Nishanth Vemgal
Ph.D. Researcher - McGill University Mila
Montreal, Quebec, Canada
Summary
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Senior🎓
Top SchoolNishanth Vemgal is a Ph.D. researcher at McGill University and Mila with a decade of experience building novel continual reinforcement learning algorithms inspired by neuroscience, including publications at NeurIPS and ICML. He developed a value-decomposition framework separating permanent and transient components to speed adaptation in non-stationary environments and introduced Preferential Temporal Difference Learning for efficient estimation under partial observability. Beyond research, he co-instructs graduate RL courses, co-supervises theses, and led the mentorship-driven AIF-GEN project that produced an ICML workshop paper, demonstrating a blend of technical leadership and community building. His industry background in deploying RL and anomaly-detection systems at Fractal Analytics gives him a practical bent for taking research ideas toward real-world impact.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering (BE) Telecommunications Engineering, Bachelor of Engineering (BE) Telecommunications Engineering at PES UniversityDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at McGill University
English, Kannada, Telugu, Hindi
Github Skills (59)
grid-world10
gymnasium10
reinforcement-learning10
ranking10
q-learning10
science10
computer-science10
machine-learning9
grid9
deep-learning9
react9
cuda9
deep-reinforcement-learning9
actor-critic8
approximation8
Programming languages (5)
Github contributions (5)
NishanthVAnand/nishanthvanand.github.io
Oct 2019 - Jul 2024
personal website
Contributions:20 pushes, 2 branches in 4 years 9 months
NishanthVAnand/Preferential-Temporal-Difference-Learning
Mar 2020 - Jun 2021
Contributions:18 commits, 3 pushes in 1 year 2 months
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