Manish Shetty

Research Fellow, Microsoft Research India

manish.shetty.m [at]


About Me

Hi!👋 I'm a Research Fellow (RF) at Microsoft Research (MSR) - India. At MSR, I work on intelligent tools and systems to aid software developement processes. I'm advised by Chetan Bansal, Dr. Suman Nath, Dr. Tom Zimmermann, and Dr. Nachi Nagappan. Prior to joining as an RF, I also interned @ MSR for 6 months.

In May 2020, I graduated from PES University, Bangalore with a B.Tech in Computer Science. During undergrad I worked on ML Systems for healthcare advised by Dr. Gowri Srinivasa.

Research Interests

Software Engineering (SE), Machine Learning (ML), and Systems (Sys)

Currently, my research concerns combining statistical, neural, and traditional techniques to build novel systems that improve/aid software engineering processes.

From a SE/PL perspective, I'm fascinated by how distributed data-driven programs are changing how we develop, maintain, debug, and evolve software systems:
Empirical SE, ML+SE, Program Analysis & Synthesis.

From an ML perspective, I'm excited about techniques that allow processing weak, dynamic, and reusable stimuli to easily build robust systems:
Multi-task/Meta Learning, Weak Supervision, Programmatic Supervision

If you'd like to collaborate or just chat with me about about research, feel free to drop me an email.

Recent Publications


Large-scale Crash Localization using Multi-Task Learning
SoftNER: Mining Knowledge Graphs From Cloud Incidents
Neural Knowledge Extraction From Cloud Service Incidents


A Machine Learning Understanding of Sepsis
Exploration and Comparison of Modern AI Algorithms to Predict Drug Efficacy


News Service Experience
  • [Nov '21] Recommended as Reviewer from ICLR '22 mentee pool for excellent review!
  • [Jul '21] Excited to be selected as a Reviewer mentee @ ICLR '22!
  • [Jul '21] Our work on an ML interpretation of Sepsis was accepted @ EMBC '21!
  • [May '21] Presented SoftNER @ ICSE '21
  • [Jan '21] Selected to be on the Shadow PC @ MSR '21
  • [Jan '21] SoftNER was accepted at ICSE (SEIP) '21!
  • [Jul '20] Preprint featured in VentureBeat - Check it out!
  • [Jun '20] Filed my first patent - "Automatic Recognition of Entities Related to Cloud Incidents"

Recommended from reviewer mentee
pool for excellent review.

10th International Conference on Learning Representations 2022 (ICLR'22)

Shadow PC (Invited)

Mining Software Repositories 2021 (MSR'21)


Journal of Software Engineering Research and Development (JSERD)

Aug 2020 - Present Research Fellow, Microsoft Research (India)
Working on AIOps & ML4SE.
Jan 2020 - Jun 2020 Research Intern, Microsoft Research (India)
Worked on ML4SE. Created/developed SoftNER.
Jul 2019 - Jun 2020 Research Assistant, Center for Pattern Recognition, PES University
Worked on ML powered drug discovery.
Jun 2019 - Aug 2019 Machine Learning Research Intern, Deloitte
Worked on algorithms/tools for the Cyber-Risk team.
Jun 2018 - Feb 2019 Research Intern, Center for Cloud Computing and Big Data, PES University
Worked on intelligent and energy aware VM provisioning algorithms.