Find Academic Supervisors

• Human-AI Interaction
• Artificial Intelligence
• Human Factors Engineering
• +3 more

Junho Park is an Assistant Professor at the University of Calgary, holding cross-appointment across three academic units: Schulich School of Engineering (Biomedical Engineering), Cumming School of Medicine (Community Health Sciences), and Faculty of Arts (Psychology). He also serves as Faculty Researcher at W21C Research and Innovation Centre, Member at O'Brien Institute for Public Health, and Child Health and Wellness Researcher at Alberta Children's Hospital Research Institute. PhD in Industrial and Systems Engineering (Texas A&M University) MSc in Industrial Engineering (Seoul National University) BSc in Computer and Industrial Engineering with Psychology minor (Yonsei University) His research focuses on Human-AI Interaction, Human Factors Engineering, and Ergonomics, with specific applications in biosignal processing for prosthetics, workload assessment in assistive technologies, and cognitive support systems for aging populations. Current projects include augmented reality biofeedback systems and autonomous vehicle interfaces for individuals with cognitive impairments. Recent publications demonstrate expertise in applying machine learning to biomedical engineering challenges and human factors assessments. The HERO Lab actively seeks postdoctoral researchers and graduate students in areas spanning human-AI interaction, ergonomics, and computational modeling. Scientific Awards Student Member with Honours, Human Factors and Ergonomics Society (2023) IEEE International Conference on Human-Machine Systems Travel Grant (2022) Institute for Applied Creativity Student Fellowship, TAMU (2022) Korean-American Scholarship Foundation (2021) HFES Best Student Paper Award (2021)

• Biomedical Engineering
• Bioelectronics
• Artificial Intelligence
• +3 more

Rüştü Murat Demirer serves as an Assistant Professor in the Department of Electrical and Electronics Engineering at Işık University's Faculty of Engineering and Natural Sciences. His academic career spans decades with active teaching responsibilities including Biomedical Engineering courses such as Clinical Care Informatics, Biosignal Processing, and Medical Imaging since at least 2012 across multiple institutions including Işık University and Bahçeşehir University. His educational foundation includes: PhD in Biomedical Engineering from Boğaziçi University (1983-2002) MS in Energy from Istanbul Technical University (1980-1982) BS in Electronics and Communications Engineering from Kocaeli University (1976-1980) Dr. Demirer's research integrates Biomedical Engineering with cutting-edge computational neuroscience, focusing on Bioelectronics, Artificial Intelligence applications, and Neuroscience. He pioneers methodologies for analyzing brain dynamics through EEG/ECoG signal processing, entropy-based biomarker development, and machine learning algorithms for neurological and psychiatric conditions. His work bridges theoretical neuroscience with clinical applications in epilepsy, bipolar disorder, and brain-computer interfaces. Analysis of his publication trends reveals strong interdisciplinary convergence between neuroscience, biomedical engineering, and artificial intelligence. Key methodological themes include Hilbert transform applications, nonlinear dynamics in brain signals, entropy quantification for psychiatric diagnostics, and hybrid machine learning approaches for medical signal classification. This research trajectory demonstrates consistent innovation in translating complex brain signal analysis into clinically relevant diagnostic tools. Dr. Demirer has actively mentored 11 graduate students (10 Master's and 1 PhD) between 2013-2025. His advisees' research spans diverse applications including: Machine learning for cybersecurity threat detection Cryptocurrency market analysis using predictive modeling EEG/eye-tracking fusion for cognitive decision studies Medical diagnostics through convolutional neural networks Natural language processing for offensive language detection He maintains professional engagement as a member of the Chamber of Electrical Engineers (Elektrik Mühendisleri Odası) while teaching specialized courses across biomedical engineering, cybersecurity, and data science domains.

