Projects
2025
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Theoretical and Algorithmic Foundations of In-Context Learning and Chain of Thought Using Properly Trained Transformer Models | Meng Wang | Songtao Lu, Pin-Yu Chen, Xiaodong Cui |
| High resolution x-ray imaging for 3D-HI chiplet non-destructive internal metal joints inspection | Edwin Fohtung, James Lu | Roy Yu, Katsuyuki Sakuma |
| Control of orientation and handedness of nanoscale topological and directional interconnect conductors on amorphous SiO2 | Jian Shi, Ravishankar Sundararaman | Ching-Tzu Chen, Fausto Martelli |
| Interpretable Foundation Models for General-Purpose Time Series Analysis | Agung Julius | Lam Nguyen |
| Key-Value Cache Compression for Memory-Efficient Large Language Model Inference | Mohammad Mohammadi Amiri | Pin-Yu Chen, Tejaswini Pedapati, Subhajit Chaudhury |
| Strategic AI: Enhancing Large Language Model Agents with Decision-Making Algorithms for Advanced Reasoning and Planning | Santiago Paternain | Dharmashankar Subramanian |
| Low-precision Distributed Accelerated Methods and Library Development for Training and Fine-tuning Foundation Models | Yangyang Xu, George Slota | Jie Chen, Naigang Wang |
| Efficient Deployment of Large Language Model over Heterogeneous Computing Systems | Meng Wang, Tong Zhang | Kaoutar El Maghraoui, Naigang Wang |
| Intermetallic compounds for high-conductivity interconnects | Daniel Gall | Atharv Jog, Ching-Tzu Chen, Nargess Arabchi |
| Large Language Models as Planning Domain Model Generators | Selmer Bringsjord | Kavitha Srinivas, Harsha Kokel, Michael Katz, Shirin Sohrabi |
| Closing the Accuracy Gap in Analog In-memory Training: Device-dependent Algorithms and Hyperparameter Search | Tianyi Chen, Liu Liu | Tayfun Gokmen, Omobayode Fagbohungbe |
| Bringing AI Intelligence to 5G/6G Edge Platform | Ish Jain, Ali Tajer | Alberto Gracia, Kaoutar El Maghraoui |
| Discovering topological materials for BEOL interconnects using ?rst-principles calculations and machine learning | Trevor David Rhone, Ravishankar Sundararaman | Ching-Tzu Chen, Dmitry Zubarev, Timothy Philip |
| Meta-Learned Digital Twins for Circuit Design in Chiplet Integration | Tianyi Chen | Cheng Chi, Songtao Lu, Xin Zhang, Shawn Pinkett |
| Validation of multiscale 3D chiplet stack thermal model with temperature-dependent materials through 3w measurements | Jacob Merson, Theodorian Borca-Tasciuc, Max Bloomfield | Prabudhya Roy Chowdhury, Aakrati Jain |
| Optimization of Hardware-based Neural Network Accelerators for Fluorescence Lifetime in Biomedical Applications | Xavier Intes, Vikas Pandey | Karthik Swaminathan, Aporva Amarnath, Nigang Wang |
| Integration and Scheduling of High Performance Computing (HPC) and Quantum Computing Workflows | Christopher Carothers | Antonio Córcoles |
| Holistic Algorithm-Architecture Co-Design of Approximate Computing for Scalable Foundation Models | Tong Zhang, Liu Liu | Swagath Venkataramani, Sanchari Sen |
| E-beam glancing angle scattering for hybrid bonding surface planarity measurement | Gwo-Ching Wang, Toh-Ming Lu | Nicholas Polomoff, Katsuyuki Sakuma |
| Educating the Quantum Future: Filling the Pipeline from Middle School to the Workforce | Brian Callahan, Malik Magdon-Ismail, Ali Tajer | |
| Associative Energy-based Diffusion Models for Generative AI | Mohammed J. Zaki | Dmitry Krotov, Rogerio S. Feris |
