Education
- Ph.D in Computer Science, Northwestern University, 2021-Present
- Masters in Computer Science, Northwestern University, 2021- 2023
- Masters of Mathematics(MMath), Indian Statistical Institute(Kolkata), 2020
- Bachelors of Science(hons) in Mathematics and Computer Science, Chennai Mathematical Institute, 2018
Internships
Summer 2026: DoorDash as a Machine Learning Engineer in the Ads Recommendations team
- Summer 2025: Pinterest as a Machine Learning Engineer in the HomeFeed Recommendations team
- Developed and deployed PinRec, a generative AI–based ranking model to replace Pinterest’s legacy deep learning system (pinnability), applied across search, ranking, and retrieval. Recommendation from my manager!
- Improved model performance beyond deep learning baselines by driving gains in repins, shares, and clicks through innovations such as user action sampling, role embeddings, and advanced architectures.
- Summer 2024: Research Internship at Nokia Bell Labs
- Our paper Personalized Federated Learning through Clustering of Loss Vector Embeddings accepted in International Conference on Machine Learning (ICML 2026)
- Tech stack: Python, Numpy, Pandas, Scikeat-Learn, PyTorch, Matplotlib, Seaborn, Git
- Summer 2023: Research Intern
- The Institute for Data, Econometrics, Algorithms, and Learning
- Project: Discrepancy Theory
- Supervisor: Vishesh Jain
- Summer 2019: Research Intern
- Indian Statistical Institute, Kolkata, 2019
- Duties included: Completing a project on Coding Theory
- Supervisor: Sourav Chakraborty
- Fall 2017: Research Intern
- Harish Chandra Research Institute, Allahabad, 2017
- Project: Additive Combinatorics and Number Theory
- Supervisor: Gyan Prakash
- Fall 2016: Research Intern
- Indian Statistical Institute, Kolkata, 2016
- Project: Lattice Cryptography
- Supervisor: Rishiraj Bhattacharyya
Courses Completed at Northwestern
- 2021: Topics in Probability
- 2021: Randomized Algorithms
- 2021: Mechanism Design
- 2022: Graduate Algorithms
- 2022: Foundations of Quantum Computation
- 2022: Theory of Computational Complexity
- 2022: Combinatorial Optimization
- 2022: Advanced Graphics
- 2022: Logic in Artificial Intelligence
- 2022: Machine Learning
- 2022: Introduction to Data Science Pipeline
- 2023: Approximation Algorithms
Served as Reviewer
- International Conference on Machine Learning (ICML 2026 (5))
- International Conference on Artificial Neural Networks (ICANN 2026 (4))
- Uncertainty in Artificial Intelligence (UAI 2026 (4))
- Neural Information Processing Systems (NeurIPS 2025)
- IEEE/CAA Journal of Automatica Sinica (6)
- International Conference on Machine Learning and Applications (ICMLA 2025 (2))
- IEEE Transactions on Computational Social Systems
- International Conference on Artificial Intelligence and Statistics (AISTATS 2026 (2))
- Conference on Language Modelling (COLM 2025 (2),2026 (3))
- International Conference on Data Mining (ICDM 2024(2), 2025(2))
- European Symposium on Algorithms (ESA 2024,2025)
- Nature Scientific Reports (2)
- BigData 2024
- Integrating Materials and Manufacturing Innovation Journal
- Served as judge for programming contest HackDartmouth 2021
Master’s Project
- Adviser: Sourav Chakraborty,ISI Kolkata
- Markov Chains & Monte Carlo Methods and FPRAS for bipartite graphs. Notes used are here and here.
Undergraduate Project
- Adviser: Ramachandran Balasubramanian, IMSc
- Project: Analytic Number Theory
Honors and Awards
- Best Paper Award, The 20th IEEE International Conference on Dependable, Autonomic and Secure Computing (DASC 2022)
- International Youth Math Challenge organized by Indian Institute of Technology, 2019
- Chess Award, 2018
- Science and Engineering Research Board International Travel Award, Department of Science and Technology, 2017
- Top 20 in the Higher Secondary Examination, 2015
- Mathematical Talent Reward Program Award, Indian Statistical Institute, 2014
- Achievement Cum Diagnostic Test in Mathematics Gold Medalist, 2013
Technical and Language Skills
- Languages: Python, C++, PHP, HTML, R, Haskell, SQL,Java
- Frameworks: Numpy, Pandas, Scikeat-Learn, PyTorch, Matplotlib, Seaborn, Networkx,
- Software Tools: Git, Excel, LaTeX, A/B tests, statistical experiments
- ML Techniques: Supervised/unsupervised/Reinforcement Learning, Few-shot Learning, Transformer Models
Teaching Assistantships
- Data Structures and Algorithms, 2025
- Introduction to Data Science, 2025
- Introduction to Computer Graphics, 2024
- Design and Analysis of Algorithms, Northwestern University, 2024
- Foundations of Computer Science, Northwestern University, 2023
- Analysis II TA, Chennai Mathematical Institute, 2017
Talks
- 2023 - Poster Presentation at NeurIPS 2023
- 2023 - A constant lower bound for the union-closed sets, Venue: Northwestern University
- 2017 - A Variant of Large Sieve, Venue: Institute of Mathematical Sciences
- 2017 - Roth’s Theorem, Venue: Institute of Mathematical Sciences
- 2016 - Introduction to Cryptography, Venue: Chennai Mathematical Institute
Fun Projects
References
Available upon request