Biography
I am a Staff Machine Learning Researcher at Qualcomm AI Research. My research interests lie in the areas of Neural Reasoning, Embodied Systems and Generative Models. Previously, I was a Postdoc at the University of Tuebingen working in the Autonomous Vision Group. Before that I was a PhD student at the Max Planck Institut für Informatik, Saarbrücken, advised by Dr. Bernt Schiele and Dr. Mario Fritz. I completed my Master’s Thesis at Saarland University under the supervision of Dr. Jilles Vreeken in the area of Algorithmic Data Mining and my Bachelors degree at the National Institute of Technology, Karnataka, India.
News
- DiMA to be presented at NeurIPS 2025 Workshop on Efficient Reasoning.
- Organizing the CVPR 2025 Workshop on Vision-based Assistants in the Real-World.
Publications
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Apratim Bhattacharyya*, Bicheng Xu*, Sanjay Haresh, Reza Pourreza, Litian Liu, Sunny Panchal, Leonid Sigal, Roland Memisevic Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance? (*joint first authorship) NeurIPS, 2025 (Coming Soon!) -
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Litian Liu, Reza Pourreza, Sunny Panchal, Apratim Bhattacharyya, Yao Qin, Roland Memisevic Enhancing Hallucination Detection through Noise Injection. Paper -
Rajeev Yasarla, Shizhong Han, Hsin-Pai Cheng, Litian Liu, Shweta Mahajan, Apratim Bhattacharyya, Yunxiao Shi, Risheek Garrepalli, Hong Cai, Fatih Porikli RoCA: Robust Cross-Domain End-to-End Autonomous Driving. Paper -
Deepti Hegde, Rajeev Yasarla, Hong Cai, Shizhong Han, Apratim Bhattacharyya, Shweta Mahajan, Litian Liu, Risheek Garrepalli, Vishal M Patel, Fatih Porikli Distilling Multi-modal Large Language Models for Autonomous Driving. CVPR, 2025. Paper -
Sunny Panchal* , Apratim Bhattacharyya*, Guillaume Berger, Antoine Mercier, Cornelius Böhm, Florian Dietrichkeit, Reza Pourreza, Xuanlin Li, Pulkit Madan, Mingu Lee, Mark Todorovich, Ingo Bax, Roland Memisevic Live Fitness Coaching as a Testbed for Situated Interaction. (*joint first authorship) NeurIPS (D&B Track), 2024. Paper; Data; Code -
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Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Reza Pourreza, Pulkit Madan, Roland Memisevic Look, Remember and Reason: Grounded Reasoning in Videos with Language Models. ICLR, 2024. Paper -
Reza Pourreza, Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Pulkit Madan, Roland Memisevic Painter: Teaching Auto-regressive Language Models to Draw Sketches. ICCV Workshops, 2023. Paper -
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients. ECCV, 2022 (Oral) Paper; Project Page -
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Apratim Bhattacharyya, Christoph-Nikolas Straehle, Mario Fritz, Bernt Schiele Haar Wavelet based Block Autoregressive Flows for Trajectories. GCPR, 2020. (Oral) Paper -
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Ahmed Salem, Apratim Bhattacharyya, Michael Backes, Mario Fritz, Yang Zhang Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning. USENIX Security, 2020. Paper -
Apratim Bhattacharyya, Michael Hanselmann, Mario Fritz, Bernt Schiele, Christoph-Nikolas Straehle Conditional Flow Variational Autoencoders for Structured Sequence Prediction. ML4AD @ NeurIPS, 2019 (Oral). Paper -
Apratim Bhattacharyya, Mario Fritz, Bernt Schiele Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods. ICLR, 2019. Paper; Code + Data -
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Apratim Bhattacharyya, Mario Fritz, Bernt Schiele Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty. CVPR, 2018. Paper; Code + Data -
Apratim Bhattacharyya, Mateusz Malinowski, Bernt Schiele, Mario Fritz Long Term Image Boundary Prediction. AAAI, 2018. Paper -
Apratim Bhattacharyya, Jilles Vreeken Efficiently Summarising Event Sequences with Rich Interleaving Patterns. SDM, 2017. Paper