identity_basis": "source_id", "identity_status": "source_identified", "name": "DAN NEGRUT", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 16, "quality": 4.69, "difficulty": 3, "quality_count": 16, "difficulty_count": 16, "profile_id": "rmp:812301", "source_url": "https://www.ratemyprofessors.com/professor/812301", "match_basis": "exact_name", "observed_at": "2026-09-07 16:46:30.629179+00:00", "courses": { "course_63e805b33518ff3fd8dc0a39": { "review_count": 11, "quality": 4.82, "difficulty": 3.09, "quality_count": 11, "difficulty_count": 11 }, "course_16dd91dc41baac6af9c4c95b": { "review_count": 1, "quality": 4, "difficulty": 2, "quality_count": 1, "difficulty_count": 1 }, "course_691928789e696386436f0132": { "review_count": 1, "quality": 5, "difficulty": 3, "quality_count": 1, "difficulty_count": 1 }, "course_30b7af243793fc0540887d4f": { "review_count": 2, "quality": 4.5, "difficulty": 3, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 4.117603213081442, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.811, "graded": 1308, "counts": [ 1002, 189, 68, 33, 13, 3, 0 ], "sections": 230 }, "instructor_url": "/instructors/DAN_NEGRUT--instructor_2a89e605adc37d459f748897" }, { "instructor_uid": "instructor_99e169e78510227a8237cc55", "source": "madgrades", "source_instructor_id": "5215124", "identity_basis": "source_id", "identity_status": "source_identified", "name": "NICHOLAS OLSEN", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.908, "graded": 103, "counts": [ 89, 10, 3, 1, 0, 0, 0 ], "sections": 3 }, "instructor_url": "/instructors/NICHOLAS_OLSEN" }, { "instructor_uid": "instructor_f0c020ba12d2e5500524008f", "source": "madgrades", "source_instructor_id": "5546159", "identity_basis": "source_id", "identity_status": "source_identified", "name": "MILAD RAKHSHA", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.891, "graded": 69, "counts": [ 58, 8, 2, 1, 0, 0, 0 ], "sections": 1 }, "instructor_url": "/instructors/MILAD_RAKHSHA--instructor_f0c020ba12d2e5500524008f" }, { "instructor_uid": "instructor_59566005d723eab7d5962f71", "source": "madgrades", "source_instructor_id": "5738478", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JSON ZHOU", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.926, "graded": 170, "counts": [ 151, 13, 6, 0, 0, 0, 0 ], "sections": 2 }, "instructor_url": "/instructors/JSON_ZHOU--instructor_59566005d723eab7d5962f71" }, { "instructor_uid": "instructor_8d49fe66b3eb445220210b50", "source": "madgrades", "source_instructor_id": "6239625", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JINGQUAN WANG", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.916, "graded": 149, "counts": [ 130, 13, 6, 0, 0, 0, 0 ], "sections": 1 }, "instructor_url": "/instructors/JINGQUAN_WANG" }, { "instructor_uid": "instructor_ef4067d4a5f9b5ae5aa990e6", "source": "madgrades", "source_instructor_id": "6204981", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HARRY ZHANG", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.916, "graded": 149, "counts": [ 130, 13, 6, 0, 0, 0, 0 ], "sections": 1 }, "instructor_url": "/instructors/HARRY_ZHANG--instructor_ef4067d4a5f9b5ae5aa990e6" }, { "instructor_uid": "instructor_f275cc0d0bcf83d0a415d027", "source": "madgrades", "source_instructor_id": "6248478", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HUZAIFA MUSTAFA UNJHAWALA", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.907, "graded": 204, "counts": [ 175, 22, 6, 0, 1, 0, 0 ], "sections": 3 }, "instructor_url": "/instructors/HUZAIFA_MUSTAFA_UNJHAWALA--instructor_f275cc0d0bcf83d0a415d027" }, { "instructor_uid": "instructor_3f9647149c2d1d7925d56432", "source": "madgrades", "source_instructor_id": "6586984", "identity_basis": "source_id", "identity_status": "source_identified", "name": "TSUNG-WEI HUANG", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.837, "graded": 366, "counts": [ 308, 32, 8, 11, 2, 5, 0 ], "sections": 30 }, "instructor_url": "/instructors/TSUNG-WEI_HUANG--instructor_3f9647149c2d1d7925d56432" }, { "instructor_uid": "instructor_6b538cd1085236661960506e", "source": "enrollment", "source_instructor_id": "thuang295", "identity_basis": "netid", "identity_status": "source_identified", "name": "Tsung-Wei