Ayan Chakrabarti

I am a Senior Staff Research Scientist on the GenAI team at Google DeepMind, working on improving the capability and training and inference efficiency of large language models.

I received my PhD advised by Todd Zickler at Harvard University, and did my undergraduate studies at IIT Madras. Before joining Google, I was an assistant professor of computer science at WashU, a research assistant professor at the Toyota Technological Institute at Chicago, and a post-doctoral fellow at Harvard.

Photo of Ayan Chakrabarti

Ayan Chakrabarti

I am a Senior Staff Research Scientist on the GenAI team at Google DeepMind, working on improving the capability and training and inference efficiency of large language models.

I received my PhD advised by Todd Zickler at Harvard University, and did my undergraduate studies at IIT Madras. Before joining Google, I was an assistant professor of computer science at WashU, a research assistant professor at the Toyota Technological Institute at Chicago, and a post-doctoral fellow at Harvard.

Google Scholar / LinkedIn / E-mail

Research

Analyzing Similarity Metrics for Data Selection for Language Model Pretraining

NeurIPS 2025

Dylan Sam, Ayan Chakrabarti, Afshin Rostamizadeh, Srikumar Ramalingam, Gui Citovsky, Sanjiv Kumar

paper

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long context, and Next Generation Agentic Capabilities

arXiv 2025

Gemini Team

paper

Gemma 3 Technical Report

arXiv 2025

Gemma Team

paper

LatentCRF: Continuous CRF for Efficient Latent Diffusion

arXiv 2024

Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit, Ayan Chakrabarti, Daniel Glasner, Michael S. Ryoo, Srikumar Ramalingam, Sanjiv Kumar

paper

SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection

arXiv 2024

Ke Ye, Heinrich Jiang, Afshin Rostamizadeh, Ayan Chakrabarti, Giulia DeSalvo, Jean-François Kagy, Lazaros Karydas, Gui Citovsky, Sanjiv Kumar

paper

MarkovGen: Structured Prediction for Efficient Text-to-Image Generation

CVPR 2024

Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar

paper

Rethinking FID: Towards a Better Evaluation Metric for Image Generation

CVPR 2024

Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar

paper

Benchmarking Robustness to Adversarial Image Obfuscations

NeurIPS 2023

Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

paper benchmark

Tree Recovery by Dynamic Programming

PAMI 2023

Gustavo Gratacós, Ayan Chakrabarti, Tao Ju

paper appendices code + data

Leveraging Redundancy in Attention with Reuse Transformers

arXiv 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar

paper

Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation

arXiv 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit

paper

Understanding Robustness of Transformers for Image Classification

ICCV 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Daniel Glasner, Daliang Li, Thomas Unterthiner, Andreas Veit

paper

Can Optical Trojans Assist Adversarial Perturbations?

AROW (ICCV) 2021

Adith Boloor, Tong Wu, Patrick Naughton, Ayan Chakrabarti, Xuan Zhang, Yevgeniy Vorobeychik

paper

Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments

CVPR 2021

Zhihao Xia, Michaël Gharbi, Federico Perazzi, Kalyan Sunkavalli, Ayan Chakrabarti

paper project

Real-Time Edge Classification: Optimal Offloading under Token Bucket Constraints

SEC 2021

Ayan Chakrabarti, Roch Guérin, Chenyang Lu, Jiangnan Liu

arxiv code

Generating and Exploiting Probabilistic Monocular Depth Estimates

CVPR 2020 (oral)

Zhihao Xia, Patrick Sullivan, Ayan Chakrabarti

paper project

Basis Prediction Networks for Effective Burst Denoising with Large Kernels

CVPR 2020

Zhihao Xia, Federico Perazzi, Michaël Gharbi, Kalyan Sunkavalli, Ayan Chakrabarti

paper project

Protecting Geolocation Privacy of Photo Collections

AAAI 2020

Jinghan Yang, Ayan Chakrabarti, Yevgeniy Vorobeychik

paper project

Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures

WACV 2020

Kyle Yee, Ayan Chakrabarti

paper project

Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising

WACV 2020

Zhihao Xia, Ayan Chakrabarti

paper project

Training Image Estimators without Image Ground-Truth

NeurIPS 2019 (spotlight)

