| 2025 | AAAI | Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning. | Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar |
| 2025 | AAAI | Offline Safe Reinforcement Learning Using Trajectory Classification. | Ze Gong, Akshat Kumar, Pradeep Varakantham |
| 2025 | COMSNETS | Adaptive Moving Target Defense in Web Applications and Networks using Factored MDP. | Megha Bose, Praveen Paruchuri, Akshat Kumar |
| 2025 | SoMeT | MedEForm: Medical Data Mobile App. | Shelly Sachdeva, Subhash Bhalla, Nikita Juyal, Akshat Kumar |
| 2024 | ICML | Unified Training of Universal Time Series Forecasting Transformers. | Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo |
| 2023 | AAAI | Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming. | Aravinth Chembu, Scott Sanner, Hassan Khurram, Akshat Kumar |
| 2023 | AAAI | Planning and Learning for Non-markovian Negative Side Effects Using Finite State Controllers. | Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein |
| 2023 | CPAIOR | A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. | Jihwan Jeong, Scott Sanner, Akshat Kumar |
| 2023 | ICML | Learning Deep Time-index Models for Time Series Forecasting. | Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi |
| 2022 | AAAI | Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. | Siow Meng Low, Akshat Kumar, Scott Sanner |
| 2022 | CHI | InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools. | Mustafa Doga Dogan, Ahmad Taka, Michael Lu, Yunyi Zhu, Akshat Kumar, Aakar Gupta, Stefanie Mller |
| 2022 | CP | Trajectory Optimization for Safe Navigation in Maritime Traffic Using Historical Data. | Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar |
| 2022 | ICLR | CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting. | Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi |
| 2022 | IJCAI | Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies. | Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar |
| 2019 | AAAI | Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs. | Tarun Gupta, Akshat Kumar, Praveen Paruchuri |
| 2019 | AAAI | Multiagent Decision Making For Maritime Traffic Management. | Arambam James Singh, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau |
| 2019 | IJCAI | Decision Making for Improving Maritime Traffic Safety Using Constraint Programming. | Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau |
| 2019 | IJCAI | Multiagent Decision Making and Learning in Urban Environments. | Akshat Kumar |
| 2018 | AAAI | Resource-Constrained Scheduling for Maritime Traffic Management. | Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau |
| 2018 | AAAI | Planning and Learning for Decentralized MDPs With Event Driven Rewards. | Tarun Gupta, Akshat Kumar, Praveen Paruchuri |
| 2018 | AAAI | Planning and Learning for Decentralized MDPs with Event Driven Rewards. | Tarun Gupta, Akshat Kumar, Praveen Paruchuri |
| 2018 | AAAI | Integrated Cooperation and Competition in Multi-Agent Decision-Making. | Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein |
| 2017 | AAAI | Decentralized Planning in Stochastic Environments with Submodular Rewards. | Rajiv Ranjan Kumar, Pradeep Varakantham, Akshat Kumar |
| 2017 | AAAI | Collective Multiagent Sequential Decision Making Under Uncertainty. | Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau |
| 2017 | AAAI | Robust Optimization for Tree-Structured Stochastic Network Design. | XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein |
| 2016 | AAAI | Shortest Path Based Decision Making Using Probabilistic Inference. | Akshat Kumar |
| 2016 | AAAI | Robust Decision Making for Stochastic Network Design. | Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon |
| 2016 | AISTATS | Approximate Inference Using DC Programming For Collective Graphical Models. | Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon |
| 2015 | ICML | Message Passing for Collective Graphical Models. | Tao Sun, Daniel Sheldon, Akshat Kumar |
| 2015 | IJCAI | Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs. | Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham |
| 2013 | ICML | Approximate Inference in Collective Graphical Models. | Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich |
| 2013 | IJCAI | Parameter Learning for Latent Network Diffusion. | XiaoJian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein |
| 2013 | IJCAI | Automated Generation of Interaction Graphs for Value-Factored Dec-POMDPs. | William Yeoh, Akshat Kumar, Shlomo Zilberstein |
| 2013 | UAI | Collective Diffusion Over Networks: Models and Inference. | Akshat Kumar, Daniel Sheldon, Biplav Srivastava |
| 2012 | AAAI | Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning. | Akshat Kumar, XiaoJian Wu, Shlomo Zilberstein |
| 2011 | IJCAI | Scalable Multiagent Planning Using Probabilistic Inference. | Akshat Kumar, Shlomo Zilberstein, Marc Toussaint |
| 2011 | UAI | Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation. | Akshat Kumar, Shlomo Zilberstein |
| 2010 | UAI | Anytime Planning for Decentralized POMDPs using Expectation Maximization. | Akshat Kumar, Shlomo Zilberstein |
| 2009 | FlAIRS | Dynamic Programming Approximations for Partially Observable Stochastic Games. | Akshat Kumar, Shlomo Zilberstein |
| 2009 | IJCAI | Event-Detecting Multi-Agent MDPs: Complexity and Constant-Factor Approximations. | Akshat Kumar, Shlomo Zilberstein |
| 2008 | AAAI | H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP. | Akshat Kumar, Adrian Petcu, Boi Faltings |
| 2004 | CEC | Tournament versus fitness uniform selection. | Shane Legg, Marcus Hutter, Akshat Kumar |