People
Faculty
Dr. Yousefi specializes in neuroscience data analysis, with a focus on developing statistical frameworks to connect neural activity with biological and behavioral signals. His research integrates methods in statistical inference, signal processing, Bayesian analysis, and stochastic estimation to model neural system dynamics. These methodologies are applied to neural data, such as spike trains and local field potentials, to dynamically characterize and replicate neural activity in real time.
Education:
- B.S. in Electrical Engineering, Iran University of Science and Technology, 1998
- M.S. in Electrical Engineering, Sharif University of Technology, 2000
- Ph.D. in Electrical Engineering, University of Southern California, 2014
- Postdoctoral Fellow, Department of Psychiatry, Harvard Medical School, 2019
- Research Scientist, Department of Mathematics and Statistics, Boston University, 2019
PhD Students
Pedram Rajaei is a Ph.D. student in Biomedical Engineering since 2024. He got his master’s degree from Sharif University of Technology. His research focuses on developing tools and theories for analyzing neuroscience data, with applications in brain-computer interfaces and clinical neuroscience. He integrate machine learning, statistical modeling, computational neuroscience, and cloud-based computing to create these tools.
Yasaman Anbari is a PhD student in Biomedical Engineering. She earned her master’s degree in medical imaging from UTU. Her research interests focus on improving the quantification of radionuclide biodistribution and enhancing workflows for image-guided treatments.
Amer Ziouziou is a Ph.D. student in Biomedical Engineering at the University of Houston. He holds an M.S. degree in Electromechanical Engineering from École Nationale Supérieure d’Arts et Métiers. His research focuses on brain–computer interfaces and neurotechnology, particularly the development of wearable systems and computational methods for analyzing electroencephalogram data. His work integrates embedded hardware, signal processing, and machine learning algorithms. His goal is to advance wearable neurotechnology to improve cognitive function.
Shahab Tavasoli is a PhD student in Biomedical Engineering. He earned his master’s degree in Mechanical Engineering from Sharif University of Technology. He develops machine learning based frameworks and control strategies within neurostimulation systems to regulate mood. His research interests include signal processing, statistical modeling, and control engineering.
Jointly Supervised PhD Students
Maryam Ostadsharif Memar is a Ph.D. student in Electrical Engineering at Isfahan University of Technology (IUT), Iran. She also earned both her Bachelor’s and Master’s degrees in Electrical Engineering from IUT. Her research interests lie at the intersection of computational neuroscience and machine learning techniques, aiming to enhance the understanding of neural processes. Her expertise includes digital signal processing, particularly in analyzing brain signals and developing brain decoding algorithms to improve neural computation and achieve significant advancements in computational neuroscience.
Navid Ziaei is a Ph.D. candidate in Electrical Engineering, specializing in Communication Systems, at Isfahan University of Technology (IUT), where he also earned both his Bachelor’s and Master’s degrees in Electrical Engineering. He has also been a visiting researcher at Worcester Polytechnic Institute (WPI), where he contributed to research on neural data and computational neuroscience. His work focuses on Deep Learning and Statistical Machine Learning with applications in computational neuroscience, image and signal processing, healthcare, and Natural Language Processing (NLP) blending theory with impactful interdisciplinary applications.
Master’s Students
Kallam Pavan Teja Reddy, Master of Science in Data Science Engineering
Karthik Nunna, Master of Science in Data Science Engineering
Former Students and Lab Members
Maceo Richards, MSc, currently a post-baccalaureate scholar at the Harvard University Kempner Institute
Yalda Amidi, PhD, is currently a Machine Learning Engineer at Arbor Biotechnology and a postdoctoral trainee at Harvard Medical School