Find Academic Supervisors

• Creative Technologies
• Games User Research
• Ergogenic Aids
• +6 more

Dr. Pooya Soltani is a Senior Lecturer at Staffordshire University's Digital, Tech, Innovation & Business School. His research bridges game technology with healthcare, sports performance, and human behavior analysis. He holds a PhD in Sports Sciences (Biomechanics and Human Energetics) from the University of Porto, and MSc/BSc degrees from Shiraz University. Key research areas include mixed reality technologies' impact on human behavior, VR applications in rehabilitation, and exergaming for diabetes management. He has secured significant grants, including Marie Skłodowska-Curie Actions (2018) and Collège de France Postdoctoral Funding (2018-2019). Teaching focuses on serious games, military game design, and project management. His work has been featured in BBC, Bloomberg, and Daily Mail, emphasizing public engagement in technology-driven health solutions. Professional highlights include: Designed VR-based training programs for motor control and deception analysis Developed exergame policies adopted by the Brazilian Society of Diabetes Conducted workshops on tech integration for SMEs and creative enterprises Recipient of Whatuni Student Choice Awards 2023 for Facilities & Social Inclusion Current roles include academic leadership, operational management, and enterprise activities, alongside ongoing research in hyper-realistic avatars and their behavioral impacts.

Julian KangView profile

Associate Professor

• 3D/4D Modeling
• Biomimetic Structures
• Virtual Reality-Based Training
• +3 more

Dr. Julian Kang serves as the Department Head and Associate Professor in the Department of Construction and Concrete Industry Management at South Dakota State University. With over 30 years of experience, his career spans industry and academia, including roles at Korea Power Engineering Company and Texas A&M University. He pioneered Building Information Modeling (BIM) education in the U.S. and co-founded the Building Information Modeling Texas Alliance to bridge academia and industry. Education: B.S. and M.S. in Civil Engineering, Yonsei University (Seoul, South Korea, 1986–1988) Ph.D. in Civil Engineering, Texas A&M University (2001) Research Focus: Kang’s research emphasizes 3D/4D modeling, biomimetic structures, VR-based training, and digital fabrication. His innovations include the Computer Aided Virtual Environment (CAVE) for BIM collaboration and stochastic simulation models for construction decision-making. His work addresses challenges in infrastructure sustainability, repair technologies, and immersive visualization systems. Key Contributions: His 2023 studies explore VR spatial estimation accuracy and structural design optimization, while earlier work (2007–2012) established foundational BIM methodologies. He holds a patent for 3D-printed concrete repair and has been recognized with the William A. Klinger Memorial Research Award (2007). Awards & Recognition: William A. Klinger Memorial Research Award (2007) Advising & Grants: Kang’s academic leadership includes advising graduate researchers and securing funding for BIM, VR, and biomimetic projects. His work integrates industry collaboration, exemplified by the BIM Texas Alliance and partnerships with firms like Tongyang Cement. Labs & Teams: Leads the BIM/CAVE immersive system development and collaborates with interdisciplinary teams on digital construction solutions.

Noelia Grande GutiérrezView profile

Assistant Professor

• bioengineering
• computer-aided design (CAD)
• biomechanics
• +2 more

Noelia Grande Gutiérrez is an Assistant Professor in Mechanical Engineering and Biomedical Engineering at Carnegie Mellon University's College of Engineering. She holds a courtesy appointment in Biomedical Engineering. Her research integrates computational engineering with cardiovascular medicine, developing multiphysics models to support clinical decision-making for cardiovascular diseases. Key areas include bioengineering, biomechanics, fluid dynamics, and medical device technology. Her computational frameworks simulate complex physiological processes from platelet deposition to arterial occlusion, enabling patient-specific thrombosis investigations in coronary artery disease. Recent work focuses on multiscale modeling approaches bridging molecular interactions with systemic hemodynamics. Grande Gutiérrez received the American Heart Association Fellowship (2016-2018) for her innovative cardiovascular research.

William StaceyView profile

Professor

• Neural Engineering
• Epilepsy Research
• Biomedical Computation and Modeling
• +3 more

