Short Bio

I am a Research Scientist at PocketFM in the Data Science Team. Prior to joining PocketFM I worked as a Ph.D. scholar(Qualcomm PhD Fellow) under the supervision of Dr. Sayan Ranu in the Department of Computer Science and Engineering at IIT Delhi.

Research Interests:

1. Learning Combinatorial algorithms on graphs
2. Learning to Solve Mixed Integer Programs
3. Graph Generative Modeling
4. Few shot learning/ Meta-Learning
Prior to joining IIT Delhi, I worked as a Research Engineer in the Machine learning and statistics group at Conduent Labs( Formerly Xerox Research Center India). I received my Master’s degree in Computer Science and Engineering from the Indian Institute of Technology Guwahati. Please visit my Google Scholar profile for more details.

News

** May 2023: Paper on Neural Graph Partitioning accepted in KDD 2024 Video.

Dec 2023: Outstanding Reviewer Award at ACM CODS COMAD 2024. Rewarded to top 3 out of 49 reviewers

Nov 2023::Paper Accepted in Learning on Graphs Conference(LOG 2023)

June 2023:: Outstanding Teaching Assistanship Award for Database Systems and Graph Neural Network course (UG + PG) at IIT Delhi 2023

April 2023:: 2 papers accepted in ICML 2023

April 2023: Selected for attending HLF: Was one of the 200 young researchers selected across the globe to attend the Heidelberg Laureate Forum in Germany in 2023.

March 2023: Outstanding Teaching Assistanship Award for Computer Networks course(UG + PG) at IIT Delhi 2022.

Jan 2023: Oral at AAAI : Our AAAI paper : Lifelong Learning to solve Mixed Integer Programs is selected for oral presentation.

Dec 2022: University of Tokyo: Worked as a visiting researcher in the area of Graph condensation for Graph Neural Networks under the supervision of Prof. Toyotaro Suzumura at the University of Tokyo, Japan

Nov 2022: Paper accepted AAAI 2023: Lifelong Learning to solve Mixed Integer Programs

July 2022: Serving as PC member of AAAI 2023

June 2022: Received Qualcomm Innovation Fellowship(QIF) for 2022-2023

June 2022: Paper accepted in ECML-PKDD 2022.

May 2022: US Patent Granted Trained Pattern Analyzer for Rollout Decisions” USPTO.

Jan 2022: Serving as PC member in Applied Data Science Track in KDD 2022

Nov 2021: Paper accepted in AAAI 2022

Sep 2021: Paper accepted in NeurIPS 2021

Sep 2020: Paper accepted in NeurIPS 2020

Sep 2020: Joined as a Research Intern in the Machine learning and optimization Team at NAVER Labs, Europe.