| 2026 | AAAI | Nanoporous Materials Discovery via Search Bias-Guided Surrogate Modeling. | Azza Fadhel, Yassine Chemingui, Minh Hoang, Aryan Deshwal, Trong Nghia Hoang, Jana Doppa |
| 2026 | AAAI | Discovery of Feasible 3D Printing Configurations for Metal Alloys via AI-Driven Adaptive Experimental Design. | Azza Fadhel, Nathaniel W. Zuckschwerdt, Aryan Deshwal, Susmita Bose, Amit Bandyopadhyay, Jana Doppa |
| 2025 | AAAI | Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning. | Yassine Chemingui, Aryan Deshwal, Honghao Wei, Alan Fern, Jana Doppa |
| 2025 | AAAI | Adaptive Experimental Design to Accelerate Scientific Discovery and Engineering Design. | Aryan Deshwal |
| 2025 | EMNLP | COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier. | Gaoxiang Luo, Aryan Deshwal |
| 2024 | AAAI | Offline Model-Based Optimization via Policy-Guided Gradient Search. | Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa |
| 2024 | ICML | Learning Surrogates for Offline Black-Box Optimization via Gradient Matching. | Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang |
| 2024 | IJCAI | Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. | Mohammed Amine Gharsallaoui, Bhupinderjeet Singh, Supriya Savalkar, Aryan Deshwal, Ananth Kalyanaraman, Kirti Rajagopalan, Janardhan Rao Doppa |
| 2023 | AISTATS | Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. | Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson |
| 2022 | AAAI | Bayesian Optimization over Permutation Spaces. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim |
| 2021 | AAAI | Mercer Features for Efficient Combinatorial Bayesian Optimization. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa |
| 2021 | DAC | Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach. | Aryan Deshwal, Syrine Belakaria, Ganapati Bhat, Janardhan Rao Doppa, Partha Pratim Pande |
| 2021 | ICML | Bayesian Optimization over Hybrid Spaces. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa |
| 2020 | AAAI | Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach. | Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa |
| 2020 | AAAI | Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. | Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa |
| 2020 | AAAI | Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Alan Fern |
| 2020 | DATE | Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning. | Zhiyuan Zhou, Syrine Belakaria, Aryan Deshwal, Wookpyo Hong, Janardhan Rao Doppa, Partha Pratim Pande, Deukhyoun Heo |
| 2019 | IJCAI | Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning. | Chao Ma, F. A. Rezaur Rahman Chowdhury, Aryan Deshwal, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth |
| 2019 | IJCAI | Learning and Inference for Structured Prediction: A Unifying Perspective. | Aryan Deshwal, Janardhan Rao Doppa, Dan Roth |