Outlier Aware Network Embedding for Attributed Networks. - Sambaran Bandyopadhyay; Lokesh Nagalapatti; M. Narasimha Murty (AAAI, 2019)

Overview and Importance of Data Quality for Machine Learning Tasks. - Abhinav Jain 001; Hima Patel; Lokesh Nagalapatti; Nitin Gupta 005; Sameep Mehta; Shanmukha C. Guttula; Shashank Mujumdar; Shazia Afzal; Ruhi Sharma Mittal; Vitobha Munigala (KDD, 2020)

Data Augmentation for Personal Knowledge Graph Population. - Lingraj S. Vannur; Lokesh Nagalapatti; Balaji Ganesan; Hima Patel (CoRR, 2020)

Game of Gradients: Mitigating Irrelevant Clients in Federated Learning. - Lokesh Nagalapatti; Ramasuri Narayanam (AAAI, 2021)

Ranking Data Slices for ML Model Validation: A Shapley Value Approach. - Eitan Farchi; Ramasuri Narayanam; Lokesh Nagalapatti (ICDE, 2021)

Data Augmentation for Fairness in Personal Knowledge Base Population. - Lingraj S. Vannur; Balaji Ganesan; Lokesh Nagalapatti; Hima Patel; M. N. Tippeswamy (PAKDD (Workshops), 2021)

Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets. - Nitin Gupta 005; Hima Patel; Shazia Afzal; Naveen Panwar; Ruhi Sharma Mittal; Shanmukha C. Guttula; Abhinav Jain 001; Lokesh Nagalapatti; Sameep Mehta; Sandeep Hans; Pranay Lohia; Aniya Aggarwal; et al. (CoRR, 2021)

Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning. - Lokesh Nagalapatti; Ruhi Sharma Mittal; Ramasuri Narayanam (AAAI, 2022)

Learning Recourse on Instance Environment to Enhance Prediction Accuracy. - Lokesh Nagalapatti; Guntakanti Sai Koushik; Abir De; Sunita Sarawagi (NeurIPS, 2022)

A Data-centric AI Framework for Automating Exploratory Data Analysis and Data Quality Tasks. - Hima Patel; Shanmukha C. Guttula; Nitin Gupta 005; Sandeep Hans; Ruhi Sharma Mittal; Lokesh Nagalapatti (ACM J. Data Inf. Qual., 2023)

Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. - Lokesh Nagalapatti; Akshay Iyer; Abir De; Sunita Sarawagi (AAAI, 2024)

PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect. - Lokesh Nagalapatti; Pranava Singhal; Avishek Ghosh; Sunita Sarawagi (ICML, 2024)

Gradient Coreset for Federated Learning. - Durga Sivasubramanian; Lokesh Nagalapatti; Rishabh K. Iyer; Ganesh Ramakrishnan (WACV, 2024)

Tab-Shapley: Identifying Top-k Tabular Data Quality Insights. - Manisha Padala; Lokesh Nagalapatti; Atharv Tyagi; Ramasuri Narayanam; Shiv Kumar Saini (AAAI, 2025)

From Search to Sampling: Generative Models for Robust Algorithmic Recourse. - Prateek Garg; Lokesh Nagalapatti; Sunita Sarawagi (ICLR, 2025)

Robust Root Cause Diagnosis using In-Distribution Interventions. - Lokesh Nagalapatti; Ashutosh Srivastava; Sunita Sarawagi; Amit Sharma (ICLR, 2025)

Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE. - Lokesh Nagalapatti; Pranava Singhal; Avishek Ghosh; Sunita Sarawagi (Trans. Mach. Learn. Res., 2025)