Ritwik K. Niyogi

I am a Senior Research Scientist | Senior Deep Learning Researcher at MediaTek Research.

I was a Sir Henry Wellcome Post-doctoral Fellow, hosted by University College London. I was at the UCL-Max Planck Centre for Computational Psychiatry and Ageing Research. My Research Sponsor was Dr.Robb Rutledge. My mentor was Professor Nathaniel Daw at the Princeton Neuroscience Institute.

I did my PhD in Machine Learning and Theoretical Neuroscience at the Gatsby Computational Neuroscience Unit, University College London (UCL), supervised by Professor Peter Dayan. I did a minor in Reinforcement Learning with Dr. David Silver.

I was formerly hosted by the University of Oxford, based at the Department of Experimental Psychology, my Research Sponsor was Dr. Mark Walton and Sponsor was Professor Matthew Rushworth.

I previously did the first two parts of my Sir Henry Wellcome fellowship investigating vigour-anergia, reward learning and real-time cost-benefit decision-making at the (1) Solomon H. Snyder Department of Neuroscience and Brain Science Institute, the Johns Hopkins University School of Medicine, (my Research Sponsor was Dr.Jeremiah Cohen ) and (2) Department of Psychiatry, UNC Neuroscience Center, University of North Carolina at Chapel Hill with Research Sponsor Prof. Garret Stuber).

I am an AI Research Scientist interested in resource efficient AI and in applications of AI to difficult societal challenges in Mental Health, drug discovery and economics

Contact

E-mail: ritwik7@gmail.com / ritwik.niyogi@gatsby.ucl.ac.uk

Curriculum Vitae

News

2021

  • Our work Fast dopamine release signals reward rate to mediate vigor has been accepted at CoSyNe,2021.

2020

Research Interests

Machine Learning; Computational Psychiatry; Intelligence in Brains and Machines; Reinforcement learning and stochastic optimal control

In Preparation

Preprints

Publications

  • Ahilan, S., Solomon, R., Breton Y-A, Conover, K., Niyogi, R.K., Shizgal P., Dayan, P. Forgetful inference in a sophisticated world model , PLoS Computational Biology pdf BioArxiv

  • Niyogi, R.K., Shizgal, P., & Dayan, P. Some work and some play: microscopic and macroscopic approaches to labor and leisure , PLoS Computational Biology 10(12): e1003894 (2014) pdf Pubmed

  • Niyogi, R.K., Breton, Y-A, Solomon, R.B., Conover, K., Shizgal, P., & Dayan, P. Optimal indolence: a normative microscopic approach to work and leisure, Journal of the Royal Society Interface,11, 20130969 (2014) pdf Supplementary Information Pubmed

  • Niyogi, R.K. & Wong-Lin, K-F, Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making, PLoS Computational Biology, 9(6):e1003099 (2013) pdf Pubmed

  • Balci, F., Simen, P., Niyogi, R., Saxe, A., Hughes, J.A., Holmes, P., & Cohen, J.D. Acquisition of decision making criteria: accuracy ultimately loses the competition with reward rate, Attention Perception Psychophysics, 73(2), 640-657 (2011) pdf Supplementary Material Pubmed

  • Niyogi, R.K. & English, L.Q. Learning-rate-dependent clustering and self-development in a network of coupled phase oscillators, Physics Review E, 80, 066213 (2009) pdf Pubmed

Theses

  • What to do, when to do it, how long to do it for: a normative microscopic approach to the labour leisure tradeoff (PhD Thesis, University College London)

  • The Source of Suboptimality in Human Performance on Two-Alternative Forced Choice Motion-Discrimination Decision-Making Tasks (Neuroscience Honors Thesis, Dickinson College)

  • Dynamical Effects of Non-Linearities and Time-Varying Gain Modulation in Neurally Plausible Network Models of Perceptual Decision-Making Tasks (Mathematics Honors Thesis, Dickinson College)

  • Synchronization and Hebbian Learning in a Network of Coupled Neural Phase Oscillators (Physics Honors Thesis, Dickinson College)

Collaborators

I have had the privilege of working with and being mentored by

I follow (and often preach) the work of my friends:

Teaching

Links

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