I am a Ph.D. student at the Center for Data Science at New York University, advised by Prof. Carlos Fernandez-Granda and Prof. Eero P Simoncelli. I am a member of the Laboratory for Computational Vision and Math and Data. I am broadly interested in computer vision, deep learning and signal processing.

Previously, I obtained my B.Tech in Electrical Engineering from Indian Institute of Technology Madras, where Prof. Kaushik Mitra supervised my bachelor’s thesis. I interned at IST Austria mentored by Dr. Gasper Tkacik during the summer of 2017 and at the Flatiron Institute mentored by Dr. Dmitri Chklovskii and Prof. Cengiz Pehlevan during the summer of 2016. Here’s my CV

Publications

  • Unsupervised Deep Video Denoising
    Dev Sheth*, Sreyas Mohan*, Joshua L. Vincent,Ramon Manzorro, Peter A. Crozier, Mitesh Khapra, Eero P. Simoncelli, Carlos Fernandez-Granda
    [ Paper ] [ Website ]
  • Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy.
    Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang, Dev Yashpal Sheth, Eero P. Simoncelli, David S. Matteson, Peter A. Crozier, Carlos Fernandez-Granda
    [ Paper ] [ Website ] [ Code and Dataset ]
  • Be Like Water: Robustness to Extraneous Variables Via Adaptive Feature Normalization.
    Aakash Kaku*, Sreyas Mohan*, Avinash Parnandi, Heidi Schambra, Carlos Fernandez-Granda
    [Paper]
  • Robust and Interpretable Blind Image Denoising via Bias-free Convolutional Neural Networks.
    Sreyas Mohan*, Zahra Kadkhodaie*, Eero Simoncelli, Carlos Fernandez-Granda
    Proc. International Conference on Learning Representations (ICLR), 2020
    Solving Inverse Problems with Deep Networks Workshop, Neural Information Processing Systems (NeurIPS), Vancouver (Canada) 2019
    [ Paper ] [ Website ] [ Code ]
  • Data-driven Estimation of Sinusoid Frequencies.
    Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
    Proc. 33rd Conference on Neural Information Processing Systems (NeurIPS), Vancouver (Canada) 2019
    [ Paper ] [ Website ] [ Code ]
  • Automatic Knee Segmentation using Diffusion Weighted MRI.
    Alejandra Duarte *, Chaitra Hegde *, Aakash Kaku *, Sreyas Mohan*, Jose G Raya
    Medical Imaging Meets NeurIPS, Neural Information Processing Systems (NeurIPS), Vancouver (Canada) 2019 (Extended Abstract)
    [ Paper ] [ Code ]
  • Data Driven Coded Aperture Design for Depth Recovery.
    Prasan Shedligeri, Sreyas Mohan, Kaushik Mitra
    IEEE International Conference on Image Processing (ICIP), Sep 2017, Beijing, China.
    [ Paper ] [ Website ]
  • Blind Nonnegative Source Separation Using Biological Neural Networks.
    Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii
    Neural computation, vol. 29, no. 11, pp. 2925–2954, 2017
    COSYNE, Salt Lake City, Utah, 2017 (Extended Abstract)
    [ Paper ] [ Extended Abstract] [ Video Demo ]

Teaching

At NYU

Elsewhere

  • Kigali, Rwanda: NLP with Deep Learning at the African Institute of Mathematical Sciences, Rwanda. (March 2019, 2020).
  • IIT Madras, India: EE5177 Machine Learning for Computer Vision (Spring 2017) for Prof. Kaushik Mitra
  • Chennai, India: IIT for Villages - Volunteered to teach Physics and Mathematics for Higher Secondary School students from underprivileged sections of the society (2013-2017)

Service