• Signal Processing
• Computer Vision
• Robotics
• +5 more

Petros Maragos is a Professor at the National Technical University of Athens (NTUA) in the School of Electrical and Computer Engineering, where he directs the Division of Signals, Control and Robotics. He founded the Computer Vision, Speech Communication & Signal Processing Lab (1999) and the Hellenic Robotics Center of Excellence (2025). His research spans signal processing, computer vision, robotics, and machine learning, with 450+ publications and leadership in 50+ EU/Greek/US projects. Education includes a Dipl.Ing. from NTUA (1980), M.Sc./Ph.D. from Georgia Tech (1982/1985), and faculty positions at Harvard University (1985-1993) and Georgia Tech (1993-1998). Research Focus: Multimodal perception, nonlinear systems, assistive robotics, and deep learning. Recent work integrates tropical geometry with neural networks, robotic healthcare applications, and sign language technologies. Articles emphasize neural architectures, real-world robotics, and AI for social good. Awards: IEEE Fellow (1995), EURASIP Fellow (2010) IEEE W.R.G. Baker Prize (1995) NSF Presidential Young Investigator Award (1987-1992) CVPR/PETRA Best Paper Awards (2022-2025) Advising & Grants: Supervised 30+ PhDs and 130+ Master's students. Secured funding from EU Horizon 2020, NSF, and Greek national programs for projects like i-Walk (robotic mobility) and e-Prevention (mental health monitoring). Labs: Leads NTUA's Intelligent Robotics Lab and co-founded the Robotics Institute at Athena Research Center, focusing on human-robot interaction and perception systems.

Pietro AricoView profile

Assistant Professor

• Brain-Computer Interfaces (BCI)
• Bioengineering
• Signal Processing
• +12 more

Pietro Arico is an Assistant Professor at the Department of Computer, Control and Management Engineering, Sapienza University of Rome, and Chief Technology Officer at BrainSigns. He holds a PhD in Bioengineering from University of Bologna (2014) and an M.Sc. in Biomedical Engineering from Sapienza University of Rome (2010). Biomedical Engineering Education Expertise in Brain-Computer Interfaces (BCI) Specializes in biosignal processing and machine learning His research focuses on: Passive BCI Systems: Real-time assessment of mental states (workload, attention, stress) using EEG, ECG, and other biosignals in operational environments like driving and aviation. Signal Processing Innovation: Development of algorithms for artifact removal and feature extraction in non-laboratory settings. Hybrid BCI Applications: Integration of EEG and EMG for rehabilitation systems targeting post-stroke patients. Recent work trends emphasize: Real-time mental workload monitoring in clinical and automotive contexts. Artifact correction techniques for EEG data in naturalistic environments. Neurophysiological characterization of mixed reality embodiment. Scientific awards include: 2024 - MINDTOOTH paper selected for AIIC National Conference 2014 - Award 'Massimo Grattarola' for BCI research 2014 - Scientific Prize 'I Guidoniani' for mental load studies 2013 - Finalist for Scientific Award 'I Guidoniani' He teaches Biosignal Processing , Biological System Models , and Biosignal Processing and Electromagnetic Fields in Sapienza's MSc programs in Biomedical Engineering and Medicine and Surgery HT.

• Neuroscience
• Biomedical engineering
• Biosignal Interpretation
• +7 more

Keiko Momose is an Associate Professor at Waseda University's Faculty of Human Sciences, specializing in Biomedical Engineering. She holds a Doctor of Engineering degree from Waseda University and has maintained continuous academic appointment since 2005. Her academic journey began with undergraduate studies at Waseda University's School of Science and Engineering, followed by advanced research that led to her current position. Dr. Momose's research primarily focuses on biosignal interpretation, with particular expertise in visual evoked potentials (VEPs), eye movement analysis, and mother-infant interaction studies. Her work integrates engineering principles with neuroscience to develop novel methods for assessing visual function and understanding human cognitive processes. She has made significant contributions to the development of pseudorandom binary sequence (PRBS) stimulation techniques for rapidly assessing temporal frequency characteristics of the visual system, which has important clinical applications in diagnosing and monitoring conditions like glaucoma and macular degeneration. Her recent research has expanded into cross-cultural studies of mother-infant interactions, comparing Japanese and Scottish parenting behaviors during feeding and infant pick-up scenarios. This work reveals culturally specific patterns in intersubjectivity, timing, and empathy between mothers and infants, demonstrating how cultural contexts shape early developmental experiences. Her publications show a clear progression from technical development of VEP measurement techniques to broader applications in developmental psychology and cross-cultural neuroscience. Dr. Momose has secured multiple research grants from the Japan Society for the Promotion of Science, including projects on eye movement training for children with dyslexia, blink-based detection methods for visual motion evoked potentials, and the early development of parent-infant inter-body relationships. Her research demonstrates consistent innovation in methodology development while addressing clinically and developmentally significant questions. She actively teaches across Waseda University's programs, including undergraduate courses in Human Sensory Processing and Measurement and Modeling of Human, as well as graduate-level seminars in Biomedical Engineering. Her teaching spans both traditional and online degree programs, reflecting her commitment to accessible education in biomedical engineering principles and applications.

