Janardhan Rao Doppa
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
78
Venues
20
Active years
2009–2026
Best venue rank
A*
Where they publish
Papers
78 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | DATE | Focus Session: Hardware/Software Co-Design to Accelerate Generative AI Workloads on Heterogeneous Architectures. | Pratyush Dhingra, Vibhanshu Sharma, Janardhan Rao Doppa, Partha Pratim Pande |
| 2025 | DAC | Uncertainty-Aware Energy Management for Wearable IoT Devices with Conformal Prediction. | Dina Hussein, Chibuike E. Ugwu, Ganapati Bhat, Janardhan Rao Doppa |
| 2025 | DATE | DEAR: Dependable 3D Architecture for Robust DNN Training. | Ashish Reddy Bommana, Farshad Firouzi, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2025 | DATE | Odin: Learning to Optimize Operation Unit Configuration for Energy-efficient DNN Inferencing. | Gaurav Narang, Janardhan Rao Doppa, Partha Pratim Pande |
| 2025 | IJCAI | Sustainable Wearables for Health Applications and Beyond via Uncertainty-Aware Energy Management. | Dina Hussein, Chibuike E. Ugwu, Ganapati Bhat, Janardhan Rao Doppa |
| 2024 | AAAI | Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization. | Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa |
| 2024 | AAAI | Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract). | Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa |
| 2024 | AAAI | Offline Model-Based Optimization via Policy-Guided Gradient Search. | Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, Janardhan Rao Doppa |
| 2024 | COMAD | Preference-Aware Constrained Multi-Objective Bayesian Optimization. | Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa |
| 2024 | DATE | FARe: Fault-Aware GNN Training on ReRAM-Based PIM Accelerators. | Pratyush Dhingra, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Ananth Kalyanaraman, Partha Pratim Pande |
| 2024 | DATE | Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads. | Harsh Sharma, Gaurav Narang, Janardhan Rao Doppa, mit Y. Ogras, Partha Pratim Pande |
| 2024 | ICCAD | Heterogeneous Manycore In-Memory Computing Architectures. | Chukwufumnanya Ogbogu, Gaurav Narang, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande |
| 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 |
| 2024 | IJCAI | Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach. | Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa |
| 2024 | ITC | SEC-CiM: Selective Error Compensation for ReRAM-based Compute-in-Memory | Ashish Reddy Bommana, Farshad Firouzi, Chukwufumnanya Ogbogu, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2024 | VTS | Thermal Modeling and Management Challenges in Heterogenous Integration: 2.5D Chiplet Platforms and Beyond. | Jaehyun Park, Alish Kanani, Lukas Pfromm, Harsh Sharma, Parth Solanki, Eric Tervo, Janardhan Rao Doppa, Partha Pratim Pande, mit Y. Ogras |
| 2023 | AAAI | Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis. | Subhankar Ghosh, Taha Belkhouja, Yan Yan, Janardhan Rao Doppa |
| 2023 | AISTATS | Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach. | Syrine Belakaria, Janardhan Rao Doppa, Nicol Fusi, Rishit Sheth |
| 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 |
| 2023 | DATE | Achieving Datacenter-scale Performance through Chiplet-based Manycore Architectures. | Harsh Sharma, Sumit K. Mandal, Janardhan Rao Doppa, mit Y. Ogras, Partha Pratim Pande |
| 2023 | DATE | Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars. | Chung-Hsuan Tung, Biresh Kumar Joardar, Partha Pratim Pande, Janardhan Rao Doppa, Hai Helen Li, Krishnendu Chakrabarty |
| 2023 | ETS | Attacking Memristor-Mapped Graph Neural Network by Inducing Slow-to-Write Errors. | Ching-Yuan Chen, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2023 | IJCAI | Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features (Extended Abstract). | Taha Belkhouja, Janardhan Rao Doppa |
| 2023 | ISLPED | Energy-Efficient Missing Data Recovery in Wearable Devices: A Novel Search-Based Approach. | Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa |
| 2023 | ISLPED | Uncertainty-Aware Online Learning for Dynamic Power Management in Large Manycore Systems. | Gaurav Narang, Raid Ayoub, Michael Kishinevsky, Janardhan Rao Doppa, Partha Pratim Pande |
