Texas A&M University
fahimehorvatinia@tamu.edu | GitHub | LinkedIn | Google Scholar | CV (PDF)
I’m a PhD student in Computer Engineering at Texas A&M University, advised by Dr. Joshua Peeples. My research focuses on computer vision, machine learning, and their applications in agricultural imaging and human behavior modeling. I earned my Master’s degree in Electrical Engineering from the University of Notre Dame in 2025 and my Bachelor’s degree in Electrical Engineering from Amirkabir University of Technology in 2020.
Traffic-aware pedestrian intention prediction
Fahimeh Orvati Nia, Hai Lin
American Control Conference (ACC), 2025
arXiv:2507.12433
Neighborhood Feature Pooling for Remote Sensing Image Classification
Fahimeh Orvati Nia, Joshua Peeples, et al.
WACV 2026 Workshop on Earth Observation
arXiv:2510.25077
Evaluating GAN-LSTM for Smart Meter Anomaly Detection in Power Systems
Fahimeh Orvati Nia, S. Salehi, J. Peeples
TPEC 2026
arXiv:2601.09701
Integrating Multispectral Imaging and Low-Field Magnetic Resonance Imaging for Comprehensive Phenotyping of Horticultural Crops
A. McFarland, L. Rossi, F. Nia, J. Peeples, A. Svyanek
HORTSCIENCE 60 (7), 2025
Research Assistant
Texas A&M AgriLife Research
Jan 2025, Present
Teaching Assistant
University of Notre Dame
Fall 2023, Spring 2024
Courses: Introduction to Electrical Engineering, Signals and Systems
Peer Reviewer
LXAI-NeurIPS 2025, IEEE RA-L, ICRA 2026, ACC 2025, CCTA 2025
Chloe Tiley, Sophia Martinez-Badiillo, Michael Morse, Amran Kassaye, Nazar Oladepo