About me

I am a Carmine and Jean Iannacone Postdoctoral Fellow working with Dr. Kamran Paynabar in the School of Industrial and Systems Engineering (ISyE) at Georgia Institute of Technology. I earned my Ph.D. in Industrial & Systems Engineering at the University of Florida under the supervision of Dr. Mostafa Reisi Gahrooei.

My research lies at the intersection of machine learning, data science, and data-driven decision-making, with a focus on developing interpretable, robust, and privacy-preserving methods for analyzing high-dimensional and multimodal data. A central theme of my work is transforming diverse and irregular data streams into trustworthy insights that support organizational and societal decision-making. I develop tensor-based and federated frameworks for personalized and privacy-preserving modeling, as well as multimodal data fusion techniques for human-centered AI systems. More broadly, I aim to design human-centered and trustworthy analytics that bridge methodological rigor with real-world impact across healthcare, transportation, energy, and immersive technologies.

Key areas of my research include:

• Multimodal Data Fusion for Human-Centered AI and AR/VR Systems – integrating gaze, head, hand, and physiological signals to model expertise, workload, and behavioral dynamics.
• Computational Phenotyping and Risk Prediction from EHR – tensor-based models for interpretable patient phenotypes and outcome prediction from irregular and partially labeled data.
• Privacy-Preserving and Federated Analytics for Healthcare and Complex Systems – frameworks enabling cross-institutional collaboration without sharing raw data, with applications in healthcare, agriculture, and manufacturing.
• Personalized Modeling in Telemonitoring and Neuroimaging – multi-task tensor learning for individualized predictions in Parkinson’s severity monitoring and ADHD characterization.
• Forecasting and Decision Support in Energy and Transportation – adaptive methods for renewable energy forecasting and resilience-focused monitoring of transportation networks.

I am always open to collaborative opportunities that push these areas forward and welcome interdisciplinary projects with societal impact. Please feel free to contact me if you are interested in working together.

Outside of work, I enjoy biking, running and hiking, and I am a big coffee enthusiast.

Education

• Ph.D. in Industrial & Systems Engineering, University of Florida, 2024

• M.S. in Industrial Engineering, Boğaziçi University, 2021

• B.S. in Industrial Engineering, Boğaziçi University, 2018

News

• May 2025: Received the ENBIS Knowledge Fund to attend the ENBIS-25 Conference in Piraeus, Greece. I will present “Data-Driven Personalization in Telemonitoring and Neuroimaging for Diverse Populations.”
• December 2024: Successfully defended my dissertation and earned my Ph.D. in Industrial & Systems Engineering from the University of Florida.
• April 2024: Awarded the UF Industrial & Systems Engineering Graduate Research Award.
• April 2024: Received an NSF Student Travel Award for the Joint Research Conference (JRC 2024) at the University of Waterloo, Canada. Presented poster “Semi-supervised PARAFAC2 Decomposition for Medical Decision Making.”
• May 2023: Federated Generalized Scalar-on-Tensor Regression was nominated as a finalist for the Best Paper Competition at the INFORMS ICQSR Conference in Raleigh, NC.
• April 2023: Federated Generalized Scalar-on-Tensor Regression was selected as a finalist in the IISE QCRE Best Student Paper Competition. Presented at the IISE Annual Meeting in New Orleans, LA.
• March 2023: Selected to attend the FutureBAProf Workshop at the Tippie College of Business, University of Iowa, with travel support.
• June 2022: Received NSF Travel and Registration Award for the Quality and Productivity Research Conference (QPRC 2022).
• June 2021: Defended my Master’s thesis at Boğaziçi University, Istanbul.
• January 2021: Ranked in the top 10 out of 247 participants in the “Wind Power Forecasting for the Day-Ahead Energy Market” challenge organized by Compagnie Nationale du Rhône (CNR).