Ameya Godbole

Ameya Godbole

Research Fellow in Computer Science

University of Massachusetts, Amherst


I am actively applying to Ph.D. programs

I am a Research Fellow with the Information Extraction and Synthesis Laboratory (IESL) at the University of Massachusetts (UMass), Amherst. Before joining the lab, I obtained a Master’s degree in Computer Science from UMass and a B.Tech. in Electronics and Communication Engineering (with a minor in Computer Science and Engineering) from IIT Guwahati prior to that.

I am interested in research on natural language processing (NLP) systems that can reason over text and knowledge bases. I have worked on retrieval for open-domain QA and have made forays into knowledge base completion which is an important component of automated reasoning on structured data.

As a research fellow, I contribute to IESL’s efforts into OpenReview (reviewer matching, paper-reviewer affinity), and IESL’s collaboration with the Chan Zuckerberg Initiative where I am working on affiliation disambiguation. I am fortunate to have worked with and to be working with awesome lab members at IESL.

I sporadically blog (I mostly edit and proof-read) on Medium.


  • Artificial Intelligence
  • Machine Learning
  • Natural Language Processing
  • Reinforcement Learning


  • MSc in Computer Science, 2020

    University of Massachusetts, Amherst

  • BTech in Electronics and Communication Engineering, 2018

    Indian Institute of Technology (IIT), Guwahati


Quickly discover relevant content by filtering publications.
Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion
A Simple Approach to Case-Based Reasoning in Knowledge Bases
Chains-of-Reasoning at TextGraphs 2019 Shared Task: Reasoning over Chains of Facts for Explainable Multi-hop Inference
Multi-Step Entity-Centric Information Retrieval for Multi-Hop Question Answering
Progressively Balanced Multi-class Neural Trees



Research Fellow

Information Extraction and Synthesis Laboratory (IESL)

Jun 2020 – Present Massachusetts

The role allows me to pursue projects with the IESL lab members. In addition, I contribute to OpenReview, the open-access, open-discussion conference platform. I also work with the Chan Zuckerberg Initiative to apply IESL’s lab output to CZI’s systems and databases.


  • Case-based reasoning for knowledge base completion and question answering.
  • Incorporated a language model based system trained on citation and authorship graphs into OpenReview Expertise which generates affinity scores between submitted papers and available reviewers. This system generates affinity scores between submitted papers and available reviewers' past body of work.
  • Added features to the fairness-constrained matching algorithms of OpenReview Matcher, which solve an optimization problem to assign papers for review given pre-computed affinity scores. The “fair” matching algorithms ensure that the reviewers assigned to every submission possess a (combined) minimum level of familiarity with the research area.
  • Currently working to scale an affiliation disambiguation system to 400K+ target affiliation labels as part of IESL’s collaboration with the Meta-CZI.

Machine Learning Intern

SRI International

May 2019 – Aug 2019 California

Member of a team of researchers from the Artificial Intelligence Center (AIC), SRI International participating in the DARPA program: Radio Frequency Machine Learning Systems (RFMLS)


  • Developed and maintained an RF spectrum simulator for fast and reproducible experimentation.
  • Implemented and benchmarked reinforcement learning approaches to control/steer an antenna array for RF monitoring.
  • Experimented with alternative training regimes such as imitation learning. This method led to better performance than the available baselines.

Software Development Intern

Centre for Development of Advanced Computing (CDAC)

May 2016 – Jul 2016 Pune, India
  • Studied and implemented the principles of parallel processing using MPI and OpenMP.
  • Contributed to a molecular dynamics simulator capable of leveraging the compute capabilities of a CPU cluster. The simulator implemented distributed computation of the physics of particle movement.


  • ameyag416 [at] gmail [dot] com