Post Doctoral RuCCS Laboratory Affiliates
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Theodoros Bermperidis
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Theo is an Electrical Engineer with a strong mathematical training interested in advancing methods of machine learning and AI for smart health and applications to sports and the performing arts. He has completed his MSci in Psychology and developed several analytical models to automatically classify complex behaviors and distinguish different phenotypes. More recently, Theo has developed new methods of analyses to interrogate the transcriptome in humans and mice models.
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Mona Elsayed
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Mona is a doctorate student under Dr. Torres supervision. Mona received her B.S. in Biology with a minor in Psychology at the College of New Jersey. She has completed her MSci in Psychology, and is currently finishing up her PhD in Psychology. In addition to her rigorous science, Mona is an excellent teacher. She has significantly contributed to the development of the Rutgers Autism Certification to be launched in the Fall of 2023 and offered through the Rutgers Continuing Education Program.
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Amritpal Singh
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Amrit received his PhD in Developmental Psychology at Cornell University in 2024. He completed his BA in a Great Books Program at St. John’s College. His research focuses on the contextual and developmental forces that shape how abstractly we think and how we reason about abstract entities. His dissertation work investigated differences in abstract thought across and within cultures, operationalizing abstract thought in different ways (i.e., event cognition and analogical reasoning). In the Quad Lab, he studies how context and time may shape the way we think about quantitative information, such as proportions and probabilities.
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Samuel Sohn
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Sam received his PhD in Computer Science at Rutgers University in 2024. His doctoral studies centered around simulating and predicting human navigation in built environments at both the individual level and the crowd level with thousands of agents. This body of work carefully grounded its models in spatial cognition and leveraged machine learning techniques to eliminate a long-standing computational barrier to simulating at scale. His focus now is on investigating behavioral nuances that manifest in navigation and speech among individuals with diverse physical and neurocognitive abilities.
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