Associate dean of research at the institute for cognitive and brain sciences, Shahid Beheshti University, Iran
Dr. Reza Khosrowabadi is an Associate Professor of Cognitive Modeling at the Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran. With a focus on cognitive neuroscience and computational modeling, his research spans areas like neurodevelopment, brain-computer interfaces, EEG-based emotion recognition, and behavioral disorders. Dr. Khosrowabadi has extensive experience in both academia and industry, having worked as a postdoc researcher at renowned institutions such as A*STAR, Singapore, and Shahid Beheshti University. In addition to his academic roles, he is deeply involved in the Iranian cognitive science community, contributing as a scientific advisor and editor for leading journals. His work has earned numerous prestigious awards, including the Top Scientist Award from Shahid Beheshti University (2023). Dr. Khosrowabadi’s passion for interdisciplinary research in
cognitive neuroscience and machine learning continues to shape the future of neurodevelopmental research and smart assistive technologies.
Profile
Goole scholar
Strengths for the Award
- Extensive and Diverse Research Background:
- Dr. Khosrowabadi has a diverse research portfolio, spanning from cognitive modeling and neurodevelopmental processes to neuroimaging, emotion recognition, and brain-computer interface technologies. His work covers essential fields in computational neuroscience, biomedical signal processing, and cognitive neuroscience.
- Notably, his focus on neurodevelopmental disorders, particularly autism, and the impact of various stimuli on brain function (e.g., emotion and stress), places him at the forefront of interdisciplinary research bridging neurology, psychiatry, and engineering.
- International Collaborations and Recognition:
- Dr. Khosrowabadi’s postdoctoral work at A*STAR, Duke-NUS Medical School, and collaborations across Iran, Singapore, Germany, and Brazil show his ability to lead and engage in high-level international collaborations. These global connections are reflected in the broad citation of his work (over 200 citations for several publications).
- His active participation in global conferences, such as OHBM, FENS, and IBRO, showcases his recognition as a leading figure in the neuroscience community. His scientific involvement in several prestigious journals as an editor and reviewer adds to his strong academic presence.
- Innovative Contributions:
- His research on EEG-based emotion recognition, autism spectrum disorder detection, and stress reactivity using EEG signals pushes the boundaries of biomedical engineering and cognitive neuroscience. His work on brain networks, especially in conditions such as autism, chronic stress, and mental workload, demonstrates an innovative approach combining machine learning, neuroimaging, and signal processing.
- Noteworthy publications such as “Automated detection of autism spectrum disorder using CNN” and “EEG-based emotion recognition using self-organizing map” have significant impact in clinical neuroscience and computational medicine.
- Commitment to Education and Mentorship:
- Dr. Khosrowabadi has mentored several students and early-career researchers, particularly in the context of cognitive science and neuroscience at the Institute for Cognitive and Brain Sciences at Shahid Beheshti University.
- His role as an instructor and advisor in IBRO schools and as editor for journals like the Journal of Basic and Clinical Neuroscience demonstrates a commitment to educating and guiding the next generation of researchers in these fields.
- Awards and Grants:
- Dr. Khosrowabadi’s numerous awards, including the Iranian National Talent Award, Young Researcher Award, Top Scientist Award, and travel grants from DAAD and FENS, attest to his recognition in both the national and international research community.
Areas for Improvement
- Broader Impact on Clinical Practice:
- While Dr. Khosrowabadi’s work has substantial theoretical and technical contributions, further emphasis could be placed on translating research findings into clinical practice. For example, enhancing the applicability of EEG-based systems for real-time monitoring and intervention could further solidify the real-world impact of his research.
- His focus on basic science and computational models is essential, but increasing collaboration with clinical settings (e.g., hospitals, treatment centers) could help bridge the gap between neuroscience research and healthcare applications.
- Interdisciplinary Collaboration with Psychiatry and Clinical Psychology:
- Although his work covers cognitive disorders and neural systems, greater interdisciplinary collaboration with psychiatrists, psychologists, and neurologists could enhance his research’s impact on understanding and treating disorders like autism and stress-related conditions. Joint studies with clinical psychology could potentially result in more comprehensive interventions for mental health.
- Research on Long-term Impact and Follow-ups:
- Given the nature of his research in developmental processes and mental health disorders, there could be more long-term studies that track the effects of his proposed interventions and cognitive models over time, offering data on the durability and effectiveness of treatments or assessments.
