Sagnik Majumder (Preferred)
Sagnik Majumder
University of Texas, Austin
Names
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Emails
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.
****@cs.utexas.edu
, ****@gmail.com
, ****@ccc.cs.uni-frankfurt.de
Personal Links
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Education & Career History
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PhD student
University of Texas, Austin (utexas.edu)
2021 – 2025
MS student
University of Texas, Austin (utexas.edu)
2019 – 2021
Research assistant
Goethe University (uni-frankfurt.de)
2018 – 2019
Undergrad student
BITS Pilani, BITS Pilani (pilani.bits-pilani.ac.in)
2014 – 2018
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
PhD Advisor
Kristen Grauman
****@cs.utexas.edu
2020 – 2025
Coauthor
Changan Chen
****@cs.utexas.edu
2020 – 2025
Coauthor
Ziad Al-Halah
****@gmail.com
2020 – 2025
Coauthor
Santhosh Kumar Ramakrishnan
****@cs.utexas.edu
2020 – 2025
Coauthor
Ruohan Gao
****@cs.stanford.edu
2020 – 2021
Coauthor
Greg Durrett
****@cs.utexas.edu
2019 – 2021
Coauthor
Chinmoy Samant
****@cs.utexas.edu
2019 – 2021
Coauthor
Visvanathan Ramesh
****@em.uni-frankfurt.de
2017 – 2021
Coauthor
Martin Mundt
****@em.uni-frankfurt.de
2017 – 2021
Coauthor
Iuliia Pliushch
****@em.uni-frankfurt.de
2017 – 2021
Coauthor
Rishabh Bhardwaj
****@pilani.bits-pilani.ac.in
2017 – 2020
Coauthor
Christoph von der Malsburg
****@fias.uni-frankfurt.de
2017 – 2019
Coauthor
Sreenivas Narasimha Murali
****@fias.uni-frankfurt.de
2017 – 2019
Coauthor
Panagiotis Panetsos
****@egnatia.gr
2017 – 2019
Coauthor
Surekha Bhanot
****@pilani.bits-pilani.ac.in
2017 – 2017
Coauthor
Aashish Richhariya
****@pilani.bits-pilani.ac.in
2017 – 2017
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing
Audio-visual learning
2019 – Present
Multi-modal scene understanding
2019 – Present
Egocentric perception
2019 – Present
Active learning
2019 – Present