About
Engineer by training, problem-solver by instinct.
I build intelligent systems for complex, real-world decisions. I care as much about how a solution works in practice as how it performs in an experiment.
“The formulation of a problem is often more essential than its solution.”
How I approach the work
My background in industrial and systems engineering shapes the way I approach artificial intelligence. Before selecting a model, I ask what decision the system should improve, what constraints matter, how success should be measured, and what people need in order to trust and use the result.
I enjoy taking projects from an initially open-ended problem to a well-defined and usable outcome. That process may involve designing the data strategy, developing algorithms, organizing experiments, validating results, building a software prototype, and communicating the final system to technical and nontechnical collaborators.
The most rewarding work for me happens where analytical depth and practical implementation meet: turning a difficult scientific or engineering question into something measurable, reproducible, and useful.
Core strengths
Machine learning and computer vision
Designing and evaluating learning systems for classification, detection, visual measurement, and decision support.
Optimization and decision modeling
Translating operational requirements, uncertainty, and domain constraints into structured analytical objectives.
End-to-end system development
Connecting data, models, software, sensors, dashboards, and deployment-oriented prototypes into complete working systems.
Technical leadership and collaboration
Organizing interdisciplinary work, mentoring developing researchers, and communicating technical decisions clearly.
Education
Ph.D. in Industrial and Systems Engineering
Mississippi State UniversityAnticipated May 2027
M.S. in Industrial Engineering
Iran University of Science and Technology
B.S. in Industrial Engineering
Garmsar University
Professional interests
I am especially interested in problems where a technically strong model must also remain reliable, interpretable, and useful under real operating conditions.
- Extracting meaningful measurements and decisions from visual data
- Learning effectively from limited, heterogeneous, or imperfect data
- Incorporating evidence, constraints, and domain knowledge into AI
- Connecting predictive models with optimization and decision processes
- Moving analytical ideas into reproducible software and usable systems
Teaching and mentoring
I view teaching and mentoring as extensions of professional leadership. My goal is to help students move beyond following instructions and become confident in framing problems, defending technical choices, and communicating their work.
Graduate mentoring
Co-mentored graduate researchers on machine learning, computer vision, experimental design, and scholarly communication, with collaborations leading to peer-reviewed publications.
Undergraduate mentoring
Mentored five undergraduate researchers in the 2026 USDA Research and Extension Experiences for Undergraduates program.
Instruction
Delivered instruction in deep learning with PyTorch, technical writing with LaTeX and Overleaf, financial engineering, and financial risk management.
Leadership and professional service
Professional leadership
President of the Mississippi State University INFORMS Student Chapter for 2026–2027, following service as Vice President.View leadership announcement.
Community leadership
Vice President of the Iranian Student Association at Mississippi State University, following service as President during the 2024–2025 academic year.View verification.
Peer review
Reviewer for journals and conferences spanning artificial intelligence, optimization, manufacturing, sustainability, and engineering applications.
Conference leadership
Session Chair
Emerging Methods in Vision-Based Decision Support
2025 IISE Annual Conference & Expo
Session Chair
Advanced AI Solutions in Health and Diagnostics
2025 IISE Annual Conference & Expo
Selected recognition
Finalist, IISE DAIS Student Data Challenge, Wood-Chip Monitor
Third Place, IISE DAIS Data Analytics Competition
Third Place, Mississippi State University AI Club Campus Vision Challenge
Let's connect
I welcome conversations about applied AI, optimization, research collaboration, and opportunities to build useful intelligent systems.