An Ensemble Learning and Problem Solving Architecture for Airspace Management. - Xiaoqin Zhang 001; Sung Wook Yoon; Phillip DiBona; Darren Scott Appling; Li Ding 001; Janardhan Rao Doppa; Derek T. Green; Jinhong K. Guo; Ugur Kuter; Geoffrey Levine; Reid MacTavish; Daniel McFarlane; et al. (IAAI, 2009)

Learning Algorithms for Link Prediction Based on Chance Constraints. - Janardhan Rao Doppa; Jun Yu; Prasad Tadepalli; Lise Getoor (ECML/PKDD (1), 2010)

Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. - Shahed Sorower; Thomas G. Dietterich; Janardhan Rao Doppa; John Walker Orr; Prasad Tadepalli; Xiaoli Z. Fern (NIPS, 2011)

Learning Rules from Incomplete Examples via Implicit Mention Models. - Janardhan Rao Doppa; Shahed Sorower; Mohammad NasrEsfahani; John Walker Orr; Thomas G. Dietterich; Xiaoli Z. Fern; Prasad Tadepalli; Jed Irvine (ACML, 2011)

Output Space Search for Structured Prediction. - Janardhan Rao Doppa; Alan Fern; Prasad Tadepalli (ICML, 2012)

An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. - Xiaoqin Zhang 001; Bhavesh Shrestha; Sung Wook Yoon; Subbarao Kambhampati; Phillip DiBona; Jinhong K. Guo; Daniel McFarlane; Martin O. Hofmann; Kenneth R. Whitebread; Darren Scott Appling; Elizabeth T. Whitaker; Ethan Trewhitt; et al. (ACM Trans. Intell. Syst. Technol., 2012)

HC-Search: Learning Heuristics and Cost Functions for Structured Prediction. - Janardhan Rao Doppa; Alan Fern; Prasad Tadepalli (AAAI, 2013)

Learning to Detect Basal Tubules of Nematocysts in SEM Images. - Michael Lam; Janardhan Rao Doppa; Xu Hu; Sinisa Todorovic; Thomas G. Dietterich; Abigail Reft; Marymegan Daly (ICCV Workshops, 2013)

HC-Search for Multi-Label Prediction: An Empirical Study. - Janardhan Rao Doppa; Jun Yu; Chao Ma 001; Alan Fern; Prasad Tadepalli (AAAI, 2014)

Learning Scripts as Hidden Markov Models. - John Walker Orr; Prasad Tadepalli; Janardhan Rao Doppa; Xiaoli Z. Fern; Thomas G. Dietterich (AAAI, 2014)

Prune-and-Score: Learning for Greedy Coreference Resolution. - Chao Ma 001; Janardhan Rao Doppa; John Walker Orr; Prashanth Mannem; Xiaoli Z. Fern; Thomas G. Dietterich; Prasad Tadepalli (EMNLP, 2014)

HC-Search: A Learning Framework for Search-based Structured Prediction. - Janardhan Rao Doppa; Alan Fern; Prasad Tadepalli (J. Artif. Intell. Res., 2014)

Structured prediction via output space search. - Janardhan Rao Doppa; Alan Fern; Prasad Tadepalli (J. Mach. Learn. Res., 2014)

Learning Greedy Policies for the Easy-First Framework. - Jun Xie; Chao Ma 001; Janardhan Rao Doppa; Prashanth Mannem; Xiaoli Z. Fern; Thomas G. Dietterich; Prasad Tadepalli (AAAI, 2015)

ℋC-search for structured prediction in computer vision. - Michael Lam; Janardhan Rao Doppa; Sinisa Todorovic; Thomas G. Dietterich (CVPR, 2015)

Optimizing 3D NoC Design for Energy Efficiency: A Machine Learning Approach. - Sourav Das 002; Janardhan Rao Doppa; Daehyun Kim 004; Partha Pratim Pande; Krishnendu Chakrabarty (ICCAD, 2015)

Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications. - Bryan David Minor; Janardhan Rao Doppa; Diane J. Cook (KDD, 2015)

