# BME 770: Nanotechnology in Neuroscience | UW–Madison [View on UW Courses](https://uwcourses.com/courses/BME_770) ## 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 6bbe86fb848c58b241015f287c8238878ef7fc9b560bb90d786210f10f40b996 ### course id BME 770 ### course uid course\_0e32a7555473b798e1fe2787 ### catalog version id 3ba99623f07e03b80ad8348f5b01822bf6a1a80d2b7fcd5257892e9909a016c2 ### course number 770 ### subjects * BME ### title NANOTECHNOLOGY IN NEUROSCIENCE ### description Principles of micro- and nano-technology applied to neuroscience, including technological approaches applied to both in vitro and in vivo neurobiological experimentation and neurology. Fundamentals of recording and processing neural signals using nanoscale synthesis processes and technologies including nanostructured electrodes and their electrical, mechanical, and biochemical properties, active and passive 2D and 3D multielectrode arrays (MEAs), nanoscale transistors for subcellular recordings, nanoparticles, and nano-synthesized agents for recording and stimulating neural activity. Relevant theory of cell electrode coupling, electrophysiology, and neurochemical signaling. Knowledge of microfabrication technologies and biology \[such as inB M E 550] recommended. ### requirements text Graduate/professional standing ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 9f948e771b45b54f84476069c9cba69b4cc49c56b93bd7c979a73e8414238c33 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Covers principles of micro- and nano-technology applied to neuroscience, including neural signal recording and processing. ### llm topics * In vitro and in vivo neurobiological experimentation. * Multielectrode arrays and nanoscale transistors. * Cell electrode coupling, electrophysiology, and neurochemical signaling. ### llm skills * Applying micro- and nano-technology to neurobiological experimentation. * Recording and processing neural signals using nanoscale technologies. * Understanding properties of nanostructured electrodes and arrays. ### llm assumed background * Microfabrication technologies and biology, including MEMS methodology and biological system integration. ### llm search phrases * micro-technology neuroscience * neural signal processing nanoscale * neurotechnology graduate course ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash db297dbdef4b4f21c7a95e8e6d3ad0ec99924adcbc81e910dd52f3d842e42a70 #### course id BME 770 #### current instructors None recorded. #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered false #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2026: 4.00 GPA, 100.0% A/AB (n=16 letter grades). ```json { "citations": [ { "course_id": "BME 770", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "4b7cd770-fec0-364e-9d25-484fb8aa96eb", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history None recorded. #### 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 None recorded. ### offerings None recorded. ### sections None recorded. ### grade instructors ```json [ { "instructor_uid": "instructor_53917637db609dccd892558a", "source": "madgrades", "source_instructor_id": "5863604", "identity_basis": "source_id", "identity_status": "source_identified", "name": "XIAOXUAN REN", "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": 4, "graded": 29, "counts": [ 29, 0, 0, 0, 0, 0, 0 ], "sections": 2 }, "instructor_url": "/instructors/XIAOXUAN_REN" }, { "instructor_uid": "instructor_b43cf1f88115c39040c31782", "source": "madgrades", "source_instructor_id": "6180480", "identity_basis": "source_id", "identity_status": "source_identified", "name": "AVIAD HAI", "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": 3.961, "graded": 267, "counts": [ 247, 19, 1, 0, 0, 0, 0 ], "sections": 70 }, "instructor_url": "/instructors/AVIAD_HAI--instructor_b43cf1f88115c39040c31782" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "BME 770", "course_uid": "course_0e32a7555473b798e1fe2787", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Aviad Hai", "XIAOXUAN REN" ], "a": 16, "ab": 0, "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": 16, "source_aliases": [ "BME 770" ] } ] ``` ### statistics #### gpa 4 #### graded 16 #### counts * 16 * 0 * 0 * 0 * 0 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_0e32a7555473b798e1fe2787-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_0e32a7555473b798e1fe2787-0.json) #### traces * 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count 56.5 #### terms ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### BME ###### size 14 ###### gpa 3.7528996650219564 ###### top Share 87.71281693433329 ###### count 56.5 ## instructor Trends ```json [ { "uid": "instructor_53917637db609dccd892558a", "name": "XIAOXUAN REN", "count": 16, "terms": [ { "term": "1264", "count": 16, "sections": 1, "gpa": 4 } ] }, { "uid": "instructor_b43cf1f88115c39040c31782", "name": "AVIAD HAI", "count": 16, "terms": [ { "term": "1264", "count": 16, "sections": 1, "gpa": 4 } ] } ] ``` ## following None recorded.