Brain-Computer Interface (BCI) Professors and Supervisors

Frida HeskebeckView profile

Researcher

Lund UniversitySweden

Frida Heskebeck is a Doctoral student at the Department of Automatic Control , Lund Institute of Technology , Lund University , and a member of the LTH Profile Area: AI and Digitalization . She actively contributes to the research group on EEG-based Brain-Computer Interfaces (BCI) led by Prof. Bo Bernhardsson . Research Focus: Optimization of next-generation BCI using cloud computing and individualization of real-time systems. Teaching: Delivers lectures, webinars, and lab sessions for courses like Process Control and Systems Engineering (2024), Physiological Models and Computations (2023), and Automatic Control (2021, 2020). Awards: Recipient of the Pedagogical Prize for best teaching assistant in 2021 (M-guild and W-guild) and Best Master's Thesis in 2020. Research Trends: Her recent articles focus on BCI calibration, real-time control, and cloud integration. Broad keywords include Control Engineering , Machine Learning , and Neuroscience , with sub-fields like Domain Adaptation , Signal Processing , and Online Teaching . Scientific Distinctions: Teaching assistant of the year (awarded by the M-guild) 2021 Teaching assistant of the year (awarded by the W-guild) 2021 Best Master's Thesis 2020 Advising and Collaborations: Supervision of master's theses for Tom Andersen (2021) and Johanna Wilroth (2020), where the latter received a scholarship. She also held roles in the department's board and organized seminars like the AI Lund lunch seminar in 2024.

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Jaimie B. DoughertyView profile

Associate Professor

Drexel UniversityUnited States

Jaimie B. Dougherty, PhD is an Associate Professor at Drexel University's School of Biomedical Engineering, Science & Health Systems. She holds a BS and PhD in Biomedical Engineering, with postdoctoral experience in cortical encoding research. Education: BS in Biomedical Engineering, Rutgers University PhD in Biomedical Engineering, Drexel University (collaboration with Temple University) Research Interests: Jaimie focuses on brain-computer interfaces , neural encoding , and electrophysiological signal acquisition and processing , particularly in spinal cord injury and postural adjustments. Scientific Awards: Shriners Hospital for Children Postdoctoral Fellowship Current Work: She aims to integrate her expertise in functional output and cortical encoding for brain-machine interface (BMI) applications.

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Yueqing LiView profile

Associate Professor

Lamar UniversityUnited States

Dr. Yueqing Li serves as an Associate Professor in the Department of Industrial and Systems Engineering within Lamar University's College of Engineering. His expertise spans neuroergonomics, human-computer interaction, and data analytics with significant contributions to transportation safety and assistive technologies. Dr. Li's educational foundation includes: Ph.D. in Industrial Engineering from North Carolina State University M.S. in Industrial Engineering from University of Arkansas M.S. in Economics from Nanjing University of Aeronautics and Astronautics B.S. in Electronics Engineering from Zhengzhou University His research program integrates neuroergonomics (BCI systems, neurocognitive processing), human-computer interaction (haptic interfaces, AR-based systems), human factors engineering (driving safety, occupational ergonomics), and data science (machine learning applications for safety analytics). Current projects focus on UAV security systems, pipeline leak detection, and transportation resilience in extreme weather. Analysis of Dr. Li's 15 most recent publications reveals dominant themes in transportation safety (32% of works), neuroergonomics applications (28%), and machine learning for safety engineering (24%). His Southeast Texas-focused crash severity studies demonstrate methodological innovation through CART and fuzzy systems, while his BCI research bridges rehabilitation engineering and human factors. Key recognitions include: Engineering Faculty Fellow (Lamar University College of Engineering, 2017-2020) Eric Malstrom Endowed Memorial Scholarship (University of Arkansas) Multiple university-level teaching and research awards across three institutions Dr. Li actively mentors graduate students (11 primary advisees since 2017) and secures substantial research funding, including $516,031 from NSF for high-performance computing infrastructure and $33,172 from the Center for Advances in Port Management for autonomous freight safety. His $600,000+ grant portfolio addresses critical challenges in port security, pipeline monitoring, and transportation resilience. The Human Factors and Ergonomics Laboratory under Dr. Li's direction features 16-channel EEG systems, BIOPAC data acquisition suites, wireless EMG/ECG modules, driving simulators, and Gazepoint eye tracking technology. His research team collaborates with TEES and the Texas Department of Transportation on interdisciplinary projects spanning neuroergonomics, transportation safety, and assistive technology development.

