Hi! I am currently in the fourth year of my PhD at IIT Bombay, India. I started my PhD in 2021 and have the privilege of being guided by Prof. Sunita Sarawagi and Prof. Abir De. My research primarily focuses on the fields of Causal Inference and Algorithmic Recourse. I am grateful to have my PhD studies funded by the Prime Minister Research Fellowship.
Prior to joining IIT Bombay, I worked with IBM Research for about 1.5 year on topics such as Federated Learning, data quality metrics assessment, and user preference aggregation. Before that, I completed my Master’s degree at IISc Bangalore. During my time at IISc, I worked with Prof. M Narasimha Murty on the development of robust representations for nodes in Social Networks, with a specific focus on handling outliers.
Interests
- Machine Learning in general
- Causal Inference
- Algorithmic Recourse
- Federated Learning
Education
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PhD in Computer Science and Engineering, 2021 - Present
IIT Bombay
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M.Tech. in Computer Science, 2019
IISc Bangalore
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B.E. in Computer Science, 2015
CEG, Anna University
Experience
Research Intern
Worked on Root Cause Analysis of anomalies that occur in an industry.
Blue Scholar
Worked on various SOTA technologies like Data Readiness for AI, Federated Learning etc.
Member of Technical Staff - 1
Worked on Adobe Muse, an application that generates responsive websites through a plug&play interface.
Software Development Engineer
Worked on Andorid UI development for Tuscany, a multi-function printer.
Updates
- 📝 Reviewer for TMLR-25.
- 📝 Reviewer for ICLR-25.
- 📃 Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE accepted at TMLR-25.
- 📃 Tab-Shapley: Identifying Top-k Tabular Data Quality Insights accepted at AAAI-25.
- 💵 Grateful to PMRF for a travel grant to attend NeurIPS-24 in Vienna.
- 📃 Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE accepted at the CRL workshop at NeurIPS-24.
- 📝 Reviewer for NeurIPS-24.
- 💵 Grateful to Microsoft Research India for a travel grant to attend ICML-24 in Vienna.
- 🍁 Started a research internship at Microsoft Research India, working with Amit Sharma on Root Cause Analysis.
- 📃 PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect.
- 💵 Grateful to Microsoft Research India for a travel grant to attend AAAI-24 in Vancouver.
- 📃 Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing accepted at AAAI-24.
- 📃 Gradient Coresets for Federated Learning accepted as a full paper at WACV'24.
- 🔊 Delivered a talk on “Causal Inference” at Amex, Bangalore.
- 🔊 Co-taught a Machine Learning course for Master’s level students in the CSE Department at VJTI Mumbai.
- 🔊 Co-taught a Machine Learning (Theory/Lab) course for UG students in the CSE Department at SSN College of Engineering, Chennai.
- 🔊 Presented a tutorial on Gaussian Processes in CS 337.
- 🔊 Delivered an invited talk on “Learning Recourse in Instance Environments” at Adobe Research.
- 📃 Learning Recourse in Instance Environments to Enhance Prediction Accuracy accepted at NeurIPS'22.
- 🔊 Delivered a talk on Optimal Transport in the CSE Department at IIT Bombay.
- 📝 Reviewer for AAAI 2023 Research Track.
- 📝 Serving on the Program Committee (PC) of AIMLSystems 2022 Research Track.
- 📣 Teaching Linear Algebra for GATE through NPTEL. Videos available here!
- 📃 Federated Learning with Relevant Data accepted at AAAI'22.
- 📝 Delivered a KDD'21 tutorial on data quality.
- 📝 Serving on the PC of CODS-COMAD 2021 Research Track.
- 📝 Serving on the PC of AIMLSystems 2021 Industry Track.
- 🏫 Started a Ph.D. at IIT Bombay.
- 🔊 Delivered a guest lecture on “Data Quality for Machine Learning” at JDBI, Kolkata.
- 🔊 Delivered a guest lecture on “Outsmarting Outliers in Social Networks” at CEG, Chennai.
- 📃 One short paper accepted at ICDE 2021.
- 📃 One research track paper accepted at AAAI 2021.
- 🏫 Graduated with a Master’s from IISc and joined IBM Research.
- 📃 One research track paper accepted at WSDM 2020.
- 📃 One research track paper accepted at AAAI 2019.
Talks
Publications
(2025).
Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE.
TMLR'25.
(2025).
Tab-Shapley: Identifying Top-k Tabular Data Quality Insights.
AAAI'25.
(2024).
Continuous Treatment Effect estimation using Gradient Interpolation and Kernel Smoothing.
AAAI'24.
(2024).
Gradient Coresets for Federated Learning.
WACV'24.
(2022).
Learning Recourse on Instance Environment to Enhance Prediction Accuracy.
NeurIPS'22.
(2022).
Is your data relevant?: Dynamic selection of data in Federated Learning..
AAAI'22.
(2021).
Game of Gradients - Mitigating irrelevant clients in Federated Learning.
AAAI'21.
(2021).
Ranking Data Slices for ML Model Validation: A Shapley Value Approach.
ICDE'21.
Patents
Contact
- nlokeshiisc AT gmail.com
- Kanwal Rekhi building, Dept. of CSE, Powai, Mumbai, India 400076