William Stacey, M.D., Ph.D., is a Professor in the Department of Neurology and Biomedical Engineering at the University of Michigan. His research focuses on developing engineering tools to control epilepsy through neural engineering approaches, combining electrophysiology, machine learning, computational modeling, and signal processing. His lab, the Stacey Lab, investigates high-frequency oscillations (HFOs) in epilepsy, seizure mechanisms, and biophysical models of epileptic activity. Collaborations include the Translational Neural Engineering Group and international teams. He is also involved in translational research, including electrode technology and big data analysis of EEG recordings. Dr. Stacey’s work spans clinical applications, such as seizure prediction and stimulation therapies, as well as basic science projects involving rodent models and human patient databases. He currently accepts PhD students for 2024, and his lab is located at NCRC, B14-190, Ann Arbor. Research interests include computational modeling of neural activity, in vivo seizure dynamics, and EEG biomarkers. Key projects involve understanding HFOs’ role in seizure onset, developing real-time detection algorithms, and exploring synaptic pathways to control ictogenesis. Publications highlight advancements in seizure prediction, stimulation protocols, and biomarker validation. His work bridges clinical neurology with engineering innovations, aiming to improve epilepsy treatment through novel technologies and analytical methods. Dr. Stacey’s contributions span academic and clinical domains, with a focus on translating basic science into practical solutions for seizure management. His expertise in neural engineering and epilepsy has led to collaborations across disciplines, including neurology, biomedical engineering, and computational neuroscience.

Thao LaavunenView profile

Researcher

• Information-Seeking Behavior
• Digitalization
• Entrepreneurship
• +3 more

Thao Laavunen is a doctoral student and researcher affiliated with the Faculty of Human and Social Sciences at Åbo Akademi University , specifically the School of Business . Her work focuses on interdisciplinary topics such as information-seeking behavior, digitalization, and entrepreneurship, with a strong emphasis on refugee integration and social innovation. Research Interests: Information behavior in digital contexts, refugee entrepreneurship, social innovation, digitalization of business practices. Email: thao.orrensalo@abo.fi Research Trends: Her publications highlight the intersection of digitalization and entrepreneurship, particularly how information literacy and generational differences influence digital resource selection. She also explores sustainable refugee entrepreneurship through social innovation in Jordan and Finland.

Jennifer L. HamiltonView profile

Professor

• Vaccine Hesitancy
• Medical Communications
• Preventive Care
• +6 more

Jennifer L. Hamilton, MD, PhD , is a Professor and Associate Dean of Simulation at Drexel University's Department of Family, Community & Preventive Medicine. Board-certified in family medicine, she practices in Philadelphia with clinical focus areas including primary care, women's health, integrative medicine, and preventive care. MD - University of Medicine and Dentistry of New Jersey/Robert Wood Johnson Medical School (2001) PhD in Biomedical Engineering - Rutgers University (2000) MS in Biomedical Engineering - Rutgers University (1997) BSEng in Electrical Engineering and Computer Science - Princeton University (1987) Research Interests : Vaccine hesitancy and public health communication Integration of complementary/alternative medicine in primary care Gender disparities in preventive healthcare Neural network applications in neurosurgical procedures Medical education simulation technologies Women's health outcomes research Scientific Contributions : Over 20 years of research in biomedical engineering and family medicine Key publications on CAM integration (2008), vaccine science (2020), and neuroimaging (2000) Pioneering work in neural network applications for Parkinson's disease surgery Multiple peer-reviewed articles in American Family Physician , Journal of Women's Health , and Stereotactic & Functional Neurosurgery Awards & Memberships : Fellow, American Academy of Family Medicine AAFP Vaccine Science Fellowship (2015) Member, Society of Teachers of Family Medicine Clinical Services : Adolescent medicine Contraception Integrative medicine Preventive health care Women's health

Mohammad Ali MoniView profile

Researcher

• Artificial Intelligence
• Computer Vision
• Health Informatics
• +4 more

Dr. Mohammad Ali Moni is a Program Lead at the Centre for AI & Digital Health Technology within Charles Sturt University's Rural Health Research Institute. He holds a PhD in Artificial Intelligence & Data Science from the University of Cambridge and has held postdoctoral positions at prestigious institutions such as the University of New South Wales and the University of Oxford. His research focuses on developing interpretable machine learning models for healthcare applications, particularly in medical imaging, chronic disease prediction, and explainable AI. Education: PhD in AI & Digital Health, University of Cambridge (2014) Postdoctoral training: University of New South Wales, University of Sydney, University of Oxford Research Interests: Artificial Intelligence and Computer Vision Health Informatics and Bioinformatics Medical Imaging Analysis (MRI/fMRI, Ultrasound) Explainable AI for Clinical Decision-Making His work bridges data science and clinical practice, aiming to enhance transparency in AI-driven healthcare solutions. Awards: Charles Sturt Excellence Awards - Highly Commended (2023) Excellence Award (Research) (2024) Senior Honorary Fellow, The University of Queensland (2023–) Grants & Collaborations: Seed funding ($100,000) for graphene-aided biosensor research (2023) Leadership in international research programs on diabetes, stroke, and lung cancer Labs & Initiatives: Active in the Rural Health Research Institute, focusing on AI-driven solutions for regional healthcare challenges.

