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
Algorithmic Innovations and Architectural Support towards In-Memory Training on Analog AI Accelerators

Tianyi Chen, Liu Liu

Tayfun Gokmen, Malte J. Rasch

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, Jacob Merson

Roy Yu, Timothy Chainer, Prabudhya Roy Chowdhury, Aakrati Jain, Mukta Farooq

Co-Designing Analog AI System and Accelerator for Large Foundation Models

Liu Liu, Meng Wang 

Sidney Tsai, Kaoutar El Maghraoui

Control of orientation and handedness of nanoscale topological interconnect conductors on amorphous SiO2

Jian Shi, Ravishankar Sundar

Ching-tzu Chen

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

E-beam glancing angle scattering for hybrid bonding surface planarity measurement

Gwo-Ching Wang, Toh-Ming Lu

Nicholas Polomoff, Katsuyuki Sakuma

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

Foundational Models for Understanding Tabular Data Through AI Automation

Jianxi Gao

Kavitha Srinivas, Tejsawini Pedapati, Horst Samulowitz, Pin-Yu Chen

High resolution x-ray imaging for 3D-HI chiplet non-destructive internal metal joints inspection

Edwin Fohtung, James Lu

Roy Lu, Katsuyuki Sakuma

Holistic Algorithm-Architecture Co-Design of Approximate Computing for Scalable Foundation Models

Tong Zhang, Liu Liu

Swagath Venkataramani, Sanchari Sen

Intermetallic compounds for high-conductivity interconnects

Daniel Gall

Artharv Jog, Ching-tzu 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

Testing LLM Safety via Causal Reasoning

Ali Tajer

Prasanna Sattigeri, Dennis Wei, Dmitrity Katz-Rogozhnikov

Theoretical and Algorithmic Foundations of In-Context Learning Using Properly Trained Transformer Models

Meng Wang

Songtao Lu, Pin-Yu Chen

Unlearning: Dynamics of Membership Privacy and Inference Attacks Against Large Language Models

Lei Yu

Magdon Ismail, Nathalie Baracaldo, Ling Cai

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

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