Research Scholar (2020 - Present)
Industrial Engineering and Operations Research IIT Bombay
Office: PhD lab, Third Floor, IEOR buildiing, IIT Bombay,
Powai, Mumbai, Maharashtra - 400076
Email: pintuk@iitb.ac.in
pintupampam@gmail.com
CV: Link
Supervisor: Prof. N. Hemachandra
Research Interest
Representation learning, Graph representation learning
Academic Background
B.Sc.(H) Mathematics, Motilal Nehru College, University of Delhi
M.Sc. Mathematics, IIT Jodhpur, Master's thesis topic - "Dynamics of S-unimodal maps" under supervision of Prof. V V M S Chandramouli
Awards and Fellowships
- Prime Minister Research Fellow January 2021 - Present
- CSIR Junior Research Fellow January 2020 - December 2020. Qualified CSIR-UGC(NET) JRF in Mathematical Science in 2018
- Silver Medal for scoring highest marks in M.Sc. Mathematics batch, Indian Institute of Technology Jodhpur,2019
- Qualified GATE 2019 in Mathematics
- Qualified JAM in Mathematics and Mathematical Statistics in 2017
- Awarded CSSS during Bachelors and Masters,2014-2019
Teaching and TAship
- IE792: Communication Skills II. Autumn 2020
- IE683: Topics in Learning Theory. Spring 2021 with Prof. N. Hemachandra
- IE643: Deep Learning: Theory and Practice. Autumn 2021 with Prof. P. Balamurugan
- MAT2321: Probability Theory. Autumn 2021 at ICT Mumbai with Prof. Amiya Ranjan Bhowmick
- IE622: Probability and Stochastic Process -II. Spring 2022 with Prof. N. Hemachandra
- MAT2305: Stochastic Process. Spring 2022 at ICT Mumbai with Prof. Amiya Ranjan Bhomwick
- NPTEL PMRF TA: Introduction to Machine Learning taught by Prof Sudeshna Sarkar. Link to tutorials (Videos, Slides )
- IE643: Deep Learning: Theory and Practice. Autumn 2022 with Prof. P. Balamurugan
- NPTEL PMRF TA: Basic Linear Algebra taught by Prof I. K. Rana. Link to tutorials (Videos, Slides )
- IE614: Linear Systems. Spring 2023 with Prof. Vishnu Narayanan
- NPTEL PMRF TA: Essential Mathematics for Machine Learning taught by Prof. S.K. Gupta and Prof. Sanjeev Kumar. Link to tutorials (Videos, Slides)
- IE609: Mathematical Optimisation Techniques, Autumn 2023 with Prof. Vishnu Narayanan
Courses (C-Credit, A-Audit, NC-Non Credit)
- Spring 2020: Introduction to Machine Learning(C), Probabilistic Models(C), Decision Analysis and Game Theory(C), IEOR Lab(C), Communication Skills -I(NC), Communication Skills -II(NC)
- Autumn 2021: Learning with Graphs(C), Mathematical Optimisation Techniques(C), Deep Learning - Theory and Practice(C),
Topics in Learning Algorithms(C), Seminar(C) - "Graph Node Embedding",
Foundations of Machine Learning(A), Engineering Statistics(A) - Spring 2021: Probability and Stochastic Processes II(C), Simulation Modeling and Analysis(C)