Specializing in developing advanced machine learning solutions for science and engineering with a focus on making AI practical and trustworthy for high-impact scientific applications.

• JLab PI: Towards Higher Brightness Beam for BNL with AI ($700K JLab)
• JLab PI: Hardware Aware Artificial Intelligence for HEP ($0.6M JLab / $2M total)
• JLab PI: Self-driving NP Scientific User Facilities ($700K JLab / $2M total)
• Team Lead / Co-PI: ML for SNS Accelerator Performance ($600K JLab / $2.2M total)
• Team Co-lead: Mathematics and Algorithm Development Group for Nuclear Femtography Inference at Exascale Platforms (2022-2024) - $6.5M DOE SciDAC funding.
• Project Lead: ML-assisted charged particle tracking with Graph Neural Networks (2023-Present)
• Mentor junior scientists, postdocs, and graduate students in machine learning development and research methodologies
• Lead cross-functional teams on developing and deploying ML solutions for accelerator optimization and control

• Supported well engineers’ team with production level solutions.
• Improved detection/visualization of over/under gauge in oil well drilling.
• Developed novel deep learning architecture to detect surface formation transitions using gamma ray signal logs.
• Developed Encryption Agent to improve user experience.

• Development of Data Driven Solutions for Oil Well Drilling Applications.
• Devised visual analytical framework for anomaly detection.
• Improved recommender system for individual forecasting.
• Developed probabilistic envelope-based visualization technique for time series data.
• Teaching Assistant in graduate level AI class.

• Reduced operating cost by automating daily tasks including timekeeping, notifications, grades, progress reports, leaves and payroll by creating an ERP system using SQL and Java.
• Improved follow-up process with students by creating analytical tools.
• Mentored freelance developers and interns.