Huang", "email": "TSUNG-WEI.HUANG@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "instructor_url": "/instructors/TSUNG-WEI_HUANG" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1142", "term_name": "Fall 2013", "instructors": [ "Dan Negrut" ], "a": 27, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 11, "no_work": 0, "not_reported": 0, "other": 0, "total": 38, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1162", "term_name": "Fall 2015", "instructors": [ "Dan Negrut" ], "a": 58, "ab": 3, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 2, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 64, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1182", "term_name": "Fall 2017", "instructors": [ "Dan Negrut" ], "a": 76, "ab": 10, "b": 3, "bc": 1, "c": 1, "d": 0, "f": 0, "satisfactory": 4, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 95, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1194", "term_name": "Spring 2019", "instructors": [ "Dan Negrut", "MILAD RAKHSHA", "NICHOLAS OLSEN" ], "a": 58, "ab": 8, "b": 2, "bc": 1, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 70, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1204", "term_name": "Spring 2020", "instructors": [ "Dan Negrut" ], "a": 59, "ab": 10, "b": 2, "bc": 1, "c": 0, "d": 0, "f": 0, "satisfactory": 4, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 76, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1232", "term_name": "Fall 2022", "instructors": [ "Dan Negrut" ], "a": 98, "ab": 15, "b": 3, "bc": 2, "c": 0, "d": 0, "f": 0, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 119, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "Dan Negrut", "HARRY ZHANG", "HUZAIFA MUSTAFA UNJHAWALA", "JINGQUAN WANG", "JSON ZHOU" ], "a": 130, "ab": 13, "b": 6, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 5, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 155, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Tsung-Wei Huang" ], "a": 67, "ab": 2, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 69, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Tsung-Wei Huang" ], "a": 108, "ab": 4, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 112, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE/EMA/EP/ME 759", "course_uid": "course_63e805b33518ff3fd8dc0a39", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Dan Negrut" ], "a": 96, "ab": 6, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 2, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 104, "source_aliases": [ "COMPSCI/ECE/EMA/EP/ME 759" ] } ] ``` ### statistics #### gpa 3.93 #### graded 870 #### counts * 777 * 71 * 16 * 5 * 1 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_63e805b33518ff3fd8dc0a39-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_63e805b33518ff3fd8dc0a39-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_63e805b33518ff3fd8dc0a39-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_63e805b33518ff3fd8dc0a39-0.json) * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_63e805b33518ff3fd8dc0a39-1.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_63e805b33518ff3fd8dc0a39-1.json) * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_63e805b33518ff3fd8dc0a39-2.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_63e805b33518ff3fd8dc0a39-2.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_63e805b33518ff3fd8dc0a39-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_63e805b33518ff3fd8dc0a39-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_63e805b33518ff3fd8dc0a39-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_63e805b33518ff3fd8dc0a39-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_63e805b33518ff3fd8dc0a39-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_63e805b33518ff3fd8dc0a39-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.9298850574712643 #### count 870 #### university ##### size 4353 ##### gpa Percentile 80 ##### count Percentile 92 ##### median Count 119 ##### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 13 | false | | 2.8–3.2 | 280 | false | | 3.2–3.6 | 1154 | false | | 3.6–4.0 | 2905 | true | #### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 104, "gpaPercentile": 93, "countPercentile": 79, "medianCount": 217, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 13, "current": false }, { "range": "3.2–3.6", "count": 31, "current": false }, { "range": "3.6–4.0", "count": 60, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 106, "gpaPercentile": 91, "countPercentile": 89, "medianCount": 157.