Research scientists and faculty at Rensselaer join forces with IBM researchers to collaborate on projects that push the frontiers in Artificial Intelligence
The AI Research Collaboration is focused on joint research in a number of areas including:
| Projects | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| 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 |
| 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 |
| 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 |
| Projects | 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 |
| Explainable Transfer Learning | Chris Sims, Jim Hendler |
Keerthiram Murugesan, Pin-Yu Chen, Amit Dhurandhar, Ronny Luss, Karthikeyan Shanmugam |
| 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 |
| Provably Efficient Reinforcement Learning via Neuro-Symbolic Representations | Meng Wang, Tianyi Chen |
Miao Liu, Pin-Yu Chen, Songtao Lu |
| 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 |
| Projects | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| *Active Learning for Automated Decision-Making | Ali Tajer |
Payel Das |
| *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 |
| GATOR: The Goal-oriented Autonomous Dialogue System | Tomek Strzalkowski |
Mo Yu |
| 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 |
| Training Neural Network with Few-Shot Data & Applications to AI Automation | Jianxi Gao |
Pin-Yu Chen, Pedapati Tejaswini |
| Projects | RPI Principal Investigators | IBM Principal Investigators |
|---|---|---|
| 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 |
| 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 |
| 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 |
| Manifold-Structured Latent Space for Deep Generative Modeling | ||
| Neural Memories for Text and Knowledge Graphs | Dimitry Krotov |
|
| Semantic shift as measure of bias with applications to detection, explanation and mitigation of misinformation | Sibel Adali |
Pin-Yu Chen |
| Projects | 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 |
| MIKA: Music Knowledge Intelligence Agent | Curtis Bahn, Jonas Braasch, Mary Simoni |
|
| 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 |