Hybrid network-on-chip architectures for accelerating deep learning kernels on heterogeneous manycore platforms. - Wonje Choi 001; Karthi Duraisamy; Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande; Radu Marculescu; Diana Marculescu (CASES, 2016)

Reliability and performance trade-offs for 3D NoC-enabled multicore chips. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (DATE, 2016)

Energy-efficient and reliable 3D network-on-chip (NoC): architectures and optimization algorithms. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ICCAD, 2016)

Design-Space Exploration and Optimization of an Energy-Efficient and Reliable 3D Small-world Network-on-Chip. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (CoRR, 2016)

Active Preference Elicitation for Planning. - Mayukh Das; Md. Rakibul Islam 001; Janardhan Rao Doppa; Dan Roth 001; Sriraam Natarajan (AAAI Workshops, 2017)

Towards Problem Solving Agents that Communicate and Learn. - Anjali Narayan-Chen; Colin Graber; Mayukh Das; Md. Rakibul Islam 001; Soham Dan; Sriraam Natarajan; Janardhan Rao Doppa; Julia Hockenmaier; Martha Palmer; Dan Roth 001 (RoboNLP@ACL, 2017)

Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. - Chao Ma 001; Janardhan Rao Doppa; Prasad Tadepalli; Hamed Shahbazi; Xiaoli Z. Fern (ACML, 2017)

Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search. - F. A. Rezaur Rahman Chowdhury; Chao Ma 001; Md. Rakibul Islam 001; Mohammad Hossein Namaki; Mohammad Omar Faruk; Janardhan Rao Doppa (ACML, 2017)

Learning to Speed Up Query Planning in Graph Databases. - Mohammad Hossein Namaki; F. A. Rezaur Rahman Chowdhury; Md. Rakibul Islam 001; Janardhan Rao Doppa; Yinghui Wu 001 (ICAPS, 2017)

Data analytics enables energy-efficiency and robustness: from mobile to manycores, datacenters, and networks (special session paper). - Sudeep Pasricha; Janardhan Rao Doppa; Krishnendu Chakrabarty; Saideep Tiku; Daniel Dauwe; Shi Jin 001; Partha Pratim Pande (CODES+ISSS, 2017)

Robust TSV-based 3D NoC design to counteract electromigration and crosstalk noise. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (DATE, 2017)

Monolithic 3D-Enabled High Performance and Energy Efficient Network-on-Chip. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ICCD, 2017)

Adaptive Manycore Architectures for Big Data Computing. - Janardhan Rao Doppa; Ryan Gary Kim; Mihailo Isakov; Michel A. Kinsy; Hyoukjun Kwon; Tushar Krishna (NOCS, 2017)

3D NoC-Enabled Heterogeneous Manycore Architectures for Accelerating CNN Training: Performance and Thermal Trade-offs. - Biresh Kumar Joardar; Wonje Choi 001; Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (NOCS, 2017)

Design-Space Exploration and Optimization of an Energy-Efficient and Reliable 3-D Small-World Network-on-Chip. - Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications. - Bryan David Minor; Janardhan Rao Doppa; Diane J. Cook (IEEE Trans. Knowl. Data Eng., 2017)

VFI-Based Power Management to Enhance the Lifetime of High-Performance 3D NoCs. - Sourav Das 002; Dongjin Lee; Wonje Choi 001; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ACM Trans. Design Autom. Electr. Syst., 2017)

Imitation Learning for Dynamic VFI Control in Large-Scale Manycore Systems. - Ryan Gary Kim; Wonje Choi 001; Zhuo Chen; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (IEEE Trans. Very Large Scale Integr. Syst., 2017)

Bayesian Optimization Meets Search Based Optimization: A Hybrid Approach for Multi-Fidelity Optimization. - Ellis Hoag; Janardhan Rao Doppa (AAAI, 2018)

Preference-Guided Planning: An Active Elicitation Approach. - Mayukh Das; Phillip Odom; Md. Rakibul Islam 001; Janardhan Rao Doppa; Dan Roth 001; Sriraam Natarajan (AAMAS, 2018)

Hybrid on-chip communication architectures for heterogeneous manycore systems. - Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (ICCAD, 2018)

Machine learning for design space exploration and optimization of manycore systems. - Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande (ICCAD, 2018)