Education
Dr. Reza Khosrowabadi holds a PhD in Computer Science (Computational Intelligence) from Nanyang Technological University (NTU), Singapore (2007-2012), where he focused on modeling emotions based on EEG signals. His academic journey began with a Bachelor’s Degree in Biomedical Engineering (Bioelectronics) from Sahand University of Technology, Iran (1998-2002). After completing his PhD, he worked as a postdoctoral researcher at the prestigious A*STAR – Neuroscience Research Partnership (NRP) at Duke-NUS Graduate Medical School, Singapore, specializing in neuroimaging in behavioral disorders (2012-2013). He furthered his postdoctoral research at Shahid Beheshti University, Tehran, focusing on neurodevelopmental processes in infancy (2014-2015). His education, spanning both technical and neuroscience disciplines, has provided him with a strong foundation in machine learning, brain-computer interfaces, and cognitive modeling, which continue to inform his innovative research in cognitive neuroscience.
Experience
Dr. Reza Khosrowabadi’s professional career combines academic research, teaching, and industry experience. He is an Associate Professor at the Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, where he has been actively involved since 2014. His academic roles include teaching courses such as Cognitive Assessment, Biomedical Signal Processing, and Machine Learning. Additionally, Dr. Khosrowabadi has contributed to the field as an instructor for the International Brain Research Organization (IBRO) School in Tehran. His research fellowship experience includes a significant tenure at A*STAR – Neuroscience Research Partnership (NRP), Singapore (2012-2013), focusing on neuroimaging for behavioral disorders. He has also worked in various engineering roles, including as a service engineer at Akbarieh Co., Tehran, and at hospitals in Iran, providing practical exposure to medical devices and EEG technology. This blend of academic and hands-on experience allows Dr. Khosrowabadi to bridge the gap between research and clinical applications in neuroscience.
Awards and Honors
Dr. Reza Khosrowabadi’s impressive career has been recognized through numerous awards and honors. He received a prestigious NTU Scholarship for his PhD studies (2007-2011) and various student travel grants, including the IJCNN 2009 and IEEE CIS IJCNN 2011 Travel Grants. He was awarded a Research Fellowship at Duke-NUS Graduate Medical School (2012-2013), as well as a DAAD Travel Grant for research in Germany (2015). In 2015, Dr. Khosrowabadi earned the Young Researcher Award from Shahid Beheshti University, followed by the Iranian National Talent Award. He has been awarded several competitive project grants, including from the National Brain Mapping Center and CSTC-Iran. His leadership in scientific communities is further reflected in his service as the Executive Chair for the Iranian Human Brain Mapping Congress (2015-2016). Most recently, he was honored with the Top Scientist Award from Shahid Beheshti University in 2023, cementing his status as a leading figure in cognitive neuroscience.
Research Focus
Dr. Reza Khosrowabadi’s research lies at the intersection of cognitive neuroscience, computational modeling, and neurodevelopment. His primary focus is on the modeling of neurodevelopmental processes in infancy and understanding brain network dynamics using EEG, MRI, and other neuroimaging tools. He explores the relationship between brain function and behavior in neurodevelopmental disorders, such as autism, using advanced techniques like machine learning and brain-computer interfaces (BCIs). Dr. Khosrowabadi’s work also emphasizes the recognition of emotions through EEG signals, particularly in the context of affective computing. His interdisciplinary approach combines computational intelligence with cognitive neuroscience, aiming to develop smarter assistive technologies for individuals with cognitive impairments. He has contributed significantly to understanding the neurobiological underpinnings of behavioral disorders and is at the forefront of innovative neuroimaging research. With a deep interest in cognitive rehabilitation and pattern recognition, his work continues to push boundaries in both theoretical and applied neuroscience.
Publication Top Notes
- Automated detection of autism spectrum disorder using a convolutional neural network 🤖🧠
- EEG-based emotion recognition using self-organizing map for boundary detection 💡🔊
- The effect of noise exposure on cognitive performance and brain activity patterns 🎧🧠
- A Brain-Computer Interface for classifying EEG correlates of chronic mental stress 🧠💻
- ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion from EEG Signal 🤖💓
- Screening of autism based on task-free fMRI using graph theoretical approach 🧠🧩
- Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal 🧠🎶
- Alterations in brain network topology and structural-functional connectome coupling relate to cognitive impairment 🧠🔗
- Affective computation on EEG correlates of emotion from musical and vocal stimuli 🎶🎤
- Support vector machine classification of brain states exposed to social stress test using EEG-based brain network measures 🤖💭
Conclusion
Dr. Reza Khosrowabadi is a highly qualified candidate for the Best Researcher Award due to his substantial contributions to cognitive neuroscience, neuroimaging, and signal processing in the context of brain function and mental health disorders. His work is widely recognized, both regionally and internationally, and has direct relevance to both academic research and clinical practice. He has a proven record of innovation and leadership in the field of cognitive modeling and brain sciences, making him a standout researcher.