Siba Smarak Panigrahi
Email: siba.panigrahi@mail.mcgill.ca
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I am a second year M.Sc. (Thesis) student at McGill University and Mila under the supervision of Prof. Siamak Ravanbakhsh.
My research interests span geometric deep learning, generative models, and computer vision. Currently, I am also a visiting researcher at ServiceNow Research
in the Multimodal Foundation Models team, building foundation model for structured document understanding.
Previously, I was a Research Intern at PROSE at Microsoft, working on
designing algorithms and evaluation set-ups for email classification in real-world (online) settings. I was fortunate to work on topological data analysis at
Adobe Research, India and on explainability in pre-trained language models at
INK-Lab, University of Southern California
under Prof. Xiang Ren.
I earned my B. Tech. in Computer Science and Engineering from Indian Institute of Technology Kharagpur.
I was part of the CVIR Lab under the supervision of
Prof. Abir Das and Dr. Rameswar Panda where I worked on contextual
bias and multimodal learning problems.
Other:
Advice on Grad Applications |
Montreal, Canada |
Banff, Canada |
ML Reproducibility Challenge (MLRC) |
Summer Schools
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![ImprovedEquiPretrainingCVPR2024](images/ImprovedEquiPretrainingCVPR2024.png) |
Improved Canonicalization for Model Agnostic Equivariance
Siba Smarak Panigrahi, Arnab Kumar Mondal
Equivariant Vision (EquiVision) workshop (CVPR) 2024
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![KoopmanRLarXiv2023](images/KoopmanRLarXiv2023.png) |
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh
International Conference on Learning Representations (ICLR) 2024;
European Workshop on Reinforcement Learning (EWRL) 2023
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![EquiPretrainingNeurips2023](images/EquiPretrainingNeurips2023.png) |
Equivariant Adaptation of Large Pre-Trained Models
Arnab Kumar Mondal*, Siba Smarak Panigrahi*, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh
Conference on Neural Information Processing Systems (NeurIPS) 2023
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![VavRC2021](images/VavRC2021.png) |
[Re]: Value Alignment Verification
Siba Smarak Panigrahi*, Sohan Patnaik*
The ML Reproducibility Challenge (MLRC), 2021;
NeurIPS Journal Showcase Track, 2022; NeurIPS Spotlight, 2022
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![ArgminingEMNLP2021](images/ArgminingEMNLP2021.png) |
Leveraging Pretrained Language Models for Key Point Matching
Manav Nitin Kapadnis*, Sohan Patnaik*, Siba Smarak Panigrahi*, Varun Madhavan*, and Abhilash Nandy
8th workshop on ArgumentMining at Empirical Methods in Natural Language Processing (EMNLP), 2021
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![EmotionIACC2020](images/EmotionIACC2020.PNG) |
Multi-class Emotion Classification Using EEG Signals
Divya Acharya, Riddhi Jain, Siba Smarak Panigrahi, Rahul Sahni, Siddhi Jain, Sanika Prashant Deshmukh, and Arpit Bhardwaj
10th International Advance Computing Conference (IACC), 2020
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![EquiadaptGitHub2024](images/EquiadaptGitHub2024.png) |
EquiAdapt
Library to make any existing neural network architecture equivariant.
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