Abetting Planned Obsolescence by Aging 3D Networks-on-Chip. - Sourav Das 002; Kanad Basu; Janardhan Rao Doppa; Partha Pratim Pande; Ramesh Karri; Krishnendu Chakrabarty (NOCS, 2018)

Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis. - Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (Computer, 2018)

Active Anomaly Detection via Ensembles. - Shubhomoy Das; Md. Rakibul Islam 001; Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa (CoRR, 2018)

GLAD: GLocalized Anomaly Detection via Active Feature Space Suppression. - Shubhomoy Das; Janardhan Rao Doppa (CoRR, 2018)

Design Space Exploration of 3D Network-on-Chip: A Sensitivity-based Optimization Approach. - Dongjin Lee; Sourav Das 002; Dae Hyun Kim 004; Janardhan Rao Doppa; Partha Pratim Pande (ACM J. Emerg. Technol. Comput. Syst., 2018)

On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems. - Wonje Choi 001; Karthi Duraisamy; Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (IEEE Trans. Computers, 2018)

Trading-Off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach. - Nitthilan Kannappan Jayakodi; Anwesha Chatterjee; Wonje Choi 001; Janardhan Rao Doppa; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018)

Performance and Thermal Tradeoffs for Energy-Efficient Monolithic 3D Network-on-Chip. - Dongjin Lee; Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ACM Trans. Design Autom. Electr. Syst., 2018)

Scalable Network-on-Chip Architectures for Brain-Machine Interface Applications. - Xian Li; Karthi Duraisamy; Paul Bogdan; Janardhan Rao Doppa; Partha Pratim Pande (IEEE Trans. Very Large Scale Integr. Syst., 2018)

Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. - Paul Bogdan; Fan Chen 001; Aryan Deshwal; Janardhan Rao Doppa; Biresh Kumar Joardar; Hai (Helen) Li; Shahin Nazarian; Linghao Song; Yao Xiao (CODES+ISSS, 2019)

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 (DATE, 2019)

REGENT: A Heterogeneous ReRAM/GPU-based Architecture Enabled by NoC for Training CNNs. - Biresh Kumar Joardar; Bing Li 017; Janardhan Rao Doppa; Hai Li 001; Partha Pratim Pande; Krishnendu Chakrabarty (DATE, 2019)

Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning. - Chao Ma 001; F. A. Rezaur Rahman Chowdhury; Aryan Deshwal; Md. Rakibul Islam 001; Janardhan Rao Doppa; Dan Roth 001 (IJCAI, 2019)

Learning and Inference for Structured Prediction: A Unifying Perspective. - Aryan Deshwal; Janardhan Rao Doppa; Dan Roth 001 (IJCAI, 2019)

Max-value Entropy Search for Multi-Objective Bayesian Optimization. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (NeurIPS, 2019)

Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability. - Shubhomoy Das; Md. Rakibul Islam 001; Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa (CoRR, 2019)

One-Shot Induction of Generalized Logical Concepts via Human Guidance. - Mayukh Das; Nandini Ramanan; Janardhan Rao Doppa; Sriraam Natarajan (CoRR, 2019)

Guest Editors' Introduction: Special Issue on Smart and Autonomous Systems for Sustainability. - Janardhan Rao Doppa; Justinian Rosca; Paul Bogdan (IEEE Des. Test, 2019)

Autonomous Design Space Exploration of Computing Systems for Sustainability: Opportunities and Challenges. - Janardhan Rao Doppa; Justinian Rosca; Paul Bogdan (IEEE Des. Test, 2019)

Planning with actively eliciting preferences. - Mayukh Das; Phillip Odom; Md. Rakibul Islam 001; Janardhan Rao Doppa; Dan Roth 001; Sriraam Natarajan (Knowl. Based Syst., 2019)

Learning-Based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems. - Biresh Kumar Joardar; Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande; Diana Marculescu; Radu Marculescu (IEEE Trans. Computers, 2019)

MOOS: A Multi-Objective Design Space Exploration and Optimization Framework for NoC Enabled Manycore Systems. - Aryan Deshwal; Nitthilan Kannappan Jayakodi; Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande (ACM Trans. Embed. Comput. Syst., 2019)