| Quantum Computing Exploration to Advance Supply Chain | Ruimin Ke, Jose Holguin-Veras, Xiaokun (Cara) Wang, Xiaozheng (Sean) He | |
| Fast Inference and Alignment for Large Multi-modal Models | Koushik Kar, Tianyi Chen | Parikshit Ram, Nathalie Baracaldo, Yi Zhou, Horst Samulowitz, Ken Wong |
| HPC-assisted Hybrid Classical Quantum System for Drug Discovery and Development | Zhiding Liang, Xiao-Yang Liu, Tianfan Fu | |
| Molecular engineering of metal/low-k interfaces for Cu interconnects | Ganpati Ramanath, Pawel Keblinski | Dan Edelstein |
| Benchmarking Quantum Computational Methods for Thermo- Chemical Processes | Osama Raisuddin, Fabian Faulstich | |
| Meta-Transfer-Learning for Tabular Data Distillation, Generation, and Predictive Modeling | Oshani Seneviratne | Horst Samulowitz, Yi Zhou, Parikshit Ram |
| Enhancing Gate Fidelity and Speed Through AI-Driven Optimization for Hubbard Model Computation | Jian Shi, Yangyang Xu | |
| Model Optimization and Hardware-aware Neural Architecture Search for Spatiotemporal Data Mining | Yinan Wang, Liu Liu | Kaoutar El Maghraoui |
2024
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Foundational Models for Understanding Tabular Data Through AI Automation | Jianxi Gao | Kavitha Srinivas, Tejsawini Pedapati, Horst Samulowitz, Pin-Yu Chen |
| Low-precision second-order-type distributed methods for training and fine-tuning foundation | Yangyang Xu, George Slota | Jie Chen, Mayank Agarwal, Yikang Shen, Naigang Wang |
| Molecular nanoengineering of post-Cu-metal/dielectric interfaces for nanodevice wiring | Ganpati Ramanath, Pawel Keblinski, Ravishankar Sundararaman | Griselda Bonilla, Ching-tzu Chen, Atharv Jog |
| Multi-Objective Training of Foundation Acoustic Models for Automatic Speech Recognition | Tianyi Chen, Mei Si | Xiaodong Cui, Brian Kingsbury, Songtao Lu |
| Optimization of Hardware-based Neural Networks Accelerators for Fluorescence Lifetime Biomedical Applications | Xavier Intes | Karthik Swaminathan |
| Resource-Effective Fine-Tuning of Large Language Models | Mohammad Mohammadi Amiri | Pin-Yu Chen, Tejaswini Pedapati, Subhajit Chaudhury |
| Structured & Robust Neural Network Pruning on Low-Precision Hardware for Guaranteed Learning Performance for Complex Time-Series Datasets | Christopher Carothers, Meng Wang | Kaoutar El Maghraoui, Pin-Yu Chen, Naigang Wang |
| Algorithmic Innovations and Architectural Support towards In-Memory Training on Analog AI Accelerators | Tianyi Chen, Liu Liu | Tayfun Gokmen, Malte J. Rasch |
| Testing LLM Safety via Causal Reasoning | Ali Tajer | Prasanna Sattigeri, Dennis Wei, Dmitrity Katz-Rogozhnikov |
| Anisotropic Thermal Resistance Characterization of SI, BEOL, and underfill layers using 3 omega Joule heating thermometry and exploratory non-destructive scanning Thermal Microscopy/ Multiscale Thermal Modeling of 3D ICs | Theo Borca-Tasciuc, Jacob Merson, Max Bloomfield | Roy Yu, Timothy Chainer, Prabudhya Roy Chowdhury, Aakrati Jain, Mukta Farooq |
| Theoretical and Algorithmic Foundations of In-Context Learning Using Properly Trained Transformer Models | Meng Wang | Songtao Lu, Pin-Yu Chen |
| Control of orientation and handedness of nanoscale topological interconnect conductors on amorphous SiO2 | Jian Shi, Ravishankar Sundar | Ching-tzu Chen |