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 5, "current": false }, { "range": "3.2–3.6", "count": 43, "current": false }, { "range": "3.6–4.0", "count": 58, "current": true } ] } }, { "subject": "EMA", "comparison": { "size": 20, "gpaPercentile": 95, "countPercentile": 79, "medianCount": 122.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 6, "current": true } ] } }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 75, "gpaPercentile": 89, "countPercentile": 82, "medianCount": 135, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 35, "current": false }, { "range": "3.6–4.0", "count": 36, "current": true } ] } } ] ``` ### terms #### 1142 ##### term 1142 ##### gpa 4 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | ECE | | | EMA | | | EP | | | ME | | #### 1162 ##### term 1162 ##### gpa 3.9754098360655736 ##### count 61 ##### university ###### size 954 ###### gpa Percentile 95 ###### count Percentile 47 ###### median Count 64.5 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 23 | false | | 2.8–3.2 | 234 | false | | 3.2–3.6 | 350 | false | | 3.6–4.0 | 345 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 35, "gpaPercentile": 94, "countPercentile": 59, "medianCount": 56, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 14, "current": false }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 11, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 32, "gpaPercentile": 100, "countPercentile": 42, "medianCount": 68, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 7, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 27, "gpaPercentile": 96, "countPercentile": 46, "medianCount": 65, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 5, "current": false }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 6, "current": true } ] } } ] ``` #### 1182 ##### term 1182 ##### gpa 3.8736263736263736 ##### count 91 ##### university ###### size 1025 ###### gpa Percentile 87 ###### count Percentile 64 ###### median Count 69 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 21 | false | | 2.8–3.2 | 216 | false | | 3.2–3.6 | 369 | false | | 3.6–4.0 | 418 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 36, "gpaPercentile": 89, "countPercentile": 51, "medianCount": 90.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 13, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 11, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 40, "gpaPercentile": 90, "countPercentile": 67, "medianCount": 63, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 16, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 23, "gpaPercentile": 95, "countPercentile": 59, "medianCount": 88, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 9, "current": true } ] } } ] ``` #### 1194 ##### term 1194 ##### gpa 3.891304347826087 ##### count 69 ##### university ###### size 1040 ###### gpa Percentile 85 ###### count Percentile 51 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 23 | false | | 2.8–3.2 | 220 | false | | 3.2–3.6 | 342 | false | | 3.6–4.0 | 454 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 38, "gpaPercentile": 84, "countPercentile": 35, "medianCount": 92, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 15, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 11, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 36, "gpaPercentile": 91, "countPercentile": 40, "medianCount": 77, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 5, "current": false }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 15, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 23, "gpaPercentile": 100, "countPercentile": 55, "medianCount": 68, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 6, "current": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 7, "current": true } ] } } ] ``` #### 1204 ##### term 1204 ##### gpa 3.8819444444444446 ##### count 72 ##### university ###### size 1012 ###### gpa Percentile 71 ###### count Percentile 55 ###### median Count 65.5 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 1 | false | | 2.8–3.2 | 25 | false | | 3.2–3.6 | 301 | false | | 3.6–4.0 | 685 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 42, "gpaPercentile": 88, "countPercentile": 32, "medianCount": 90.