Impact of Electrostatic Coupling on Monolithic 3D-enabled Network on Chip. - Dongjin Lee; Sourav Das 002; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ACM Trans. Design Autom. Electr. Syst., 2019)

Dynamic Resource Management of Heterogeneous Mobile Platforms via Imitation Learning. - Sumit K. Mandal; Ganapati Bhat; Chetan Arvind Patil; Janardhan Rao Doppa; Partha Pratim Pande; Ümit Y. Ogras (IEEE Trans. Very Large Scale Integr. Syst., 2019)

Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (AAAI, 2020)

Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. - Syrine Belakaria; Aryan Deshwal; Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa (AAAI, 2020)

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework. - Aryan Deshwal; Syrine Belakaria; Janardhan Rao Doppa; Alan Fern (AAAI, 2020)

PETNet: Polycount and Energy Trade-off Deep Networks for Producing 3D Objects from Images. - Nitthilan Kanappan Jayakodi; Janardhan Rao Doppa; Partha Pratim Pande (DAC, 2020)

Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs. - Sumit K. Mandal; Ümit Y. Ogras; Janardhan Rao Doppa; Raid Zuhair Ayoub; Michael Kishinevsky; Partha Pratim Pande (DAC, 2020)

GRAMARCH: A GPU-ReRAM based Heterogeneous Architecture for Neural Image Segmentation. - Biresh Kumar Joardar; Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa; Hai Li 001; Partha Pratim Pande; Krishnendu Chakrabarty (DATE, 2020)

Power, Performance, and Thermal Trade-offs in M3D-enabled Manycore Chips. - Shouvik Musavvir; Anwesha Chatterjee; Ryan Gary Kim; Dae Hyun Kim 004; Janardhan Rao Doppa; Partha Pratim Pande (DATE, 2020)

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 (DATE, 2020)

SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms. - Nitthilan Kanappan Jayakodi; Janardhan Rao Doppa; Partha Pratim Pande (ICCAD, 2020)

Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data. - Garrett Wilson; Janardhan Rao Doppa; Diane J. Cook (KDD, 2020)

Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (CoRR, 2020)

Scalable Combinatorial Bayesian Optimization with Tractable Statistical models. - Aryan Deshwal; Syrine Belakaria; Janardhan Rao Doppa (CoRR, 2020)

Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (CoRR, 2020)

Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (CoRR, 2020)

Few-Shot Induction of Generalized Logical Concepts via Human Guidance. - Mayukh Das; Nandini Ramanan; Janardhan Rao Doppa; Sriraam Natarajan (Frontiers Robotics AI, 2020)

Making a Case for Partially Connected 3D NoC: NFIC versus TSV. - Aqeeb Iqbal Arka; Srinivasan Gopal; Janardhan Rao Doppa; Deukhyoun Heo; Partha Pratim Pande (ACM J. Emerg. Technol. Comput. Syst., 2020)

3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks. - Bing Li 017; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty; Joe X. Qiu; Hai (Helen) Li (ACM J. Emerg. Technol. Comput. Syst., 2020)

Analyzing Deep Learning for Time-Series Data Through Adversarial Lens in Mobile and IoT Applications. - Taha Belkhouja; Janardhan Rao Doppa (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. - Nitthilan Kanappan Jayakodi; Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (ACM Trans. Embed. Comput. Syst., 2020)

An Energy-aware Online Learning Framework for Resource Management in Heterogeneous Platforms. - Sumit K. Mandal; Ganapati Bhat; Janardhan Rao Doppa; Partha Pratim Pande; Ümit Y. Ogras (ACM Trans. Design Autom. Electr. Syst., 2020)

Mercer Features for Efficient Combinatorial Bayesian Optimization. - Aryan Deshwal; Syrine Belakaria; Janardhan Rao Doppa (AAAI, 2021)

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 (DAC, 2021)

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 (DATE, 2021)

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 (DATE, 2021)

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 (ICCAD, 2021)

A General Hardware and Software Co-Design Framework for Energy-Efficient Edge AI. - Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa; Partha Pratim Pande (ICCAD, 2021)