| Unlearning: Dynamics of Membership Privacy and Inference Attacks Against Large Language Models | Lei Yu | Magdon Ismail, Nathalie Baracaldo, Ling Cai |
| Co-Designing Analog AI System and Accelerator for Large Foundation Models | Liu Liu, Meng Wang | Sidney Tsai, Kaoutar El Maghraoui |
| Control-Based Reinforcement Learning | Santiago Paternain | Mark Squillante; Chai Wah Wu |
| Correctors and Selectors: Building An Ecosystem for LLM Alignment | Alex Gittens | Mikhail Yurochkin, Mayank Agarwal |
| Data Distillation in Tabular Date: A Foundation Model Approach | Oshani Seneviratne, Inwon Kang | Horst Samulowitz, Parikshit Ram, Yi Zhou |
| Discovering topological materials for BEOL Interconnects using first-principles calculations and machine learning | Trevor Rhone, Ravishankar Sundar | Ching-tzu Chen, Atharv Jog |
| Energy Transformer for Foundational Models | Mohammed Zaki | Dmitry Krotov, Benjamin Hoover, Hendrik Strobelt |
| FIT: Fast Inference using Transformer models | Koushik Kar, Tianyi Chen | Parikshit Ram, Nathalie Baracaldo, Yi Zhou, Soham Dan, Horst Samulowitz |
2023
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Provably Efficient Reinforcement Learning via Neuro-Symbolic Representations | Meng Wang, Tianyi Chen | Miao Liu, Pin-Yu Chen, Songtao Lu, Keerthiram Murugesa, Subhajit Chaudhury |
| Quickest Failure Prediction Algorithm for High Dimensional Time Series Data | Bulent Yener, Ali Tajer | Kyongmin Yeo, Wesley Gifford |
| Robustness of Causal Bandits | Ali Tajer | Prasanna Sattigeri, Dennis Wei, Dmitriy Katz-Rogozhnikov |
| SafeR: Automating Safe Reinforcement Learning | Sandipan Mishra, Santiago Paternain, Koushik Kar | Long Vu, Lan Hoany, Dharmashankar Subramanian |
| A Framework for Automating Decentralized Training of Foundation Models | Koushik Kar, Tianyi Chen | Theodoros Salonidis, Parikshit Ram, Nathalie Baracaldo, Yi Zhou |
| Deep Causal Representation Learning Towards Generalizable, Explainable, and Fair AI Systems | Qiang Ji | Tian Gao, Amit Dhurandhar |
| Enhancing Efficiency and Robustness Simultaneously in Processing Deep Neural Networks | Liu Liu | Swagath Venkataramani |
| Explainable Transfer Learning | Christopher Sims, James Hendler | Keerthiram Murugesan, Amit Dhurandhar, Ronny Luss, Pin-Yu Chen |
| Fairness Auditor: Stress-testing AI Fairness Methodologies using Synthetic Data | Kristin Bennett | Ioana Baldini, Dennis Wei, Jiaming Zeng |
| Large-Scale Foundation Acoustic Modeling for Automatic Speech Recognition | Tianyi Chen, Mei Si | Xiaodong Cui, Brian Kingsbury, Songtao Lu |
2022
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Accelerated and Compressed Distributed Stochastic Optimization for Deep Learning | Yangyang Xu | Jie Chen, Chia-Yu Chen, Songtao Lu |
| GATOR: The Goal-oriented Autonomous Dialogue System | Tomek Strzalkowski | Dakou Wang |
| Anomaly Detection on Knowledge Graphs | Alex Gittens, Mohammed Zaki | Charu Aggarwal |
| AutoDML: A Framework for Automating Decentralized Machine Learning | Koushik Kar, Tianyi Chen | Theodoros Salonidis, Parikshit Ram, Nathalie Baracaldo, Yi Zhou |
| Fairness Auditor Stress-Testing AI Fairness Methodologies Using Synthetic Data | Kristin Bennett | Yoonyoung Park, Ioana Baldini, Dennis Wei |
| Interpretable Failure Prediction Algorithm for Time Series Data | Bulent Yener | Kyongmin Yeo, Wesley Gifford |
