Biography
Somayeh Keshavarz is an Assistant Teaching Professor in the Department of Electrical and Computer Engineering at Drexel University's College of Engineering. She joined the
department in 2023, bringing with her a wealth of experience in both
academia and industry. Keshavarz’s research interests focus on the
development and application of machine learning techniques to solve
real-world problems, particularly in the fields of computer vision, image
processing, and medical imaging.
She is currently a PhD candidate in Computer and Information Science at
Temple University, where her dissertation focused on “Discretization
without Labels: Learning from Features.” Her academic journey also includes
an MS in Computer Science from the University of Central Florida and an MS
in Electrical Engineering from Shahrood University of Technology.
Keshavarz has taught various undergraduate and graduate courses, including
Machine Learning, Computer Vision, Data Science, and Digital Systems. Her
passion for teaching is evident through her innovative course design and
commitment to student success.
Degrees / Education
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PhD candidate, Computer and Information Science, Temple
University, Philadelphia, PA, USA (Expected 2024)
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MS, Computer Science, University of Central Florida, Orlando, FL,
USA (2016)
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MS, Electrical Engineering, Shahrood University of Technology,
Semnan, Iran (2009)
Research Interests
Machine Learning and Artificial Intelligence, Computer Vision and Image Processing, Explainable AI and Interpretable Models, Medical Imaging Applications, Video Analysis and Surveillance
Areas of Study
Select Publications
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Keshavarz, S., Brachman, M., Stylianou, A., Souvenir, R.
(IJHCS, Under review).
Evaluating Image Labeling Paradigms for Mobile Crowdsourcing
Applications
- Black, S., Keshavarz, S., Souvenir, R. (2021, IJCV).
Evaluation of Inpainting and Augmentation for CensoredImage
- Black, S., Keshavarz, S., Souvenir, R. (2020, WACV).
Evaluation of Image Inpainting for Classification and Retrieval
- Keshavarz, S., Tran, Q. Souvenir, R. (2020, ICPR).
Learning Natural Thresholds for Image Ranking.
- Keshavarz, S., Saleemi, I. Atia, G. (2017, ICIP).
Exploiting probabilistic Relationships Between Action Complex Event
Classification.