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S M Shafiul HasanView profile

Assistant Professor

Mercer UniversityUnited States

Dr. S M Shafiul Hasan serves as Assistant Professor of Computer Science in the Department of Informatics and Mathematics at Mercer University's College of Professional Advancement. His academic journey includes a PhD and MSc in Electrical and Computer Engineering from Florida International University, complemented by MSc and BSc degrees from Bangladesh University of Engineering and Technology. Prior to Mercer, he conducted postdoctoral research at Emory University developing ML models for stroke recovery diagnostics. His research bridges artificial intelligence and healthcare through: Biomedical signal processing for stroke and Parkinson's diagnostics Neurovascular coupling analysis using transfer entropy EEG-based movement intention prediction systems EHR data mining for atrial fibrillation and dementia risk With 15 peer-reviewed publications since 2016 spanning IEEE Transactions, Stroke, and Frontiers in Neurology, his work demonstrates consistent translational impact. Recent publications (2023-2025) focus on contralateral neurovascular coupling in stroke patients and real-time gait intention prediction, reflecting an evolving research trajectory toward clinical implementation. As an active IEEE member, he contributes to professional discourse while mentoring students through research-intensive projects. His Emory postdoctoral experience indicates strong NIH-relevant grant activity, though specific awards aren't publicly listed. Current work integrates computer vision with prosthetic control systems, showing expansion into assistive robotics.

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Bin HeView profile

Professor

Menlo CollegeUnited States

Bin He is the Trustee Professor and Head of Biomedical Engineering at Carnegie Mellon University, with adjunct appointments in Electrical and Computer Engineering and the Neuroscience Institute. Previously, he held the Distinguished McKnight University Professor and Medtronic-Bakken Endowed Chair positions at the University of Minnesota. His research revolutionizes noninvasive brain-computer interfaces, enabling mind-controlled prosthetics and drones. Key innovations include the first continuous 3D robotic arm control via EEG. His lab pioneers neuroimaging and electrophysiological source imaging, integrating AI and machine learning to decode neural signals. Research spans: BCI Applications: Prosthetics, drone control, and therapeutic devices for neurological disorders. Imaging Breakthroughs: High-resolution EEG/MEG source localization and cardiac activation mapping. Translational Impact: Collaborations with medical device industries to commercialize technologies. Awards include the Distinguished McKnight Professorship and Medtronic-Bakken Endowed Chair. He leads major journals and societies, driving global neuroengineering advancements. Current grants support BCI scalability and clinical translation.

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Marie-Hélène BEKAERTView profile

Lecturer

University of LilleFrance

Marie-Hélène BEKAERT serves as a Lecturer at ESPRIT and holds an elected position on the unit council, demonstrating active involvement in academic governance. She is based in office S4.06 at the Scientific City campus and affiliated with the BCI research team. Her research focuses on interdisciplinary work at the intersection of: Brain-Computer Interface systems Neuroscience applications Biomedical engineering solutions Computational neuroscience Through her role in the BCI team, she contributes to advancing neural signal processing and assistive technologies. Her academic service extends beyond teaching to institutional leadership via the unit council, reflecting commitment to both research innovation and academic community development.

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José RouillardView profile

Lecturer

University of LilleFrance

José Rouillard is a Lecturer-Researcher in Computer Science (section 27) at Université de Lille, affiliated with the CRIStAL laboratory (Centre de Recherche en Informatique, Signal et Automatique de Lille) where he works in the Brain-Computer Interface (BCI) research team. His academic position combines teaching responsibilities with active research in human-computer interaction, particularly focusing on novel interface technologies and assistive applications. Dr. Rouillard's primary research interests center around Brain-Computer Interfaces with particular expertise in Steady-State Somatosensory-Evoked Potentials (SSSEP). His work explores multimodal interaction techniques, virtual reality integration with BCI systems, and applications for individuals with motor disabilities such as Duchenne muscular dystrophy. Recent publications (2023-2024) demonstrate continued innovation in BCI technology, including Wizard of Oz studies on user perception, advanced SSSEP recording techniques with cEEGrid systems, and multimodal cobot interaction frameworks using MQTT protocol. His research bridges theoretical neuroscience with practical applications for assistive technologies. As an educator, Dr. Rouillard has created one of the most comprehensive App Inventor 2 teaching resources available, with 76 detailed projects covering the full spectrum of mobile application development. His course materials progress from basic applications to advanced implementations involving Bluetooth communication with Arduino, Firebase database usage, and AI APIs including OpenAI's ChatGPT and DALL-E. His teaching spans multiple academic years, with documented student projects from 2013 through 2023 across various Master's programs including MMD IAE, MIAGE, and e-Services. Supervised PhD thesis: "Hybrid brain-machine interface to overcome disability caused by Duchenne muscular dystrophy" (Alban Dupres, 2016) Supervised PhD thesis: "Filtrage somesthésique pour des interfaces cerveau-ordinateur utilisant des stimulations vibro-tactiles" (Jimmy Petit, 2022) Dr. Rouillard maintains a strong educational presence through his extensive online resources, including YouTube video tutorials, NextCloud file sharing for course materials, and detailed project guides. His student projects demonstrate practical applications of mobile development across diverse domains including health monitoring, gaming, social networking, and educational tools. The breadth of his educational impact is evident in the hundreds of student applications documented from 2013-2023, showcasing his commitment to practical, hands-on learning in computer science education.

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