Rahul Nadkarni

Ph.D. student, Computer Science & Engineering
M.S. Computer Science & Engineering, 2017
University of Washington

B.S. Electrical Engineering & Computer Science, 2015
B.S. Bioengineering, 2015
University of California, Berkeley

curriculum vitae
Google Scholar
I am a second-year Ph.D. student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, advised by Emily Fox and a member of the MODE Lab. My research interests are in statistical machine learning applied to scientific data, particularly in neuroscience. My undergraduate research was in the Brain-Machine Interface Systems Lab at UC Berkeley, advised by Jose Carmena.


Sparse plus low-rank graphical models of time series for functional connectivity in MEG
Nicholas J. Foti, Rahul Nadkarni, Adrian KC Lee, and Emily B. Fox
2nd SIGKDD Workshop on Mining and Learning from Time Series, 2016
pdf talk slides


Autumn 2015 Statistical Inference (STAT 512)
Winter 2016 Graphical Models (CSE 515), Natural Language Processing (CSE 517)
Spring 2016 Machine Learning for Big Data (CSE 547)
Autumn 2016 Convex Optimization (EE 578), Databases (CSE 544)
Winter 2017 Computational Neuroscience (CSE 528), Algorithms (CSE 521)
Spring 2017 Computer Vision (CSE 576)


Autumn 2015 Teaching Assistant, Data Structures and Algorithms (CSE 373)
Winter 2016 Teaching Assistant, Data Structures and Algorithms (CSE 373)
Spring 2016 Teaching Assistant, Introduction to Artificial Intelligence (CSE 415)