| Joint Domain Generalization and Algorithm Robustness for Trusted AI | Pingkun Yan, Ali Tajer, Yangyang Xu | Karthikeyan Shanmugam, Richard Chen, Pin-Yu Chen, Amit Dhurandhar |
| Secure and Robust Cross-Silo Vertical Federated Learning | Stacy Patterson | Shiqiang Wang |
| Signal Temporal Logic Neural Network (STL-NN): A Neuro-Symbolic Framework for Human-Interpretable Machine Learning | Julius Agung | Achille Fokoue |
| Sufficiently Accurate Model Based Reinforcement Learning | Santiago Paternain | Dharmashankar Subramanian |
| Training Neural Network with Few-Shot Data & Applications to AI Automation | Jianxi Gao | Pin-Yu Chen, Tejaswini Pedapati |
2021
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Combining Learning and Reasoning for Embedding Ethical Properties in AI Group Decision Making | Lirong Xia | Francesca Rossi |
| Deep Learning for Trust in Cybersecurity | Nidhi Rastogi, Alex Gittens, Mohammed Zaki | Charu Aggarwal |
| Extracting Types from Python Machine Learning Libraries | Ana Milanova | Martin Hirzel, Julian Dolby |
| Fast Learning of Neural Network Models with Provable Generalizability | Meng Wang | Jinjun Xiong, Sijia Liu, Pin-Yu Chen |
| Manifold-Structured Latent Space for Deep Generative Modeling | Rongjie Lai | Jie Chen |
| Self-Supervision Method for Natural Language Processing and Applications | Sibel Adali | Pin-Yu Chen |
| Composable Systems | Christopher Carothers | Kailash Gopalakrishnan |
| Interpretable Similarity Metric Learning | Derya Malak, Ali Tajer, Bulent Yener | Karthikeyan Natesan Ramanurthy, Dennis Wei, Amit Dhurandhar |
| Towards a General Framework | Stacy Patterson | Shiqiang Wang |
| Active Learning for Automated Decision-Making | Active Learning for Automated Decision-Making | Payel Das |
2020
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Semantic shift as measure of bias with applications to detection, explanation and mitigation of misinformation | Sibel Adali | Pin-Yu Chen |
| A Code Knowledge Graph for Planning Data Science Experiments | Jamie McCusker, Deborah McGuinness | Kavitha Srinivas, Julian Dolby, Michael Katz, Octavian Udrea, Shirin Sohrabi Araghi |
| Active Learning of Adversarial Attack Boudaries | Ali Tajer | Payel Das |
| AI Models for Curation of Threat Intelligence | Nidhi Rastogi | Charu Aggarwal |
| Asynchronous and adaptive stochastic approximation methods for accelerating deep learning | Yangyang Xu | Jie Chen |
| Improving Generalization and Abstraction in Deep Reinforcement Learning | Chris R. Sims | Tim Klinger |
| Learning and Embedding Ethical Guidelines in Group Decision-Making AI | Lirong Xia | Francesca Rossi, Michael Hind, Pin-Yu Chen |
| Neural Memories for Text and Knowledge Graphs | Mohammed J. Zaki | Dimitry Krotov |
2019
| Project | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| Capacity Limited Reinforcement Learning in Minds and Machines | Chris Sims | Gerald Tesauro |
| Data Recovery and Subspace Clustering from Quantized and Corrupted Measurements | Meng Wang | Jinjung Xiong |
| Exploration of Artificial Intelligence Approaches to Earth Observing Remote Sensing | Kevin Rose, Peter Fox | Harry Kolar |
| Neural Memories: Distributed Representations and Associative Retrieval | Mohammed Zaki | Dmitry Krotov |
| Smart Contracts Augmented with Learning and Semantics | Oshani Seneviratne, Lirong Xia | Geeth De Mel |
| Tentacular AI (TAI) | Selmer Bringsjord, Naveen Govindarajulu | Karthik Talamadupula |