Daivaras SokasView profile

Researcher

• Digital Signal Processing
• Machine Learning
• Biomedical Engineering
• +1 more

Daivaras Sokas is a researcher at the Institute of Biomedical Engineering, Kaunas University of Technology, affiliated with the Biosignal Analytics Laboratory. His primary responsibilities include conducting laboratory work and grading reports for the course 'Digital Signal Processing and Machine Learning.' He holds an ORCID ID (0000-0001-5723-3655). Research Interests: His work focuses on Digital signal processing Machine learning applications in biomedical contexts Electrical and electronic engineering (T001) Laboratory Affiliation: He is actively involved with the Biosignal Analytics Laboratory at KTU.

Andrius PetrėnasView profile

Associate Professor

• Biosignal Processing
• Physiological Signal Modeling
• Clinical Data Analysis
• +3 more

Dr. Andrius Petrėnas is a Senior Researcher and Associate Professor at the Kaunas University of Technology (KTU), affiliated with the Faculty of Electrical Engineering and the Department of Electronics Engineering. He serves as the Laboratory Manager of the Biosignal Analytics Laboratory within the KTU Institute of Biomedical Engineering, where he leads research initiatives focused on biosignal processing algorithms and physiological signal modeling. Scientific role: Senior Researcher in projects SV/115, SV3/116, and SV3240177 Primary research interests: analysis of biosignals for clinical applications, algorithm development, and physiological system modeling

• Brain-Computer Interfaces
• Biosignal Processing
• Assistive Robotics
• +3 more

Gabriel Pires is an Adjunct Professor in the Department of Electrical Engineering at the Polytechnic Institute of Tomar (Portugal) and Integrated Researcher at the Institute of Systems and Robotics - University of Coimbra. He coordinates Lab. VITA.IPT (Life Assisted by Intelligent Environments) and leads the Brain-Computer Interface research group in the Human-Centered Mobile Robotics Lab. His cross-disciplinary affiliations include collaboration with the Coimbra Institute for Biomedical Imaging and Translational Research. Dr. Pires specializes in EEG-based brain-computer interfaces and biosignal processing, aiming to enhance BCI reliability for clinical rehabilitation and assistive technologies. His research spans: BCI usability enhancement Wearable biosensors development Telehealth platforms Human-robot interaction Machine learning for medical applications He has supervised over 70 students and researchers, and manages multiple national/EU projects including: BCI4ALL (€1.8M FEDER, 2025-2028) FLEXEMG (wearable muscle sensors) UpReGain (stroke rehabilitation) POWERAUT (autism intervention) Honors include the IEEE Transactions Best Paper Award (2022) and Fraunhofer Portugal Challenge.

Phil RichterView profile

Research Fellow

• Chemoreception
• Taste and Odor Perception
• Gastric Physiology
• +5 more

Dr. Phil Richter is a Research Fellow (Postdoc) at the Leibniz Institute for Food Systems Biology at the Technical University of Munich, conducting pioneering research in the Metabolic Function & Biosignals Research Group on extra-oral chemoreceptor physiology. His academic credentials include: PhD in Natural Sciences (summa cum laude) from Leibniz Institute for Food Systems Biology at TUM (2020-2025) Master of Science in Organic Chemistry from University of Bayreuth, Elite Graduate Program (2017-2020) Master of Education from University of Bayreuth (2017-2020) First state teaching examination (Biology/Chemistry) in Bavaria (2019) Dr. Richter's research centers on chemosensory mechanisms beyond classical perception , investigating how food metabolites interact with gastrointestinal receptors to influence physiological processes. His work reveals how sweet proteins like thaumatin are digested into bitter peptides that activate gastric TAS2R receptors , triggering anti-inflammatory pathways and modulating acid secretion. Current projects examine environmental pollution effects on nutrient sensing and industry-backed applications of bitter plant extracts for gastric health. His 2022-2025 publication record demonstrates consistent innovation in molecular food-gut interactions , employing advanced techniques like atomic force microscopy to characterize receptor binding without calcium signaling. This research bridges food chemistry and gastrointestinal physiology to develop novel dietary interventions for inflammation-related conditions. As Postdoc Representative (since 2025), Dr. Richter actively shapes the institute's research culture while contributing to Leibniz Association-funded projects. Though not supervising students directly, he mentors junior researchers in the group's collaborative environment focused on translating chemosensory discoveries into health applications. The Metabolic Function & Biosignals Research Group operates at the intersection of food science and human biology, utilizing cutting-edge infrastructure at the Freising campus to decode how dietary compounds influence health through chemoreceptor-mediated pathways.