Zhihao Xia, Ayan Chakrabarti

paper project

Backprop with Approximate Activations for Memory-efficient Network Training

NeurIPS 2019

Ayan Chakrabarti, Benjamin Moseley

paper project

Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices

ICCAD 2019 + TCAD

Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang

ICCAD TCAD

Learning to Separate Multiple Illuminants in a Single Image

CVPR 2019

Zhuo Hui, Ayan Chakrabarti, Kalyan Sunkavalli, Aswin C. Sankaranarayanan

paper project

Jointly Learning to Construct and Control Agents using Deep Reinforcement Learning

ICRA 2019

Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter

paper project

NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support

DATE 2019 + TCAD

Weidong Cao, Xin He, Ayan Chakrabarti, Xuan Zhang

DATE TCAD

Learning Privacy Preserving Encodings through Adversarial Training

WACV 2019

Francesco Pittaluga, Sanjeev J. Koppal, Ayan Chakrabarti

paper

Stabilizing GAN Training with Multiple Random Projections

arXiv 2018

Behnam Neyshabur, Srinadh Bhojanapalli, Ayan Chakrabarti

paper project

Jointly Optimizing Placement and Inference for Beacon-based Localization

IROS 2017

Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter

paper project

Examining the Impact of Blur on Recognition by Convolutional Networks

arXiv 2017

Igor Vasiljevic, Ayan Chakrabarti, Gregory Shakhnarovich

paper

Learning Sensor Multiplexing Design through Back-propagation

NeurIPS 2016

Ayan Chakrabarti

paper project

Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

NeurIPS 2016

Ayan Chakrabarti, Jingyu Shao, Gregory Shakhnarovich

paper project

Single-image RGB Photometric Stereo With Spatially-varying Albedo

3DV 2016 (oral)

Ayan Chakrabarti, Kalyan Sunkavalli

paper project

A Neural Approach to Blind Motion Deblurring

ECCV 2016

Ayan Chakrabarti

paper project

Color Constancy by Learning to Predict Chromaticity from Luminance

NeurIPS 2015 (spotlight)

Ayan Chakrabarti

paper project

Low-level Vision by Consensus in a Spatial Hierarchy of Regions

CVPR 2015

Ayan Chakrabarti, Ying Xiong, Steven J. Gortler, Todd Zickler

paper project

From Shading to Local Shape

PAMI 2015

Ying Xiong, Ayan Chakrabarti, Ronen Basri, Steven J. Gortler, David W. Jacobs, Todd Zickler

paper project

Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images

PAMI 2014

Ayan Chakrabarti, Ying Xiong, Baochen Sun, Trevor Darrell, Daniel Scharstein, Todd Zickler, Kate Saenko

paper project

Rethinking Color Cameras

ICCP 2014

Ayan Chakrabarti, William T. Freeman, Todd Zickler

paper project

Depth and Deblurring from a Spectrally-varying Depth-of-Field

ECCV 2012

Ayan Chakrabarti, Todd Zickler

paper project video

Color Constancy with Spatio-Spectral Statistics

PAMI 2012

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper project

Statistics of Real-World Hyperspectral Images

CVPR 2011

Ayan Chakrabarti, Todd Zickler

paper project

Learning Object Color Models from Multi-view Constraints

CVPR 2011

Trevor Owens, Kate Saenko, Ayan Chakrabarti, Ying Xiong, Todd Zickler, Trevor Darrell

paper

Analyzing Spatially-varying Blur

CVPR 2010

Ayan Chakrabarti, Todd Zickler, William T. Freeman

paper project

An Empirical Camera Model for Internet Color Vision

BMVC 2009

Ayan Chakrabarti, Daniel Scharstein, Todd Zickler

paper project

Color Constancy Beyond Bags of Pixels

CVPR 2008

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper

Effective Separation of Sparse and Non-sparse Image Features for Denoising

ICASSP 2008

Ayan Chakrabarti, Keigo Hirakawa

paper

Super-Resolution of Face Images Using Kernel PCA-Based Prior

IEEE Transactions on Multimedia 2007

Ayan Chakrabarti, A.N. Rajagopalan, Rama Chellappa

paper

Visual Inference with Statistical Models for Color and Texture

Ph.D. Dissertation, Harvard University, 2011

Ayan Chakrabarti

pdf

Teaching

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