I am currently a first-year Ph.D. student at the University of Michigan, Ann Arbor, working under the guidance of Prof. Lu Wang. I am currently focussing on using LLMs for Argument Mining. Prior to that, I was a Research Associate at Adobe Research Labs, Bangalore where I worked on a wide range of Machine Learning projects in Document intelligence, Natural Language Processing, Information Extraction and Legal Artificial Intelligence. I recieved my Bachelor of Technology (BTech.) in Electrical Engineering with Minor in Computer Science and Engineering from Indian Institute of Technology, Bombay (IIT Bombay) in 2021. In my spare time, I enjoy gaming, reading non-fiction books, and playing sports like badminton and squash.
Research
I am broadly interested in Machine Learning, Natural Language Processing (NLP) and related fields. Currently, I am exploring how LLMs can be employed in effectively extracting the argumentative structure of the text, all with the objective of providing invaluable feedback to students regarding their essay compositions. At Adobe, I have primarily worked in document intelligence projects involving NLP techniques like semantic / topical structure analysis and information extraction. During my undergraduate studies, I worked with Prof. Suyash Awate to repurpose a generative modelling framework for the task of one-class classification and anomaly detection. Under the guidance of Prof. Shivaram Kalyanakrishnan, I worked in developing a PAC algorithm for mode estimation of discrete distribution with efficient sample complexity.
Publications
Inderjeet Nair, Shwetha S., Apoorva Saxena, Koustava Goswami; Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering; Accepted to EMNLP 2023 Findings
Adrian Kochsiek, Apoorv Umang Saxena, Inderjeet Nair, Rainer Gemulla; Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction; Accepted to ACL 2023 Workshop RepL4NLP
Inderjeet Nair, Natwar Modani; Exploiting Language Characteristics for Legal Domain-Specific Language Model Pretraining; Accepted to EACL 2023 Findings
Inderjeet Nair, Aparna Garimella, Balaji Vasan Srinivasan, Natwar Modani, Niyati Chhaya, Srikrishna Karanam, Sumit Shekhar; A Neural CRF-based Hierarchical Approach for Linear Text Segmentation; Accepted to EACL 2023 Findings
Aishwarya Agarwal, Anuj Srivastava, Inderjeet Nair, Swasti Shreya Mishra, Vineeth Dorna, Sharmila Reddy Nangi, Balaji Vasan Srinivasan; SketchBuddy: Context-Aware Sketch Enrichment and Enhancement; Accepted to 2023 ACM Multimedia Systems
Shubham Anand Jain, Rohan Shah, Sanit Gupta, Denil Mehta, Inderjeet Nair, Jian Vora, Sushil Khyalia, Sourav Das, Vinay J Ribeiro, Shivaram Kalyanakrishnan; PAC Mode Estimation using PPR Martingale Confidence Sequences; Accepted to the 2022 International Conference on Artificial Intelligence and Statistics
Natwar Modani, Anurag Maurya, Gaurav Verma, Inderjeet Nair, Vaidehi Patil, Anirudh Kanfade; Detecting Document Versions and Their Ordering in a Collection; Accepted to the 2021 International Conference on Web Information Systems Engineering; Best Paper Runners-up Award
Patents
Inderjeet Nair, Aparna Garimella, Balaji Vasan Srinivasan, Natwar Modani, Niyati Chhaya, Srikrishna Karanam, Sumit Shekhar ; Reader-driven Zoom in – Zoom out: Segmentation to enable non-linear navigation of long form documents; US Patent Application to be filed; Adobe Inc.
Inderjeet Nair, Anirudh Phukan, Aravind Veluri, Lakshya J., Mohar Kundu, Akhash Amarnath, Niyati Chhaya, Sumit Shekhar; Reflowing Infographics for Enhanced Cross-Device Consumption; US Patent Application to be filed; Adobe Inc.
Inderjeet Nair, Akshay Singhal, Kumud Lakara, Pritika Ramu, Vikas Balani, Anandhavelu N; Minimally Guided Semantic Extraction; US Patent Application to be filed; Adobe Inc.
Inderjeet Nair, Natwar Modani; Exploiting Legal Domain Characteristics for Legal Language Model Pretraining; US Patent Application to be filed; Adobe Inc.
Inderjeet Nair, Natwar Modani; Integrated Reading Experience for Contracts and their Amendments; US Patent Application 17/954,558; Adobe Inc.
Ayush Maheshwari, Inderjeet Nair, Navita Goyal, Natwar Modani, Ani Nenkova; Assisted Review of Text Content using a Machine Learning Model; US Patent Application 17/549,270; Adobe Inc.
Natwar Modani, Vaidehi Patil, Inderjeet Nair, Gaurav Verma, Anurag Maurya, Anirudh Kanfade; Systems for Generating Indications of Relationships between Electronic Documents; US Patent Application 17/534,744; Adobe Inc.
Work Experience
University of Michigan, Ann Arbor
Ph.D. Student - September 2023 - Current
Adobe Research Labs, Bangalore
Research Associate - July 2021 - August 2023
Adobe, Research Labs, Bangalore
Research Intern — June 2020 - August 2020
Stamp My Visa, Mumbai
Production Engineer — June 2019 - August 2019
CV
Contact
inderjeetnair1 [at] gmail.com
inair [at] umich.com