| 2023 | ISLPED | Energy-Efficient ReRAM-Based ML Training via Mixed Pruning and Reconfigurable ADC. | Chukwufumnanya Ogbogu, Soumen Mohapatra, Biresh Kumar Joardar, Janardhan Rao Doppa, Deuk Heo, Krishnendu Chakrabarty, Partha Pratim Pande |
| 2022 | AAAI | Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis. | Taha Belkhouja, Yan Yan, Janardhan Rao Doppa |
| 2022 | AAAI | Bayesian Optimization over Permutation Spaces. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim |
| 2022 | AAAI | Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health. | Dina Hussein, Ganapati Bhat, Janardhan Rao Doppa |
| 2022 | DATE | DIET: A Dynamic Energy Management Approach for Wearable Health Monitoring Devices. | Nuzhat Yamin, Ganapati Bhat, Janardhan Rao Doppa |
| 2022 | ICCAD | Reliable Machine Learning for Wearable Activity Monitoring: Novel Algorithms and Theoretical Guarantees. | Dina Hussein, Taha Belkhouja, Ganapati Bhat, Janardhan Rao Doppa |
| 2022 | ICCAD | Fault-Tolerant Deep Learning Using Regularization. | Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande |
| 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 | DATE | ReGraphX: NoC-enabled 3D Heterogeneous ReRAM Architecture for Training Graph Neural Networks. | Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande, Biresh Kumar Joardar, Krishnendu Chakrabarty |
| 2021 | DATE | 3D++: Unlocking the Next Generation of High-Performance and Energy-Efficient Architectures using M3D Integration. | Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande |
| 2021 | ICCAD | DARe: DropLayer-Aware Manycore ReRAM architecture for Training Graph Neural Networks. | Aqeeb Iqbal Arka, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2021 | ICCAD | A General Hardware and Software Co-Design Framework for Energy-Efficient Edge AI. | Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande |
| 2021 | ICCAD | Heterogeneous Manycore Architectures Enabled by Processing-in-Memory for Deep Learning: From CNNs to GNNs: (ICCAD Special Session Paper). | Biresh Kumar Joardar, Aqeeb Iqbal Arka, Janardhan Rao Doppa, Partha Pratim Pande, Hai Li, Krishnendu Chakrabarty |
| 2021 | ICCAD | Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise. | Xiaoxuan Yang, Syrine Belakaria, Biresh Kumar Joardar, Huanrui Yang, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Hai Helen Li |
| 2021 | ICML | Bayesian Optimization over Hybrid Spaces. | Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa |
| 2021 | IJCAI | Adaptive Experimental Design for Optimizing Combinatorial Structures. | 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 | DAC | PETNet: Polycount and Energy Trade-off Deep Networks for Producing 3D Objects from Images. | Nitthilan Kanappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande |
| 2020 | DAC | Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs. | Sumit K. Mandal, mit Y. Ogras, Janardhan Rao Doppa, Raid Zuhair Ayoub, Michael Kishinevsky, Partha Pratim Pande |
| 2020 | DATE | GRAMARCH: A GPU-ReRAM based Heterogeneous Architecture for Neural Image Segmentation. | Biresh Kumar Joardar, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2020 | DATE | Power, Performance, and Thermal Trade-offs in M3D-enabled Manycore Chips. | Shouvik Musavvir, Anwesha Chatterjee, Ryan Gary Kim, Dae Hyun Kim, Janardhan Rao Doppa, Partha Pratim Pande |
| 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 |
| 2020 | ICCAD | SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms. | Nitthilan Kanappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande |
| 2020 | KDD | Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data. | Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook |
| 2019 | DATE | Design and Optimization of Heterogeneous Manycore Systems Enabled by Emerging Interconnect Technologies: Promises and Challenges. | Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande |
| 2019 | DATE | REGENT: A Heterogeneous ReRAM/GPU-based Architecture Enabled by NoC for Training CNNs. | Biresh Kumar Joardar, Bing Li, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty |
