People | pinotsislab

Dimitris Pinotsis, PhD (PI)

Dimitris is an Associate Professor (Reader) at the Department of Psychology and Neuroscience at City St George's, University of London and head of the computational neuroscience and psychiatry lab (www.pinotsislab.com). He is also the Editor-in-Chief of the Journal of Computational Neuroscience published by Springer Nature and a Research Affiliate at MIT’s Miller Lab. A theoretical neuroscientist with a PhD in Mathematics and an MSc in Theoretical Physics from the University of Cambridge in England where he worked with Thanasis Fokas, Dimitris published more than fifteen papers in mathematics and physics journals and then decided to pursue a career in neuroscience, his true passion. Dimitris then worked with Peter Grindrod on mathrematical neuroscience and spent six and a half years at University College London (UCL) working with Karl Friston on theoretical neuroscience and data analysis. He continued at the Massachusetts Institute of Technology (MIT), where he worked with Earl Mille r on using predictive coding and deep neural networks to address fundamental questions in cognitive neuroscience. In 2018, he joined the Center for Mathematical Neuroscience and Psychology at City St George's—University of London as an Assistant Professor (Lecturer).

Dimitris' research has been funded by the NIH, US Air Force Office of Scientific Research, UK Research Councils (EPSRC, ESRC, Innovate UK) and several UK charities. It spans diverse areas including machine learning, the analysis of big data in neuroimaging, theoretical neurobiology and nonlinear systems in mathematical physics. Dimitris has received over 10 Fellowships from Cambridge Isaac Newton Trust, Onassis Foundation, NATO, Bernstein Organization and others. He is also the recipient of several awards including an OCNS Award, a Smith-Rayleigh Prize of the University of Cambridge and a Poincare Institute Award.

Principal Investigator

Namrata Nagendra

Namrata has a BSc. (Hons.) degree in Marketing & Psychology and has previously worked in a Social-Cognitive Psychology lab working on Actions, Motivated behaviours and social contagion utilising mixed methods. She spent a year working at tech-startup Scapic working with XR technologies across various industries. Her research interests include neuroeconomics, the psychophysics of decision making and the biological basis of consumer choice; which she explores through utilisation of new technologies such as VR, AR, Motion tracking and neuroimaging. In her PhD, Namrata is exploring the effects of marketing stimuli on underlying neural correlates in consumer behaviour and decisions in digital environments with a curiosity to model these effects using computational neuroscience.

PhD Student

Sandeep Hugar

Sandeep holds a BTech in Data Science & Artificial Intelligence from the International Institute of Information Technology, Naya Raipur, India. He is pursuing an MSc in Behavioural Economics at City St George's, University of London. His research focuses on developing a novel EEG-based scale for decoding preference in the human brain towards various visual stimuli, such as 2D objects, 3D objects, and VR exposure. Prior to this, he worked in the fintech industry in Southeast Asia for 3 years as an Associate Product Manager. He is interested in the intersection of Machine Learning and Neuroscience. He is working on methods where ML methods can be used to understand and predict patterns from neural data.

MSc Student

Senior Lab Alumni

Sean Fitzgerald, PhD

Sean is a tech start-up veteran and data scientist who holds a PhD from Nanyang Technological University in Singapore. His doctoral research with George Christopoulos focused on understanding decisions made for other individuals (allocentric decisions), in particular the neural mechanisms underpinning the vicarious valuation of human effort. After submitting his thesis, Sean co-founded GolfLine, Inc., a tech firm that used machine learning to evaluate golfers’ offers for tee times. He served as the Director of Data Analytics for GolfLine and developed the key intellectual property and proprietary deep-learning neural networks responsible for the real-time bid classification. Sean's aim is to synthesize best practices from his industry and academic experiences to better understand human behavior, cognition, and neural functioning. When Sean is not staring into the abyss of stack overflow tabs on his computer, he is at the nearest sand or beach volleyball court trying to deliver a perfect hand set.

Former Post Doctoral Research Associate ; Now Research Lead for London based start-up

Darshan Gohil

Darshan holds a Master's degree in Computational Neuroscience and Cognitive Robotics from the University of Birmingham and a Bachelor's degree in Engineering from Mubai University. He currently works on implementing computational models to enhance understanding of addiction. Darshan's primary research interests lie in computational neuroscience, with a focus on mapping the neural architecture and circuitry of the brain using Brain-Computer Interface (BCI) technologies. His work aims to bridge the gap between complex neural data and practical applications in neuroscience.

Former Research Assistant; Now Research Assistant at University of Oxford

Darshan Gohil

Darshan holds a Master's degree in Computational Neuroscience and Cognitive Robotics from the University of Birmingham and a Bachelor's degree in Engineering from Mubai University. He currently works on implementing computational models to enhance understanding of addiction. Darshan's primary research interests lie in computational neuroscience, with a focus on mapping the neural architecture and circuitry of the brain using Brain-Computer Interface (BCI) technologies. His work aims to bridge the gap between complex neural data and practical applications in neuroscience.

Research Assistant

Darshan Gohil

Darshan holds a Master's degree in Computational Neuroscience and Cognitive Robotics from the University of Birmingham and a Bachelor's degree in Engineering from Mubai University. He currently works on implementing computational models to enhance understanding of addiction. Darshan's primary research interests lie in computational neuroscience, with a focus on mapping the neural architecture and circuitry of the brain using Brain-Computer Interface (BCI) technologies. His work aims to bridge the gap between complex neural data and practical applications in neuroscience.

Research Assistant

Fintan Nagle, PhD

Fintan is a a cognitive scientist and software engineer with a background in computer science, vision science and machine learning. His doctoral work at UCL investigated temporal visual search in moving natural scenes. He has also worked on task-switching in automated driving, on visual complexity, and on knowledge networks. Fintan is interested in using machine learning to understand how the brain creates, samples from, and manipulates our environment.

Former Post Doctoral Research Associate; Now a Visiting Lecturer at City and Imperial

Melissa Reneaux, PhD

Melissa is a theoretical neuroscientist with a PhD degree in computational neuroscience from Jawaharlal Nehru University, India. She has a Bachelor’s and Master’s degree in Theoretical Physics from St. Stephen’s College, Delhi. During herdoctoral work with Prof. Karmeshu and Dr. A. Krishnamachari, she investigated the effect of dopamine in working memory maintenance in the prefrontal cortex using mean field models. After completing her doctoral work, she went on to work in the lab of Prof. Claudia Clopath at Imperial College London as a postdoctoral scholar, where she investigated the effect of inflammation in clinical depression.

Former Post Doctoral Research Associate ; Now Assistant Professor at University of Petroleum and Energy Studies (UPES) in Dehradun, India.

Julia Rodriguez Sanchez

Julia holds a PhD in Computational Neuroscience and an MSci in Neuroscience from University College London (UCL). During her doctoral research, supervised by Prof Rick Adams, Dr Daniel Hauke and Prof Karl Friston, she investigated excitatory (E) and inhibitory (I) circuit (dys)function in psychosis spectrum disorders using dynamic causal modelling (DCM) of M/EEG. In her current role, Julia is working on validating and refining computational biophysical models of EEG data allowing to infer E/I balance non-invasively. Ultimately, her research aims to inform treatment strategies and improve clinical outcomes for people with schizophrenia and other psychosis spectrum disorders.

Former Post Doctoral Research Associate; Now RA at UCL.