Research Projects
Our lab engages in transdisciplinary research spanning foundational AI modeling, advanced cyber-infrastructure research, and scientific applications.
Active Research Projects
Cyber-infrastructure Active (2026–2028)
Category III: Planning for a National Scale Data Platform for Personal Data
Data fuels AI models. The national data CI ecosystem lacks a robust solution for working with personal (sensitive data). We are designing an innovative data platform that can support access to personal data to address this critical shortcoming.
Sponsor: National Science Foundation (NSF AWD 2609498) • OASIS Team: Namit Juneja, Varun Chandola (PI) • Collaborators: Prof. Sharon Hewner, Prof. Kenny Joseph, Dr. Daniel Smith, Dr. Erica Smith, Dr. Matt Jones, Dr. Joe Grupp
Quantum Ramanomics Active (2025–2027)
Integrating AI with Ramanomics and Quantum Science for Live Cell Biochemical Mapping
Raman spectrometry is a powerful technology enabling the mapping of biochemical environments in living cells without external labeling agents. This project develops advanced machine learning and quantum science models to interpret complex Raman spectral signatures for non-invasive cellular diagnosis and molecular medicine.
Sponsor: University at Buffalo • OASIS Team: Tanvi Ranga, Dr. Davoud Adinehloo, Varun Chandola (PI) • Collaborators: Prof. Nalini Ratha, Prof. Paras Prasad, Prof. Vasili Perebeinos
Digital Twins & UQ Active (2025–2028)
FDT-BioTech: Uncertainty Quantification in Deep Learning-Driven Digital Twins for Type 1 Diabetes
This project develops new mathematical foundations and computational algorithms to enable rigorous uncertainty quantification in deep learning-driven digital twins. It addresses critical challenges in risk-averse, real-time closed-loop decision making for autonomous Type 1 Diabetes management systems.
Sponsor: National Science Foundation (NSF AWD 2533946) • OASIS Team: Namit Juneja, Varun Chandola (co-PI) • Collaborators: Prof. Danial Faghihi (PI), Prof. Bruce Pitman, Prof. Tarun Raj Singh, Dr. Nikolay Simakov, Dr. Lucy Mastandrea
Healthcare Analytics Active (2021–2026)
Implementing Personalized Cross-Sector Transitional Care Management via Health Information Exchange
High-need, high-cost (HNHC) patients with multiple chronic conditions require coordinated, cross-sector transitional care. This project improves health information exchange (HIE) capabilities by using machine learning to segment patient populations, automate alerts, and facilitate cross-sector care planning across community, clinical, and behavioral health systems.
Sponsor: Agency for Healthcare Research and Quality (AHRQ) • OASIS Team: Yanbo Guo, Saumya Pandey, Varun Chandola (co-PI) • Collaborators: Prof. Sharon Hewner (PI), Prof. Ekaterina Noyes, Prof. Suzanne Sullivan, Prof. Guan Yu, Prof. Elizabeth Bowen
Previous Research Projects
Exascale Simulations 2020–2025
CHREST: Center for Hybrid Rocket Exascale Simulation Technology
CHREST brings together multidisciplinary teams across exascale computing, combustion modeling, materials science, and machine learning to enable high-fidelity predictive modeling of solid/hybrid propellant rocket motors on upcoming exascale supercomputing architectures.
Sponsor: Department of Energy (DOE) / NNSA (PSAAP III) • OASIS Team: Dwyer Deighan, Amol Salunkhe, Varun Chandola (co-PI) • Collaborators: Prof. Paul Desjardin (PI), Prof. Matt Swihart, Prof. James Chen, Prof. Matt Knepley, Dr. Matt Jones, Prof. Abani Patra
Ethical AI 2020–2022
Building Fair Recommender Systems for Foster Care Services in Sociotechnical Systems
Investigating fairness, bias, and algorithmic transparency when machine learning algorithms assist social workers in recommending support services and interventions for youth navigating the child welfare and foster care ecosystem.
Sponsor: National Science Foundation (NSF AWD 1939579) & Amazon Science • OASIS Team: Pranav Sankhe, Varun Chandola (co-PI) • Collaborators: Prof. Kenny Joseph (PI), Prof. Atri Rudra, Prof. Winnie Chen, Prof. Melanie Sage
Biomedical Time Series 2019–2020
Beyond Compartment Models: Big-Data Analytics for Artificial Pancreas Controller Design
Developing continuous glucose predictive modeling and controller algorithms that combine physiological compartment mechanics with big data learning to deliver automated insulin delivery for Type 1 diabetes patients.
Sponsor: Juvenile Diabetes Research Foundation (JDRF) • OASIS Team: Arshad Zaidi, Muhanned Ibrahim, Varun Chandola (co-PI) • Collaborators: Prof. Tarun Raj Singh (PI), Dr. Lucy Mastandrea
Scalable ML & Materials 2019–2022
MEADS: Manifolds for Extreme-scale Applied Data Science
Scalable non-linear manifold learning algorithms tailored for extreme-scale scientific datasets generated by dynamical simulations in material science, organics manufacturing, and fluid flow.
Sponsor: National Science Foundation (NSF OAC 1910539) • OASIS Team: Namit Juneja, Varun Chandola (PI) • Collaborators: Prof. Jaroslaw Zola, Prof. Olga Wodo
Cybersecurity 2014–2018
Data is Social: Exploiting Data Relationships to Detect Insider Attacks
Modeling user query intent, SQL query provenance, and database access logs using graph-based and probabilistic anomaly detection to identify malicious insider behavior and database compromises.
Sponsor: National Science Foundation (NSF Grant No. 1409551) • OASIS Team: Dr. Duc Thanh Anh Luong, Varun Chandola (co-PI) • Collaborators: Prof. Shambhu Upadhyaya, Prof. Oliver Kennedy, Prof. Long Nguyen, Gokhan Kul, Ting Xie