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 19, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 34, "gpaPercentile": 82, "countPercentile": 48, "medianCount": 73.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 0, "current": false }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 25, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 20, "gpaPercentile": 89, "countPercentile": 37, "medianCount": 84, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 0, "current": false }, { "range": "3.2–3.6", "count": 4, "current": false }, { "range": "3.6–4.0", "count": 16, "current": true } ] } } ] ``` #### 1232 ##### term 1232 ##### gpa 3.885593220338983 ##### count 118 ##### university ###### size 1216 ###### gpa Percentile 80 ###### count Percentile 73 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 174 | false | | 3.2–3.6 | 356 | false | | 3.6–4.0 | 670 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 50, "gpaPercentile": 84, "countPercentile": 63, "medianCount": 82.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 19, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 44, "gpaPercentile": 86, "countPercentile": 84, "medianCount": 70, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 25, "gpaPercentile": 92, "countPercentile": 50, "medianCount": 118, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 3, "current": false }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 13, "current": true } ] } } ] ``` #### 1242 ##### term 1242 ##### gpa 3.9161073825503356 ##### count 149 ##### university ###### size 1295 ###### gpa Percentile 83 ###### count Percentile 81 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 11 | false | | 2.8–3.2 | 162 | false | | 3.2–3.6 | 394 | false | | 3.6–4.0 | 726 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 52, "gpaPercentile": 90, "countPercentile": 65, "medianCount": 99, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 20, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 41, "gpaPercentile": 90, "countPercentile": 85, "medianCount": 83, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 8, "current": false }, { "range": "3.2–3.6", "count": 18, "current": false }, { "range": "3.6–4.0", "count": 15, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 31, "gpaPercentile": 93, "countPercentile": 80, "medianCount": 107, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 2, "current": false }, { "range": "3.2–3.6", "count": 13, "current": false }, { "range": "3.6–4.0", "count": 15, "current": true } ] } } ] ``` #### 1252 ##### term 1252 ##### gpa 3.9855072463768115 ##### count 69 ##### university ###### size 1333 ###### gpa Percentile 94 ###### count Percentile 49 ###### median Count 69 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 115 | false | | 3.2–3.6 | 431 | false | | 3.6–4.0 | 773 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 54, "gpaPercentile": 94, "countPercentile": 43, "medianCount": 101, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 8, "current": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 44, "gpaPercentile": 98, "countPercentile": 40, "medianCount": 74, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 28, "gpaPercentile": 100, "countPercentile": 30, "medianCount": 116.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 13, "current": true } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.982142857142857 ##### count 112 ##### university ###### size 1289 ###### gpa Percentile 94 ###### count Percentile 74 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 128 | false | | 3.2–3.6 | 379 | false | | 3.6–4.0 | 765 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 52, "gpaPercentile": 100, "countPercentile": 55, "medianCount": 105, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 24, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 40, "gpaPercentile": 90, "countPercentile": 74, "medianCount": 87.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 8, "current": false }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 16, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 28, "gpaPercentile": 100, "countPercentile": 44, "medianCount": 121.