Nishanth Vemgal
Research Scientist at ExperienceFlow.ai
Montreal, Quebec, Canada
Summary
👤
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 (47)
algorithms10
grid-world10
gymnasium10
reinforcement-learning10
ranking10
react9
science9
computer-science9
actor-critic8
gpt8
cuda8
inference8
llm8
amd8
openai8
Programming languages (7)
Github contributions (5)
NishanthVAnand/Preferential-Temporal-Difference-Learning
Mar 2020 - Jun 2021
Contributions:18 commits, 3 pushes in 1 year 2 months
NishanthVAnand/Craftax_Baselines
Apr 2025 - Apr 2025
Contributions:59 pushes in 22 days
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