Research Topics

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:

  • Trusted AI
  • Foundational Advances in AI Algorithms
  • AI Automation
  • Natural Language Processing
  • Human-Centered AI
  • High Performance and Efficient AI Infrastructure
  • AI for Applications

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

Rongjie Lai

Jie Chen

Neural Memories for Text and Knowledge Graphs

Mohammed J. Zaki

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