| 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 |
| 2018 | AAAI | Bayesian Optimization Meets Search Based Optimization: A Hybrid Approach for Multi-Fidelity Optimization. | Ellis Hoag, Janardhan Rao Doppa |
| 2018 | ICCAD | Hybrid on-chip communication architectures for heterogeneous manycore systems. | Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu |
| 2018 | ICCAD | Machine learning for design space exploration and optimization of manycore systems. | Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande |
| 2017 | AAAI | Active Preference Elicitation for Planning. | Mayukh Das, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan |
| 2017 | ACL | Towards Problem Solving Agents that Communicate and Learn. | Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md. Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth |
| 2017 | ACML | Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. | Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli, Hamed Shahbazi, Xiaoli Z. Fern |
| 2017 | ACML | Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search. | F. A. Rezaur Rahman Chowdhury, Chao Ma, Md. Rakibul Islam, Mohammad Hossein Namaki, Mohammad Omar Faruk, Janardhan Rao Doppa |
| 2017 | DATE | Robust TSV-based 3D NoC design to counteract electromigration and crosstalk noise. | Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2017 | ICCD | Monolithic 3D-Enabled High Performance and Energy Efficient Network-on-Chip. | Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2016 | CASES | Hybrid network-on-chip architectures for accelerating deep learning kernels on heterogeneous manycore platforms. | Wonje Choi, Karthi Duraisamy, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Radu Marculescu, Diana Marculescu |
| 2016 | DATE | Reliability and performance trade-offs for 3D NoC-enabled multicore chips. | Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2016 | ICCAD | Energy-efficient and reliable 3D network-on-chip (NoC): architectures and optimization algorithms. | Sourav Das, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2015 | AAAI | Learning Greedy Policies for the Easy-First Framework. | Jun Xie, Chao Ma, Janardhan Rao Doppa, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli |
| 2015 | CVPR | ℋC-search for structured prediction in computer vision. | Michael Lam, Janardhan Rao Doppa, Sinisa Todorovic, Thomas G. Dietterich |
| 2015 | ICCAD | Optimizing 3D NoC Design for Energy Efficiency: A Machine Learning Approach. | Sourav Das, Janardhan Rao Doppa, Daehyun Kim, Partha Pratim Pande, Krishnendu Chakrabarty |
| 2015 | KDD | Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications. | Bryan David Minor, Janardhan Rao Doppa, Diane J. Cook |
| 2014 | AAAI | HC-Search for Multi-Label Prediction: An Empirical Study. | Janardhan Rao Doppa, Jun Yu, Chao Ma, Alan Fern, Prasad Tadepalli |
| 2014 | AAAI | Learning Scripts as Hidden Markov Models. | John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich |
| 2014 | EMNLP | Prune-and-Score: Learning for Greedy Coreference Resolution. | Chao Ma, Janardhan Rao Doppa, John Walker Orr, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli |
| 2013 | AAAI | HC-Search: Learning Heuristics and Cost Functions for Structured Prediction. | Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli |
| 2012 | ICML | Output Space Search for Structured Prediction. | Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli |
| 2009 | IAAI | An Ensemble Learning and Problem Solving Architecture for Airspace Management. | Xiaoqin Zhang, Sung Wook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek T. Green, Jinhong K. Guo, Ugur Kuter, Geoffrey Levine, Reid MacTavish, Daniel McFarlane, James Michaelis, Hala Mostafa, Santiago Ontan, Charles Parker, Jainarayan Radhakrishnan, Antons Rebguns, Bhavesh Shrestha, Zhexuan Song, Ethan Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Gerald DeJong, Thomas G. Dietterich, Subbarao Kambhampati, Victor R. Lesser, Deborah L. McGuinness, Ashwin Ram, Diana F. Spears, Prasad Tadepalli, Elizabeth T. Whitaker, Weng-Keen Wong, James A. Hendler, Martin O. Hofmann, Kenneth R. Whitebread |