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Ph.D., Biomedical and Health Informatics

University of Wisconsin–Milwaukee, Milwaukee, WI

• Dissertation: Medical modeling, simulation, and AI for clinical decision support
• Focus: Agent-based models, discrete-event simulation, transformer-based disease trajectory modeling, LLMs in medicine, and explainable AI for healthcare
• GPA: 3.8/4.0

M.S., Computer Science

University of Wisconsin–Milwaukee, Milwaukee, WI

• Thesis: Medical Image Segmentation Using Machine Learning (deep learning for wound image segmentation)
• GPA: 3.7/4.0

B.S., Software Engineering

Tehran Azad University, Tehran, Iran

• Thesis: Fall Detection in the Elderly Using Smartphones via Machine Learning Techniques
• GPA: 3.5/4.0

Engineer I

Medical College of Wisconsin — ReyLab (Neurosurgery Research), Milwaukee, WI

• Investigate mechanisms of human episodic memory formation and retrieval by developing data acquisition systems that integrate multiscale neural recordings (MRI, intracranial EEG, microwire single-unit/LFP) with cognitive task paradigms in epilepsy patients
• Advance epilepsy diagnosis and treatment through engineering of real-time analysis pipelines for seizure onset zone localization, leveraging single-neuron firing patterns and local field potential biomarkers
• Lead development of MCWs (MiCroWire sorter), a modular, open-source spike sorting framework engineered for human intracerebral recordings in clinical settings (first co-author, bioRxiv preprint)
• Build reproducible computational infrastructure for large-scale neural data analysis (40-core systems, 250TB storage), implementing automated quality control, artifact rejection, and feature extraction workflows

Research Assistant

University of Wisconsin–Milwaukee — Biomedical Data and Language Processing Lab, Milwaukee, WI

• Develop AI-driven clinical decision support systems for NIH-funded research, integrating agent-based modeling, discrete-event simulation, and machine learning to evaluate population health interventions
• Build LLM-based agentic systems for clinical applications using transformer architectures, synthetic data generation, RAG, and prompt engineering
• Design explainable AI frameworks combining SHAP analysis, attention mechanisms, and natural language generation to translate complex temporal prediction models into clinically interpretable risk pathways
• Engineer scalable data processing infrastructure for large-scale health datasets (7M+ patients) using distributed computing frameworks
• Collaborate across clinical specialties (otolaryngology, cardiology, gastroenterology, neurosurgery, geriatrics), contributing to 20+ publications

Data Scientist Intern

Medical College of Wisconsin — Clinical and Translational Science Institute, Milwaukee, WI

• Reimplemented WaveClus3 spike-sorting algorithm from MATLAB to Python, optimizing computational efficiency for large-scale human intracranial recordings from epilepsy patients
• Designed novel artifact rejection methods to improve single-neuron detection in hospital-based electrophysiology environments

Project Assistant

University of Wisconsin–Milwaukee — Northwestern Mutual Data Science Institute, Milwaukee, WI

• Conducted data-driven program evaluation studies analyzing enrollment patterns, learning outcomes, and engagement metrics for interdisciplinary data science curricula
• Built open-source educational framework with 50+ reproducible data science examples demonstrating real-world applications of statistical modeling and machine learning

Lecturer

University of Wisconsin–Milwaukee — College of Health Sciences, Milwaukee, WI

• Big Data & Healthcare Informatics (Graduate): Designed and delivered comprehensive curriculum covering distributed computing frameworks (Apache Spark), machine learning for large-scale health data, deep learning architectures, and production AI systems for 60+ graduate students
• Introduction to Healthcare Informatics (Graduate): Taught foundational course spanning health IT ecosystems, stakeholder analysis, clinical decision support systems, medical image processing, AI/ML in healthcare, data standards (HL7, FHIR), and translational informatics

Teaching Assistant

University of Wisconsin–Milwaukee — Big Data & Healthcare Informatics, Milwaukee, WI

• Led lab sessions on applied healthcare data science, teaching graduate students to implement ML pipelines, develop simulation models, and analyze EHRs using Python-based frameworks
• Contributed to curriculum development by designing assignments, creating coding tutorials, and developing assessment rubrics

Research Mentorship

University of Wisconsin–Milwaukee

• Mentored 10+ undergraduate and graduate students on research projects involving medical modeling, machine learning, and clinical data analysis
• Supervised 5+ students through completion of thesis projects

• NIH-funded Research (Team Member): Advancing Healthier Wisconsin Endowment — AI-driven clinical decision support systems for otolaryngology and geriatric care
• CTSI Pilot-BERD Methodological Innovation — Advanced explainable AI methodologies for clinical prediction models

• NMDSI Student Scholars Award — $7,500 (Northwestern Mutual Data Science Institute). Funded LLM-based clinical applications research

• Chancellor's Graduate Student Award — $2,500 (Apr. 2024)
• Chancellor's Graduate Student Award — (Fall 2024)
• Graduate Student Travel Award — $1,500 (May 2024). Conference presentations on pancreatic cancer mortality
• Best Reviewer Award — AMIA Informatics Summit, 2024

• Chancellor's Graduate Student Award — $6,000 (Jan. 2020)