Postdoctoral Research Scholar at the Center for Digital Cardiovascular Innovations, a multidisciplinary clinical and research hub within the University of Miami Miller School of Medicine / UHealth System, directed by Dr. Yiannis S. Chatzizisis (Chief, Division of Cardiovascular Medicine).

• Advancing heart care through artificial intelligence and computational modeling.
• Extending generative and explainable deep learning to cardiovascular imaging, modeling, and clinical decision support.

Office of Naval Research (ONR) Project: Graduate Researcher on maritime autonomy (2021–25), developing early intent recognition and threat-aware decision support in naval contexts. On-water Deployment Collaborator with Huntington Ingalls Industries on autonomous naval systems.

• Developing ML models for real-time prediction of vessel behavior under sparse, noisy, and adversarial conditions.
• Collaborating on simulation-driven experimentation, dataset design, and integration of ML/DL models into maritime situational awareness frameworks.
• Contributed to a pending collaborative external grant proposal (ONR and ONR Global) with my PI, drafting technical sections on temporal intent modeling and evaluation.

Assisted instruction in CS 477/677: Analysis of Algorithms, CS 422/622: Introduction to Machine Learning, and CS 491/691: LLMs and Multimodal AI, supporting student learning in algorithmic reasoning and applied ML.

• Led review sessions and held weekly office hours for conceptual guidance, problem-solving support, and individualized clarification.
• Designed and graded homework, exams, and programming tasks, delivering constructive feedback.

Responsibilities include:

• Building ICONIQ (AI-driven experience recommendations) and AIJINTSEE (marketing automation) with FastAPI, PostgreSQL/pgvector, and integrated LLM/DL pipelines.
• Leading and mentoring a 4-student team (2 M.S., 2 B.S.) on architecture, coding standards, and experiment design.
• Standing up ML orchestration, data flows, and inference endpoints for productionization.

Undergraduate courses: CSE 111 (Structured Programming), CSE 121 (Digital Logic Design), CSE 211 (Data Structures), CSE 311 (Artificial Intelligence & Neural Networks), CSE 313 (Database Systems), CSE 321 (Object-Oriented Analysis and Design), and CSE 411 (Software Engineering).

• Designed lecture materials, assignments, quizzes, and examinations aligned with learning outcomes.
• Supervised project-based learning activities focusing on design patterns, testing, and documentation.
• Served as Course Coordinator, contributing to course scheduling and curriculum alignment.

Defended May 7, 2026; degree awarded May 2026. Dissertation on Deep Generative and Explainable Learning Frameworks for Intent Recognition in Naval Domain, advised by Prof. Monica Nicolescu and co-advised by Prof. Mircea Nicolescu. The work contributes the NavySim multi-agent maritime simulator, CPFI/TFIS explainable feature attribution, deep intent-classification models, classical Bayesian (Kalman) trajectory baselines, and MTITP—a multi-task GAN for joint intent recognition, future-intent prediction, and intent-conditioned trajectory generation. Presented 2 papers at IEEE CASE, with additional publications across IEEE CoG, IEEE Transactions on Games, and other venues.

Courses included:

• Autonomous Mobile Manipulation
• Robotics for Humaity
• Stochastic Deep Learning

Thesis on Threatmap: A Framework for Enhancing Security Awareness and Decision-Making for Naval Agents. Supervised by Prof. Monica Nicolescu and cosupervised by Prof. Mircea Nicolescu. Presented 1 papers at IEEE Conference on Games, 1 Simulation Conference and published at 3 other conferences/journals.

Courses included:

• Introduction to Machine Learning
• Fundamentals of Deep Learning
• Mass Detection in Mammograms
• Advanced Bioinformatics