KlimmerView profile

Professor

• Organizational Design
• Change Management
• Industrial Goods Marketing
• +6 more

Prof. Klimmer is a Professor of Marketing, Organization, and Project Management at the Faculty of Industrial Engineering, Mannheim University of Applied Sciences. He holds a PhD in Business Administration (Dr. rer. pol.) from the University of Mannheim and has extensive industry experience, including roles as Project Leader at Fraunhofer ISI and Director of Corporate Development in a leading medical technology company since 1998. His research focuses on Organizational Design, Change Management, and Industrial Goods Marketing. He teaches courses such as Project Management and Product Planning. Key research interests include optimizing organizational structures, managing change in industrial contexts, and strategic marketing for capital goods. His publications span books like Unternehmensorganisation (2025) and articles on topics like service marketing challenges and process efficiency in production systems. He actively supervises master’s theses on themes like customer satisfaction optimization and market analysis in China’s automotive sector. His expertise bridges academia and industry, with a focus on practical solutions for operational and strategic challenges. He is reachable via m.klimmer@hs-mannheim.de and via Webex at https://hs-mannheim.webex.com/meet/m.klimmer.

Don RoosanView profile

Associate Professor

• Artificial Intelligence
• Quantum Computing
• Healthcare Informatics
• +3 more

Dr. Don Roosan is an Associate Professor in Data Science at Merrimack College, specializing in cutting-edge applications of artificial intelligence (AI), quantum computing, and mixed reality in healthcare. He holds a Ph.D. in Biomedical Informatics from the University of Utah and a PharmD from Purdue University. His research focuses on leveraging AI for improving patient outcomes, quantum computing for drug discovery and molecular design, and mixed reality applications for genomics and biosecurity. He has also contributed to nutrigenomics database development and telehealth security through post-quantum cryptography. Dr. Roosan’s teaching portfolio includes computational sciences, sleep and circadian rhythms, biostatistics, quantum computing, and human-computer interaction. His work integrates AI with health informatics, addressing challenges such as opioid abuse detection, electronic health record optimization, and healthcare equity in underserved populations. He pioneered the PGxKnow augmented reality application for pharmacogenomics education and developed frameworks for blockchain-based healthcare data security. His recent publications highlight advancements in quantum-aided molecular classification, AI-driven EHR exploration, and telehealth biosecurity. His articles emphasize interdisciplinary approaches at the intersection of quantum computing, AI, and healthcare, with a focus on transforming clinical decision-making and drug development. Dr. Roosan’s research also addresses health disparities in digital technology design and the ethical integration of nutrigenomics into clinical practice.

Frimpomaa AmpawView profile

Professor

• Labor Market Economics
• Persistence and Retention in Higher Education
• Race and Gender in STEM Education
• +2 more

Dr. Frimpomaa (Frim) Ampaw is a Professor and Department Chair of the Department of Advanced Studies, Leadership, and Policy at Morgan State University . Her research focuses on higher education administration, with a particular emphasis on the experiences of students from low socioeconomic backgrounds and underrepresented minorities in college transitions, retention, and labor market outcomes. As a quantitative methodologist, she has extensively studied women and minorities in STEM education. B.A. in Economics and Computer Science, University of Ghana, Legon M.A. in Applied Economics, Northeastern University M.S. in Economics, University of North Carolina, Chapel Hill Ed.D. in Higher Education Administration, North Carolina University Dr. Ampaw’s research integrates Labor Market Economics , Higher Education Finance , and Race and Gender in STEM Education , analyzing systemic barriers and equity-focused interventions. Her work explores rural students’ college access, financial leadership in K-12, and equity in STEM pedagogy. Key publication trends span Education , STEM Education , and Economics , with subfields including Postsecondary Access , Diversity in STEM , Student Retention , and Academic Career Transitions . Her studies often employ quantitative frameworks to address equity gaps. Contact: Banneker Building #315J , Morgan State University; Phone: (443) 885-1908; Email: frimpomaa.ampaw@morgan.edu .