Markus JunghöferView profile

Professor

• Affective Neuroscience
• Cognitive Neuroscience
• Clinical Neuroscience
• +3 more

Prof. Markus Junghöfer serves as faculty at the Institute of Biomagnetism and Biosignal Analysis within the Faculty of Medicine, University of Münster . He leads the "Neural Mechanisms of Emotion and Attention" working group, conducting research on emotional perception, learning, and attention control in clinical and healthy populations. His research program investigates affective neuroscience through studies of emotion recognition, awareness in emotional processing, and mechanisms underlying fear, anxiety, depression, and tinnitus. The lab employs non-invasive brain stimulation techniques to modulate neural activity and develop therapeutic interventions for neurological and psychiatric conditions. The lab maintains active research projects including the Tinnitus Project , KIKAN Project , and participation in a multi-center SFB/TRR collaborative initiative . Students seeking research internships or thesis opportunities are directed to contact Prof. Junghöfer via email for consideration.

Bruce EisensteinView profile

Professor

• Digital Signal Processing
• Pattern Recognition
• Deconvolution
• +5 more

Bruce Eisenstein is the Arthur J. Rowland Professor of Electrical and Computer Engineering at Drexel University's College of Engineering. He has held significant administrative positions including Department Head of Electrical and Computer Engineering (1980-1995) and two terms as Associate Dean of the College of Engineering (1976-1980, 2004-2005). His academic credentials include: PhD in Electrical Engineering from University of Pennsylvania (1970) MSEE from Drexel University (1965) BSEE from Massachusetts Institute of Technology His research spans multiple domains including digital signal processing, pattern recognition, deconvolution techniques, biomedical applications, wireless communications, and engineering education. He has developed innovative methodologies in signal analysis and educational pedagogy, with particular focus on system identification and curriculum development. Publication analysis reveals three primary themes: 1) Advanced signal processing techniques (deconvolution, feature extraction), 2) Biomedical engineering applications (ECG analysis), and 3) Engineering education reforms (curriculum design, project-based learning). His recent works demonstrate increasing focus on educational leadership and professional standards. Awards and honors: C. Holmes MacDonald Award for Outstanding Young Electrical Engineering Educator (1976) Delaware Valley Engineer of the Year (2000) Professional leadership highlights: IEEE President (2000) and executive roles including Vice President for Technical Activities and Treasurer President of Eta Kappa Nu and National Electrical Engineering Department Head Association ABET program evaluator across multiple engineering disciplines General Chair of Frontiers in Education Conference (1984) He has held research positions at Stanford University, NASA-Ames Research Center, and Princeton University. While specific information about grants, laboratories, or supervised students isn't provided, his extensive administrative roles indicate significant organizational leadership.

• Machine Learning in Medicine
• Medical Signal Processing
• Cardiovascular Simulation
• +3 more

Dr. Urs Hackstein serves as a Research Assistant in the EU project QUMPHY and Lecturer for special tasks at the Department of LSE, Technical University of Central Hesse (THM), Germany. His work bridges computational methods with medical diagnostics, focusing on uncertainty quantification in machine learning applications for cardiovascular analysis. Educational background: Dr. rer. nat. (Doctor of Natural Sciences) Dipl.-Math. (Diploma in Mathematics) Research Interests: Machine Learning in Medicine: Developing frameworks to quantify uncertainties in ML algorithms for medical signal interpretation, particularly photoplethysmography (PPG) analysis. Cardiovascular Diagnostics: Creating non-invasive support systems for early aortic aneurysm detection through biofluid mechanics simulations and biosignal processing. Medical Data Science: Integrating biosignal analysis with clinical data for predictive modeling in cardiovascular medicine. Active Research Projects: EU project QUMPHY: Quantifying uncertainties in machine learning for medical physics applications under Prof. Bernhard's supervision. BMBF project CardioInBaMed: Developing AI-driven diagnostic tools for aortic aneurysm detection through biosignal processing. He maintains laboratory facilities at Ringallee 37 D14.2.01, Gießen, supporting experimental work in biofluid mechanics and medical signal acquisition.