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 001; Krishnendu Chakrabarty (ICCAD, 2021)

Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise. - Xiaoxuan Yang 001; Syrine Belakaria; Biresh Kumar Joardar; Huanrui Yang; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty; Hai Helen Li (ICCAD, 2021)

Bayesian Optimization over Hybrid Spaces. - Aryan Deshwal; Syrine Belakaria; Janardhan Rao Doppa (ICML, 2021)

Adaptive Experimental Design for Optimizing Combinatorial Structures. - Janardhan Rao Doppa (IJCAI, 2021)

Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces. - Aryan Deshwal; Janardhan Rao Doppa (NeurIPS, 2021)

ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs. - Biresh Kumar Joardar; Janardhan Rao Doppa; Hai Li 001; Krishnendu Chakrabarty; Partha Pratim Pande (CoRR, 2021)

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. - Syrine Belakaria; Aryan Deshwal; Janardhan Rao Doppa (J. Artif. Intell. Res., 2021)

Power Management of Monolithic 3D Manycore Chips with Inter-tier Process Variations. - Anwesha Chatterjee; Shouvik Musavvir; Ryan Gary Kim; Janardhan Rao Doppa; Partha Pratim Pande (ACM J. Emerg. Technol. Comput. Syst., 2021)

AccuReD: High Accuracy Training of CNNs on ReRAM/GPU Heterogeneous 3-D Architecture. - Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande; Hai Li 001; Krishnendu Chakrabarty (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

Learning to Train CNNs on Faulty ReRAM-based Manycore Accelerators. - Biresh Kumar Joardar; Janardhan Rao Doppa; Hai Li 001; Krishnendu Chakrabarty; Partha Pratim Pande (ACM Trans. Embed. Comput. Syst., 2021)

HeM3D: Heterogeneous Manycore Architecture Based on Monolithic 3D Vertical Integration. - Aqeeb Iqbal Arka; Biresh Kumar Joardar; Ryan Gary Kim; Dae Hyun Kim 004; Janardhan Rao Doppa; Partha Pratim Pande (ACM Trans. Design Autom. Electr. Syst., 2021)

Performance and Accuracy Tradeoffs for Training Graph Neural Networks on ReRAM-Based Architectures. - Aqeeb Iqbal Arka; Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (IEEE Trans. Very Large Scale Integr. Syst., 2021)

Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis. - Taha Belkhouja; Yan Yan 006; Janardhan Rao Doppa (AAAI, 2022)

Bayesian Optimization over Permutation Spaces. - Aryan Deshwal; Syrine Belakaria; Janardhan Rao Doppa; Dae Hyun Kim 004 (AAAI, 2022)

Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health. - Dina Hussein; Ganapati Bhat; Janardhan Rao Doppa (AAAI, 2022)

DIET: A Dynamic Energy Management Approach for Wearable Health Monitoring Devices. - Nuzhat Yamin; Ganapati Bhat; Janardhan Rao Doppa (DATE, 2022)

Reliable Machine Learning for Wearable Activity Monitoring: Novel Algorithms and Theoretical Guarantees. - Dina Hussein; Taha Belkhouja; Ganapati Bhat; Janardhan Rao Doppa (ICCAD, 2022)

Fault-Tolerant Deep Learning Using Regularization. - Biresh Kumar Joardar; Aqeeb Iqbal Arka; Janardhan Rao Doppa; Partha Pratim Pande (ICCAD, 2022)

NoC-enabled 3D Heterogeneous Manycore Systems for Big-Data Applications. - Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (ISQED, 2022)

Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition. - Garrett Wilson; Janardhan Rao Doppa; Diane J. Cook (CoRR, 2022)

Human-guided Collaborative Problem Solving: A Natural Language based Framework. - Harsha Kokel; Mayukh Das; Md. Rakibul Islam 001; Julia Bonn; Jon Z. Cai; Soham Dan; Anjali Narayan-Chen; Prashant Jayannavar; Janardhan Rao Doppa; Julia Hockenmaier; Sriraam Natarajan; Martha Palmer; et al. (CoRR, 2022)

Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features. - Taha Belkhouja; Janardhan Rao Doppa (J. Artif. Intell. Res., 2022)

High-Throughput Training of Deep CNNs on ReRAM-Based Heterogeneous Architectures via Optimized Normalization Layers. - Biresh Kumar Joardar; Aryan Deshwal; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Accelerating Large-Scale Graph Neural Network Training on Crossbar Diet. - Chukwufumnanya Ogbogu; Aqeeb Iqbal Arka; Biresh Kumar Joardar; Janardhan Rao Doppa; Hai Helen Li; Krishnendu Chakrabarty; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

SWAP: A Server-Scale Communication-Aware Chiplet-Based Manycore PIM Accelerator. - Harsh Sharma; Sumit K. Mandal; Janardhan Rao Doppa; Ümit Y. Ogras; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis. - Subhankar Ghosh; Taha Belkhouja; Yan Yan 006; Janardhan Rao Doppa (AAAI, 2023)

Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach. - Syrine Belakaria; Janardhan Rao Doppa; Nicolò Fusi; Rishit Sheth (AISTATS, 2023)

Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. - Aryan Deshwal; Sebastian Ament; Maximilian Balandat; Eytan Bakshy; Janardhan Rao Doppa; David Eriksson (AISTATS, 2023)

Achieving Datacenter-scale Performance through Chiplet-based Manycore Architectures. - Harsh Sharma; Sumit K. Mandal; Janardhan Rao Doppa; Ümit Y. Ogras; Partha Pratim Pande (DATE, 2023)

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 (DATE, 2023)

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 (ETS, 2023)

Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features (Extended Abstract). - Taha Belkhouja; Janardhan Rao Doppa (IJCAI, 2023)

Energy-Efficient Missing Data Recovery in Wearable Devices: A Novel Search-Based Approach. - Dina Hussein; Taha Belkhouja; Ganapati Bhat; Janardhan Rao Doppa (ISLPED, 2023)

Uncertainty-Aware Online Learning for Dynamic Power Management in Large Manycore Systems. - Gaurav Narang; Raid Ayoub; Michael Kishinevsky; Janardhan Rao Doppa; Partha Pratim Pande (ISLPED, 2023)

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 (ISLPED, 2023)

Probabilistically robust conformal prediction. - Subhankar Ghosh; Yuanjie Shi; Taha Belkhouja; Yan Yan 006; Jana Doppa; Brian Jones (UAI, 2023)

Accelerating Graph Neural Network Training on ReRAM-Based PIM Architectures via Graph and Model Pruning. - Chukwufumnanya Ogbogu; Aqeeb Iqbal Arka; Lukas Pfromm; Biresh Kumar Joardar; Janardhan Rao Doppa; Krishnendu Chakrabarty; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

ReaLPrune: ReRAM Crossbar-Aware Lottery Ticket Pruning for CNNs. - Biresh Kumar Joardar; Janardhan Rao Doppa; Hai (Helen) Li; Krishnendu Chakrabarty; Partha Pratim Pande (IEEE Trans. Emerg. Top. Comput., 2023)

Dynamic Time Warping Based Adversarial Framework for Time-Series Domain. - Taha Belkhouja; Yan Yan 006; Janardhan Rao Doppa (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

ESSENCE: Exploiting Structured Stochastic Gradient Pruning for Endurance-Aware ReRAM-Based In-Memory Training Systems. - Xiaoxuan Yang 001; Huanrui Yang; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty; Hai Li 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Dynamic Power Management in Large Manycore Systems: A Learning-to-Search Framework. - Gaurav Narang; Aryan Deshwal; Raid Ayoub; Michael Kishinevsky; Janardhan Rao Doppa; Partha Pratim Pande (ACM Trans. Design Autom. Electr. Syst., 2023)

Florets for Chiplets: Data Flow-aware High-Performance and Energy-efficient Network-on-Interposer for CNN Inference Tasks. - Harsh Sharma; Lukas Pfromm; Rasit Onur Topaloglu; Janardhan Rao Doppa; Ümit Y. Ogras; Ananth Kalyanaraman; Partha Pratim Pande (ACM Trans. Embed. Comput. Syst., 2023)

