CV

Here is my Academic CV in the PDF format (Last updated in September 2024):

Academic CV (Text Format)

Education

• Ph.D. in Computer Science, University of Waterloo, 2026 (expected)
• B.E. (Hons.) in Electronics & Instrumentation, BITS Pilani, 2018

Research Experience

• Fall 2024: Internship at Databricks
  • Project: Building a code-based realistic RAG evaluation benchmark on niche topics.
  • Supervisors: Omar Khattab, Sam Havens, Michael Carbin and Andrew Drozdov.
• Winter & Summer 2024 : Internship at Vectara
  • Project: Building an effective multilingual RAG benchmark with heuristic & automatic features.
  • Supervisors: Amin Ahmad and Suleman Kazi.
• Fall 2022 & Winter 2023: Internship at Google Research
  • Project: Building an efficient multilingual embedding model using LLM-generated synthetic data.
  • Supervisors: Daniel Cer and Jianmo Ni.
• Nov 2019 - Aug 2021: Research Assistant at UKP Lab, TU Darmstadt
  • Project: Building a zero-shot heterogeneous benchmark and data-efficient sentence embedding models.
  • Supervisors: Nils Reimers and Iryna Gurevych.

Work Experience

• Sep 2018 - Oct 2018: Data Scientist at KNOLSKAPE
  • Project: Developed Krawler.ai, an deep text-based search engine built on Lucene.
  • Manager: Chaithanya Yambari

Publications (List)

NoMIRACL: Knowing When You Don’t Know for Robust Multilingual Retrieval-Augmented Generation

Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR

Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval

Resources for Brewing BEIR: Reproducible Reference Models and Statistical Analyses

HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attribution

Injecting Domain Adaptation with Learning-to-hash for Effective and Efficient Zero-shot Dense Retrieval

SPRINT: A Unified Toolkit for Evaluating and Demystifying Zero-shot Neural Sparse Retrieval

Evaluating Embedding APIs for Information Retrieval

Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval

Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages

GPL: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks

Talks (List)

Accelerating Multilingual RAG @ Micrsoft Research

December 10, 2024

Invited Talk at Microsoft Research, Bangalore, India

Heterogeneous IR Benchmarking @ IIIT Delhi

January 24, 2024

Invited Talk at IIIT-Delhi, Delhi, India

Heterogeneous IR Benchmarking @ IIT Delhi

January 23, 2024

Invited Talk at IIT-Delhi, Delhi, India

Advanced Information Retrieval @ Koç

June 01, 2023

Invited Talk at Koç University, Virtual (Online)

Heterogeneous Benchmarking @ Stanford

November 17, 2022

Invited Talk at Stanford University, California, USA

BEIR: An Open-Source Benchmark for Information Retrieval Systems @ OpenNLP

June 04, 2021

Invited Talk at OpenNLP Meetup (Deepset.ai), Virtual (Online)

Teaching

CS 370 Numerical Approximation

CS 479/679 Introduction to Artificial Intelligence

CS 241 Foundations of Sequential Programs

CS 136 Elementary Algorithm Design and Data Abstraction

CS 135 Designing Functional Programs

Service and leadership

• Shared-Task Lead Organizer on Retrieval Augmented Generation (RAG) Track at TREC 2024.
• Competition Lead Organizer on MIRACL at WSDM Cup 2023.
• Reviewer (*CL/NLP conferences): ACL Rolling Review: Oct-Nov (2021), Jan-Apr (2022)
• Reviewer (ML conferences): NeurIPS 2023.
• Reviewer (IR conferences): SIGIR 2023, ECIR 2024, NAACL 2024.