Aurélien EtiembleView profile

Assistant Professor

• Battery Energy Storage
• Lithium Ion Batteries
• Hydrogen Storage
• +5 more

Aurélien Etiemble is an Assistant Professor at ECAM School of Engineering in Lyon, France, working within the Materials and Structures department. His academic career focuses on the intersection of advanced materials science and energy storage technologies, with particular emphasis on additive manufacturing processes and battery electrode characterization. Dr. Etiemble's research interests span multiple domains of materials engineering, with primary focus on Battery Energy Storage and Additive Manufacturing technologies. His work explores the fundamental relationships between material microstructure and performance in energy storage applications, particularly lithium-ion and metal hydride batteries. He has developed expertise in advanced characterization techniques including X-ray computed tomography, focused ion beam, and acoustic emission measurements to study material behavior under operational conditions. Analysis of his recent publications reveals a clear research trajectory focusing on improving manufacturing processes for advanced materials. His work spans from fundamental studies of thin-film metallic glasses with antibacterial properties to practical applications in battery technology and metal 3D printing. The publications demonstrate strong interdisciplinary collaboration across materials science, electrochemistry, and mechanical engineering domains. Dr. Etiemble maintains an active research network with collaborations across multiple institutions, particularly with researchers at INSA Lyon and CEA Liten. His work has been cited over 800 times, indicating significant impact in the fields of battery technology and additive manufacturing.

Mohammad A. AhadView profile

Associate Professor

• Bioinstrumentation
• Biosensors
• Biosignal Modeling
• +4 more

Dr. Mohammad A. Ahad is an Associate Professor and Interim Department Chair in Electrical & Computer Engineering at Georgia Southern University, where he has been faculty since 2011. His research focuses on bioinstrumentation, biosensors, and biomedical signal processing, particularly in Electrical Impedance Myography (EIM) for non-invasive medical diagnostics. Education: Ph.D. Electrical and Computer Engineering, University of Tennessee, Knoxville (2007) M.S. Electrical and Computer Engineering, University of Tennessee, Knoxville (2002) B.S. Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (1998) Research Focus: Dr. Ahad's work spans biomedical instrumentation development, FPGA-based system design, and computational modeling of biological systems. His EIM research enables novel diagnostic approaches for muscle pathologies and cancer detection through finite element analysis and electrode optimization. Grant Leadership: Secured competitive funding as PI for multiple NIH and NSF projects focusing on human-robot interfaces, non-invasive instrumentation, and early cancer detection techniques using impedance methods. Teaching: Specializes in hands-on engineering education including digital design with DE2 boards, embedded systems programming, and signal processing laboratories.

Simon C. CorkView profile

Senior Lecturer

• Physiology
• Obesity Research
• Medical Education
• +3 more

Dr Simon C. Cork serves as Senior Lecturer at Anglia Ruskin University's School of Medicine, holding key leadership roles including Admissions Lead, Phase 1 Lead for the MBChB program, co-lead for Widening Participation, and Physiology Lead. His career uniquely integrates neurophysiological research on obesity mechanisms with national reform of medical education access. His academic credentials include: BSc (Hons) Biomedical Science, Durham University (2008) PhD in Neurophysiology, Durham University (2013) PGCert in Clinical Education, King's College London (2020) Dr Cork's research spans obesity physiology —focusing on gut hormones like GLP-1 and vagus nerve signaling in appetite regulation—and educational equity , where he designs admissions frameworks to identify potential beyond traditional metrics. His dual expertise drives innovations in both pharmacotherapeutic understanding and inclusive medical training pathways. Analysis of his 15 most recent publications reveals two dominant trajectories: cutting-edge investigations into GLP-1 receptor agonists' mechanisms (including post-bariatric applications) and transformative medical education research addressing widening participation through AI tools, alternative qualifications, and online assessment systems. This synergy positions him at the intersection of physiological discovery and educational reform. His distinguished contributions are recognized through: 2026 Widening Participation in Physiology Prize Lecture (Physiological Society) As an educator, Dr Cork supervises research students while shaping national policy via UCAT Board membership to dismantle admission barriers. His public engagement—evidenced by BBC documentaries, Cheltenham Science Festival appearances, and New York Times coverage—translates complex science for global audiences, particularly regarding anti-obesity medications. Collaborating with Imperial College London and University College London, he maintains active neurophysiology research while leading ARU's Medical School initiatives through the Medical Schools Council Selection Alliance and Physiological Society fellowship.