CALDA: Improving Multi-Source Time Series Domain Adaptation With Contrastive Adversarial Learning. - Garrett Wilson; Janardhan Rao Doppa; Diane J. Cook (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization. - Alaleh Ahmadianshalchi; Syrine Belakaria; Janardhan Rao Doppa (AAAI, 2024)

Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract). - Alaleh Ahmadianshalchi; Syrine Belakaria; Janardhan Rao Doppa (AAAI, 2024)

Offline Model-Based Optimization via Policy-Guided Gradient Search. - Yassine Chemingui; Aryan Deshwal; Trong Nghia Hoang; Janardhan Rao Doppa (AAAI, 2024)

Preference-Aware Constrained Multi-Objective Bayesian Optimization. - Alaleh Ahmadianshalchi; Syrine Belakaria; Janardhan Rao Doppa (COMAD/CODS, 2024)

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 (DATE, 2024)

Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads. - Harsh Sharma; Gaurav Narang; Janardhan Rao Doppa; Ümit Y. Ogras; Partha Pratim Pande (DATE, 2024)

Heterogeneous Manycore In-Memory Computing Architectures. - Chukwufumnanya Ogbogu; Gaurav Narang; Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande (ICCAD, 2024)

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching. - Minh Hoang; Azza Fadhel; Aryan Deshwal; Jana Doppa; Trong Nghia Hoang (ICML, 2024)

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 (IJCAI, 2024)

Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach. - Dina Hussein; Taha Belkhouja; Ganapati Bhat; Janardhan Rao Doppa (IJCAI, 2024)

HeTraX: Energy Efficient 3D Heterogeneous Manycore Architecture for Transformer Acceleration. - Pratyush Dhingra; Jana Doppa; Partha Pratim Pande (ISLPED, 2024)

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 (ITC, 2024)

Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. - Syrine Belakaria; Ben Letham; Jana Doppa; Barbara Engelhardt; Stefano Ermon; Eytan Bakshy (NeurIPS, 2024)

Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration. - Yuanjie Shi; Subhankar Ghosh; Taha Belkhouja; Jana Doppa; Yan Yan 006 (NeurIPS, 2024)

Thermal Modeling and Management Challenges in Heterogenous Integration: 2.5D Chiplet Platforms and Beyond. - Jaehyun Park 005; Alish Kanani; Lukas Pfromm; Harsh Sharma; Parth Solanki; Eric Tervo; Janardhan Rao Doppa; Partha Pratim Pande; Ümit Y. Ogras (VTS, 2024)

AgAID Institute - AI for agricultural labor and decision support. - Alan Fern; Margaret Burnett; Joseph R. Davidson; Janardhan Rao Doppa; Paola Pesántez-Cabrera; Ananth Kalyanaraman (AI Mag., 2024)

Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach. - Mohammed Amine Gharsallaoui; Bhupinderjeet Singh; Supriya Savalkar; Aryan Deshwal; Yan Yan 006; Ananth Kalyanaraman; Kirti Rajagopalan; Janardhan Rao Doppa (CoRR, 2024)

Scalable and Programmable Look-Up Table based Neural Acceleration (LUT-NA) for Extreme Energy Efficiency. - Ovishake Sen; Chukwufumnanya Ogbogu; Peyman Dehghanzadeh; Janardhan Rao Doppa; Swarup Bhunia; Partha Pratim Pande; Baibhab Chatterjee (CoRR, 2024)

MFIT: Multi-Fidelity Thermal Modeling for 2.5D and 3D Multi-Chiplet Architectures. - Lukas Pfromm; Alish Kanani; Harsh Sharma; Parth Solanki; Eric Tervo; Jaehyun Park 005; Janardhan Rao Doppa; Partha Pratim Pande; Ümit Y. Ogras (CoRR, 2024)

Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning. - Shubhomoy Das; Md. Rakibul Islam 001; Nitthilan Kannappan Jayakodi; Janardhan Rao Doppa (J. Artif. Intell. Res., 2024)