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 3, "current": false }, { "range": "3.2–3.6", "count": 8, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.9705882352941178 ##### count 102 ##### university ###### size 1283 ###### gpa Percentile 91 ###### count Percentile 71 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 20 | false | | 2.8–3.2 | 130 | false | | 3.2–3.6 | 343 | false | | 3.6–4.0 | 789 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 48, "gpaPercentile": 96, "countPercentile": 49, "medianCount": 105.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 7, "current": false }, { "range": "3.2–3.6", "count": 21, "current": false }, { "range": "3.6–4.0", "count": 19, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 45, "gpaPercentile": 95, "countPercentile": 73, "medianCount": 73, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 15, "current": false }, { "range": "3.6–4.0", "count": 25, "current": true } ] } }, { "subject": "EMA", "comparison": null }, { "subject": "EP", "comparison": null }, { "subject": "ME", "comparison": { "size": 25, "gpaPercentile": 96, "countPercentile": 33, "medianCount": 131, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 4, "current": false }, { "range": "3.2–3.6", "count": 7, "current": false }, { "range": "3.6–4.0", "count": 13, "current": true } ] } } ] ``` ### benchmarks #### all ##### school ###### size 4353 ###### gpa 3.6771862758824603 ###### top Share 83.02603068525914 ###### count 119 ##### COMPSCI ###### size 104 ###### gpa 3.5994661825316956 ###### top Share 79.1061431566766 ###### count 217 ##### ECE ###### size 106 ###### gpa 3.603737038676423 ###### top Share 78.68030253482884 ###### count 157.5 ##### EMA ###### size 20 ###### gpa 3.470944712913288 ###### top Share 70.2351822568117 ###### count 122.5 ##### ME ###### size 75 ###### gpa 3.5940153116414035 ###### top Share 77.37533574154723 ###### count 135 #### terms ##### 1142 ###### school ###### size 853 ###### gpa 3.3941849959684913 ###### top Share 65.28450334228523 ###### count 67 ###### COMPSCI ###### size 28 ###### gpa 3.279575360328891 ###### top Share 60.13197427273153 ###### count 47.5 ###### ECE ###### size 34 ###### gpa 3.308741102061444 ###### top Share 59.724830536617226 ###### count 60 ###### ME ###### size 22 ###### gpa 3.2509223940390553 ###### top Share 56.81144579867853 ###### count 73.5 ##### 1162 ###### school ###### size 954 ###### gpa 3.43726781345039 ###### top Share 68.05645304987395 ###### count 64.5 ###### COMPSCI ###### size 35 ###### gpa 3.3323013900568625 ###### top Share 63.38685451839816 ###### count 56 ###### ECE ###### size 32 ###### gpa 3.319518625747047 ###### top Share 59.51472818692325 ###### count 68 ###### ME ###### size 27 ###### gpa 3.419766276244962 ###### top Share 64.02056497575037 ###### count 65 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ###### COMPSCI ###### size 36 ###### gpa 3.352907303323745 ###### top Share 63.88103454195665 ###### count 90.5 ###### ECE ###### size 40 ###### gpa 3.456923604087721 ###### top Share 68.99771043518125 ###### count 63 ###### ME ###### size 23 ###### gpa 3.457465602596896 ###### top Share 69.62313477557635 ###### count 88 ##### 1194 ###### school ###### size 1040 ###### gpa 3.4906527436719808 ###### top Share 71.74728845515045 ###### count 67 ###### COMPSCI ###### size 38 ###### gpa 3.3433846242383978 ###### top Share 63.409438479169644 ###### count 92 ###### ECE ###### size 36 ###### gpa 3.5139370942069434 ###### top Share 73.58293880609176 ###### count 77 ###### ME ###### size 23 ###### gpa 3.411535423691701 ###### top Share 62.97771742929326 ###### count 68 ##### 1204 ###### school ###### size 1012 ###### gpa 3.703747431523761 ###### top Share 84.59811226304916 ###### count 65.5 ###### COMPSCI ###### size 42 ###### gpa 3.6240893265324647 ###### top Share 79.98991493017058 ###### count 90.5 ###### ECE ###### size 34 ###### gpa 3.7346193271517083 ###### top Share 86.80502962000203 ###### count 73.5 ###### ME ###### size 20 ###### gpa 3.669078433787773 ###### top Share 83.33636146963025 ###### count 84 ##### 1232 ###### school ###### size 1216 ###### gpa 3.575457431972425 ###### top Share 77.33712216234007 ###### count 66 ###### COMPSCI ###### size 50 ###### gpa 3.522872390836507 ###### top Share 74.11555010870671 ###### count 82.5 ###### ECE ###### size 44 ###### gpa 3.4583903966894223 ###### top Share 70.01102622146537 ###### count 70 ###### ME ###### size 25 ###### gpa 3.572892556393539 ###### top Share 76.54575303131045 ###### count 118 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### COMPSCI ###### size 52 ###### gpa 3.5206188715369935 ###### top Share 74.2043106737207 ###### count 99 ###### ECE ###### size 41 ###### gpa 3.4916867437115484 ###### top Share 71.95296745580877 ###### count 83 ###### ME ###### size 31 ###### gpa 3.5460868086391497 ###### top Share 75.80892567064664 ###### count 107 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### COMPSCI ###### size 54 ###### gpa 3.5244021201456657 ###### top Share 75.07938169795783 ###### count 101 ###### ECE ###### size 44 ###### gpa 3.5595929340853747 ###### top Share 76.26079811550397 ###### count 74 ###### ME ###### size 28 ###### gpa 3.5912563782704816 ###### top Share 76.82128204846178 ###### count 116.5 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### COMPSCI ###### size 52 ###### gpa 3.482652727664103 ###### top Share 71.33786483648515 ###### count 105 ###### ECE ###### size 40 ###### gpa 3.5198762319632855 ###### top Share 74.0918065550377 ###### count 87.5 ###### ME ###### size 28 ###### gpa 3.6206917860927894 ###### top Share 78.31689014028125 ###### count 121.5 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### COMPSCI ###### size 48 ###### gpa 3.5022746140005943 ###### top Share 73.13318776233326 ###### count 105.5 ###### ECE ###### size 45 ###### gpa 3.5814138447018746 ###### top Share 77.53027985486403 ###### count 73 ###### ME ###### size 25 ###### gpa 3.5110862399220912 ###### top Share 72.3479757717731 ###### count 131 ## instructor Trends ```json [ { "uid": "instructor_2a89e605adc37d459f748897", "name": "DAN NEGRUT", "count": 689, "terms": [ { "term": "1142", "count": 27, "sections": 1, "gpa": 4 }, { "term": "1162", "count": 61, "sections": 1, "gpa": 3.9754098360655736 }, { "term": "1182", "count": 91, "sections": 2, "gpa": 3.8736263736263736 }, { "term": "1194", "count": 69, "sections": 2, "gpa": 3.891304347826087 }, { "term": "1204", "count": 72, "sections": 2, "gpa": 3.8819444444444446 }, { "term": "1232", "count": 118, "sections": 1, "gpa": 3.885593220338983 }, { "term": "1242", "count": 149, "sections": 1, "gpa": 3.9161073825503356 }, { "term": "1264", "count": 102, "sections": 2, "gpa": 3.9705882352941178 } ] }, { "uid": "instructor_3f9647149c2d1d7925d56432", "name": "TSUNG-WEI HUANG", "count": 181, "terms": [ { "term": "1252", "count": 69, "sections": 1, "gpa": 3.9855072463768115 }, { "term": "1254", "count": 112, "sections": 1, "gpa": 3.982142857142857 } ] }, { "uid": "instructor_59566005d723eab7d5962f71", "name": "JSON ZHOU", "count": 149, "terms": [ { "term": "1242", "count": 149, "sections": 1, "gpa": 3.9161073825503356 } ] }, { "uid": "instructor_8d49fe66b3eb445220210b50", "name": "JINGQUAN WANG", "count": 149, "terms": [ { "term": "1242", "count": 149, "sections": 1, "gpa": 3.9161073825503356 } ] }, { "uid": "instructor_ef4067d4a5f9b5ae5aa990e6", "name": "HARRY ZHANG", "count": 149, "terms": [ { "term": "1242", "count": 149, "sections": 1, "gpa": 3.9161073825503356 } ] }, { "uid": "instructor_f275cc0d0bcf83d0a415d027", "name": "HUZAIFA MUSTAFA UNJHAWALA", "count": 149, "terms": [ { "term": "1242", "count": 149, "sections": 1, "gpa": 3.9161073825503356 } ] }, { "uid": "instructor_99e169e78510227a8237cc55", "name": "NICHOLAS OLSEN", "count": 69, "terms": [ { "term": "1194", "count": 69, "sections": 1, "gpa": 3.891304347826087 } ] }, { "uid": "instructor_f0c020ba12d2e5500524008f", "name": "MILAD RAKHSHA", "count": 69, "terms": [ { "term": "1194", "count": 69, "sections": 1, "gpa": 3.891304347826087 } ] } ] ``` ## following None recorded. ## projection ### target 1272 ### gpa 3.9365462350139464 ### grades | grade | percentage | | ----- | ------------------ | | A | 90.18551203539528 | | AB | 7.382790867536371 | | B | 1.9871291615307005 | | BC | 0.4445679355376494 | | C | 0 | | D | 0 | | F | 0 | ### source Terms * 1252 * 1242 * 1232 ### source Count 336 ### same Season true ### historical Range * 3.8855932203389827 * 3.9855072463768115 ### backtest #### terms 3 #### gpa Error 0.04034866135983606 #### mix Error 6.3011769070875845