| 2026 | AAAI | Group Fair Matchings Using Convex Cost Functions. | Atasi Panda, Harsh Sharma, Anand Louis, Prajakta Nimbhorkar |
| 2025 | COLT | Robust Algorithms for Recovering Planted r-Colorable Graphs. | Anand Louis, Rameesh Paul, Prasad Raghavendra |
| 2024 | IJCAI | Individual Fairness under Group Fairness Constraints in Bipartite Matching - One Framework to Approximate Them All. | Atasi Panda, Anand Louis, Prajakta Nimbhorkar |
| 2024 | SIGIR | Optimizing Learning-to-Rank Models for Ex-Post Fair Relevance. | Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis |
| 2024 | SODA | New Approximation Bounds for Small-Set Vertex Expansion. | Suprovat Ghoshal, Anand Louis |
| 2023 | AIES | Sampling Individually-Fair Rankings that are Always Group Fair. | Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis |
| 2023 | ECAI | Online Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints. | Anand Louis, Meghana Nasre, Prajakta Nimbhorkar, Govind S. Sankar |
| 2023 | IJCAI | Sampling Ex-Post Group-Fair Rankings. | Sruthi Gorantla, Amit Deshpande, Anand Louis |
| 2022 | ICALP | Exact Recovery Algorithm for Planted Bipartite Graph in Semi-Random Graphs. | Akash Kumar, Anand Louis, Rameesh Paul |
| 2022 | UAI | Robust identifiability in linear structural equation models of causal inference. | Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2021 | ICML | On the Problem of Underranking in Group-Fair Ranking. | Sruthi Gorantla, Amit Deshpande, Anand Louis |
| 2021 | IJCAI | Matchings with Group Fairness Constraints: Online and Offline Algorithms. | Govind S. Sankar, Anand Louis, Meghana Nasre, Prajakta Nimbhorkar |
| 2021 | PAKDD | Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs. | Naganand Yadati, Tingran Gao, Shahab Asoodeh, Partha P. Talukdar, Anand Louis |
| 2021 | SODA | Approximation Algorithms and Hardness for Strong Unique Games. | Suprovat Ghoshal, Anand Louis |
| 2021 | WADS | Independent Sets in Semi-random Hypergraphs. | Yash Khanna, Anand Louis, Rameesh Paul |
| 2020 | CIKM | NHP: Neural Hypergraph Link Prediction. | Naganand Yadati, Vikram Nitin, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha P. Talukdar |
| 2019 | AISTATS | On Euclidean k-Means Clustering with alpha-Center Proximity. | Amit Deshpande, Anand Louis, Apoorv Vikram Singh |
| 2019 | UAI | Stability of Linear Structural Equation Models of Causal Inference. | Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2018 | ICALP | Semi-random Graphs with Planted Sparse Vertex Cuts: Algorithms for Exact and Approximate Recovery. | Anand Louis, Rakesh Venkat |
| 2016 | FOCS | Accelerated Newton Iteration for Roots of Black Box Polynomials. | Anand Louis, Santosh S. Vempala |
| 2015 | STOC | Hypergraph Markov Operators, Eigenvalues and Approximation Algorithms. | Anand Louis |
| 2014 | IPCO | Linear Programming Hierarchies Suffice for Directed Steiner Tree. | Zachary Friggstad, Jochen Knemann, Young Kun-Ko, Anand Louis, Mohammad Shadravan, Madhur Tulsiani |
| 2014 | SODA | Approximation Algorithm for Sparsest | Anand Louis, Konstantin Makarychev |
| 2013 | FOCS | The Complexity of Approximating Vertex Expansion. | Anand Louis, Prasad Raghavendra, Santosh S. Vempala |
| 2012 | STOC | Many sparse cuts via higher eigenvalues. | Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala |
| 2010 | IPCO | A 3-Approximation for Facility Location with Uniform Capacities. | Ankit Aggarwal, Anand Louis, Manisha Bansal, Naveen Garg, Neelima Gupta, Shubham Gupta, Surabhi Jain |