Data Pruning-enabled High Performance and Reliable Graph Neural Network Training on ReRAM-based Processing-in-Memory Accelerators. - Chukwufumnanya Ogbogu; Biresh Kumar Joardar; Krishnendu Chakrabarty; Jana Doppa; Partha Pratim Pande (ACM Trans. Design Autom. Electr. Syst., 2024)

Out-of-distribution Detection in Time-series Domain: A Novel Seasonal Ratio Scoring Approach. - Taha Belkhouja; Yan Yan 006; Janardhan Rao Doppa (ACM Trans. Intell. Syst. Technol., 2024)

Mitigating Slow-to-Write Errors in Memristor-Mapped Graph Neural Networks Induced by Adversarial Attacks. - Ching-Yuan Chen; Biresh Kumar Joardar; Janardhan Rao Doppa; Partha Pratim Pande; Krishnendu Chakrabarty (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

TEFLON: Thermally Efficient Dataflow-aware 3D NoC for Accelerating CNN Inferencing on Manycore PIM Architectures. - Gaurav Narang; Chukwufumnanya Ogbogu; Janardhan Rao Doppa; Partha Pratim Pande (ACM Trans. Embed. Comput. Syst., 2024)

HuNT: Exploiting Heterogeneous PIM Devices to Design a 3-D Manycore Architecture for DNN Training. - Chukwufumnanya Ogbogu; Gaurav Narang; Biresh Kumar Joardar; Janardhan Rao Doppa; Krishnendu Chakrabarty; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-Based DNN Accelerators. - Xueying Wu; Edward Hanson; Nansu Wang; Qilin Zheng; Xiaoxuan Yang 001; Huanrui Yang; Shiyu Li 001; Feng Cheng; Partha Pratim Pande; Janardhan Rao Doppa; Krishnendu Chakrabarty; Hai Li 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning. - Yassine Chemingui; Aryan Deshwal; Honghao Wei; Alan Fern; Jana Doppa (AAAI, 2025)

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 (DATE, 2025)

Odin: Learning to Optimize Operation Unit Configuration for Energy-efficient DNN Inferencing. - Gaurav Narang; Janardhan Rao Doppa; Partha Pratim Pande (DATE, 2025)

Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression. - Hooman Shahrokhi; Devjeet Raj Roy; Yan Yan 006; Venera Arnaoudova; Jana Doppa (UAI, 2025)

Non-Myopic Multi-Objective Bayesian Optimization. - Syrine Belakaria; Alaleh Ahmadianshalchi; Barbara E. Engelhardt; Stefano Ermon; Jana Doppa (Trans. Mach. Learn. Res., 2025)

Sensor-Aware Data Imputation for Time-Series Machine Learning on Low-Power Wearable Devices. - Dina Hussein; Taha Belkhouja; Ganapati Bhat; Jana Doppa (ACM Trans. Design Autom. Electr. Syst., 2025)

A Heterogeneous Chiplet Architecture for Accelerating End-to-End Transformer Models. - Harsh Sharma; Pratyush Dhingra; Jana Doppa; Ümit Y. Ogras; Partha Pratim Pande (ACM Trans. Design Autom. Electr. Syst., 2025)

Direct Prediction Set Minimization via Bilevel Conformal Classifier Training. - Yuanjie Shi; Hooman Shahrokhi; Xuesong Jia; Xiongzhi Chen; Janardhan Rao Doppa; Yan Yan 006 (CoRR, 2025)

Energy-Efficient DNN Inferencing on ReRAM-Based PIM Accelerators Using Heterogeneous Operation Units. - Gaurav Narang; Janardhan Rao Doppa; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

Designing High-Performance and Thermally Feasible Multi-Chiplet Architectures enabled by Non-bendable Glass Interposer. - Harsh Sharma; Janardhan Rao Doppa; Ümit Y. Ogras; Partha Pratim Pande (CoRR, 2025)

THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures. - Alish Kanani; Lukas Pfromm; Harsh Sharma; Janardhan Rao Doppa; Partha Pratim Pande; Ümit Y. Ogras (CoRR, 2025)

Atleus: Accelerating Transformers on the Edge Enabled by 3D Heterogeneous Manycore Architectures. - Pratyush Dhingra; Janardhan Rao Doppa; Partha Pratim Pande (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)