Christoforos Christoforou

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  4. Christoforos Christoforou
Assistant ProfessorAssociate Professor
Computer Science, Mathematics and Science
The Lesley H. and William L. Collins College of Professional Studies
PhD, Computer Science , City University of New York - The Graduate CenterMPhil, Computer Science, City University of New York - The Graduate CenterMS, Computer Science, The City College of the City University of New York
Dr. Christoforou is an Associate Professor at the Division of Computer Science, Mathematics, and Sciences of St. John’s University in New York, USA. He also serves as the Program Director of the Master’s in Computer Science program at St. John’s University and leads the Neuro-Intelligence and Innovation Lab.

His research explores questions and problems at the intersection of computer science and neuroscience. His approach focuses on developing machine learning and AI algorithms to decode and extract information from electroencephalographic (EEG) and other neurophysiological signals and use those to design novel neurotechnology solutions and gain insights into the neurocognitive processes of the human brain during complex and dynamic tasks.

His research contributions include applications in a wide range of domain areas such as brain-computer interfaces, human-robot interaction, neuro-cinematics, and neuro-marketing, as well as the study of the neural underpinnings of reading disorders and other neurocognitive processes (i.e., spatial cognition, emotions) during complex paradigm design (i.e., dynamic video viewing).

Teaching Interests

Artificial Intelligence, Deep Neural Networks, Machine Learning, Software Development, Algorithms Design.

Research Interests

Artificial Intelligence, Deep Neural Networks, Machine Learning, Computational Neuroscience, Neuro-cinematics, Computational Biology, Computational Vision, Brain-computer Interfaces

Courses Taught

CUS
615
DATA MINING & PREDICT MODEL II
CUS
715
ALGORITHM & THEORY OF COMP
CUS
754
COMPUTER VISION & APPLICATIONS
CUS
1115
COMPUTER PROG FUND I
CUS
1116
COMPUTER PROG FUND II
CUS
1172
WEB APPLICATION DEVELOPMENT
CUS
1188
ANALYSIS OF ALGORITHMS

Select Publications

Journal Articles

Christoforou, C., Theodorou, M., Fella, A., and Papadopoulos, T. C. (2023). RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed. Frontiers in Psychology. vol. 14,

Christoforou, C., Theodorou,, ., Fella, A., and Papadopoulos, T. C. (2023). Phonological ability and neural congruency: Phonological loop or more?. Clinical Neurophysiology. vol. 156,

Christoforou, C., Ktisti, C., Richardson, U., and Papadopoulos, T. C. (2023). Microgenetic Analysis of Reading Remediation: A Novel Computational Framework. Advances in Cognitive Psychology. vol. 19,

Christoforou, C., Fella, A., Leppänen,, P. H., Georgiou,, G. K., and Papadopoulos, T. C. (2021). Fixation-related potentials in naming speed: A combined EEG and eye-tracking study on children with dyslexia. Clinical Neurophysiology. vol. 132,

Christoforou, C., Papadopoulos, T. C., Constantinidou, F., and Theodorou, M. (2017). Your brain on the movies: a computational approach for predicting box-office performance from viewer’s brain responses to movie trailers. Frontiers in neuroinformatics. vol. 11, pp. 72.

Christoforou, C., Christou-Champi, S., Constantinidou, F., and Theodorou, M. (2015). From the eyes and the heart: a novel eye-gaze metric that predicts video preferences of a large audience. Frontiers in psychology. vol. 6, pp. 579.

Sajda, P., Pohlmeyer, E., Wang, J., Parra, L. C., Christoforou, C., Dmochowski, J., Hanna, B., Bahlmann, C., Singh, M. K., and Chang, S. (2010). In a blink of an eye and a switch of a transistor: cortically coupled computer vision. Proceedings of the IEEE. vol. 98, pp. 462--478.

Parra, L. C., Christoforou, C., Gerson, A. C., Dyrholm, M., Luo, A., Wagner, M., Philiastides, M. G., and Sajda, P. (2008). Spatiotemporal linear decoding of brain state. IEEE Signal Processing Magazine. vol. 25, pp. 107--115.

Conference Proceedings

Christoforou, C., Papadopoulos, T. C., and Theodorou, M. (2023). Regularized Neural-Congruency on Spoonerism: Toward exploring the neural-underpinnings of reading disorders on phonological processing tasks. The International FLAIRS Conference Proceedings. vol. 36,

Christoforou, C., Papadopoulos, T. C., and Theodorou, M. (2022). Toward the study of the neural-underpinnings of dyslexia during final-phoneme elision: A machine learning approach. nternational Conference on Brain Informatics.

Christoforou, C., Papadopoulos, , T. C., and Theodorou, M. (2022). Machine learning approach for studying the neural underpinnings of dyslexia on a phonological awareness task.. Proceedings of the 35th International FLAIRS Conference.

Christoforou, C., and Theodorou, M. (2021). Towards EEG-based Emotion Recognition During Video Viewing: Neural-Congruency Explains User’s Emotion experienced in Music Videos. Proceedings of the 34th International FLAIRS Conference .

Christoforou, C., Papadopoulos, T. C., and Theodorou, M. (2021). Single-trial FRPs: A machine learning approach towards the study of the neural underpinning of reading disorders. Proceedings of the 34th International FLAIRS Conference .

Christoforou, C., Hatzipanayioti, A., and Avraamides, M. (2018). Perspective Taking vs Mental Rotation: CSP-Based Single-Trial Analysis for Cognitive Process Disambiguation. In: International Conference on Brain Informatics. Springer. pp. 109--118.