• Human Factors Engineering
• Ergonomics
• Vision Science
• +4 more

Dr. Alex Chaparro is a Professor of Human Factors and Behavioral Neurobiology at Embry-Riddle Aeronautical University, directing the Aging, Perception, and Performance Lab. His research focuses on visual requirements of driving, effects of visual impairment on driving performance, and speech perception in cognitive contexts. He holds a BS from Florida Institute of Technology and a PhD from Texas Tech University, with postdoctoral training at Harvard University. Education: BS in Psychology (Florida Institute of Technology), Postdoctoral Studies (Harvard University), PhD in Psychology (Texas Tech University). Research interests include human factors in aviation safety, driver distraction, and inclusive design for aging populations. He has authored over 186 publications and secured grants such as the Carl/Rozina Cassat Professorship (2015) and Coleman Entrepreneurship Fellow (2011). His work addresses checklist efficacy in healthcare, usability of advanced driver-assistance systems, and ergonomic adaptations for older adults. Recent articles explore helicopter EMS accident factors and automotive HUD design for color-vision-impaired users. Awards: WSU Excellence in Research (2009), Ford Foundation Fellowship (1991) Labs: Aging, Perception, and Performance Lab

Brant JonesView profile

Professor

• Combinatorics
• Algorithms
• Game Theory
• +3 more

Brant Jones is a Professor of Pure Mathematics at James Madison University (JMU), where he has been since 2010. He earned his PhD in Mathematics from the University of Washington in 2007 and held a VIGRE Fellowship at the University of California, Davis. His research focuses on combinatorics, particularly games, algorithms, algebraic structures, and enumerative combinatorics, often involving computational tools. He has mentored 28 undergraduate students in research projects and contributed to software libraries like liberiksson for Coxeter group computations. Jones has been awarded NSF grants for JMU's Research Experiences for Undergraduates (REU) program and led workshops at ICERM and AIM. His work has been cited by Don Knuth in The Art of Computer Programming . Education: PhD in Mathematics, University of Washington (2007); Postdoctoral Fellowship at UC Davis (2007–2010). Research Interests: Combinatorial game theory, algebraic structures, enumerative combinatorics, and reflection group representation theory. He frequently uses programming to aid his research and has experience in software engineering. Publications: Over 20 peer-reviewed articles, including works on games of best choice, Kazhdan-Lusztig polynomials, and combinatorial enumeration. Recent work includes collaborations on core partitions and affine permutation patterns. Awards/Grants: NSF REU funding (2017–2023), REUF workshop leadership (2019), citations in The Art of Computer Programming (2021). Teaching: Courses in discrete mathematics, abstract algebra, calculus, and combinatorics. Coordinates JMU's Putnam Competition team. Software Contributions: Developed liberiksson for Coxeter group calculations and contributed to Sage's combinatorics modules.

Ana-Maria CroicuView profile

Professor

• Optimal control
• Optimization
• Uncertainty quantification
• +9 more

Dr. Ana-Maria Croicu is a Professor of Mathematics and Graduate Faculty at Kennesaw State University (KSU), with a Courtesy Professor role at Florida State University's Department of Mathematics. She holds dual Ph.D.s in Applied Computational Mathematics and Statistics (Florida State University, 2005) and Mathematics (Babes-Bolyai University, Cluj-Napoca, 2001), along with degrees in Mathematics and Electrical Engineering from the Technical University of Cluj-Napoca. Her research focuses on optimal control, optimization, uncertainty quantification, and bioscience modeling, with notable contributions to aerodynamics and disease dynamics. She has secured over $1.2 million in NSF funding and led the NSF S-STEM Program supporting disadvantaged STEM students. Dr. Croicu has been recognized with prestigious awards, including the Cobb County Teacher of the Year and multiple teaching honors at KSU. Her academic roles include directing undergraduate research, organizing international conferences, and serving as a Visiting Scientist at NASA Ames Research Center. Education includes advanced training in Romania and the U.S., spanning theoretical mathematics, applied and computational mathematics, statistics, and electrical engineering. She has mentored numerous students across PhD, MS, and undergraduate levels, contributing to research in areas like HIV infection modeling and anthrax disease control. Her work bridges computational methods with real-world applications, emphasizing interdisciplinary collaboration. Key research areas include mathematical modeling of infectious diseases (e.g., Ebola, HIV, anthrax) and robust optimization in engineering contexts. She has presented at major international conferences and co-organized workshops on optimal control and numerical simulations. Her teaching excellence spans online and traditional formats, reflecting her commitment to innovative education.

Ömer Faruk BeycaView profile

Associate Professor

• Data Mining
• Machine Learning
• Artificial Intelligence
• +3 more

Ömer Faruk Beyca is an Associate Professor at Istanbul Technical University's Department of Industrial Engineering. He holds an Integrated Ph.D. from Oklahoma State University and has held academic positions since 2014, including roles as Vice President of Department at both Istanbul Technical University and Fatih University. His research focuses on machine learning applications in healthcare, finance, and energy systems, with notable work on diabetic retinopathy diagnosis via deep learning and supply chain sustainability. Education: Integrated Ph.D. in Industrial Engineering from Oklahoma State University (2007–2013); B.Sc. in Industrial Engineering from Fatih University (2003–2007). Research interests include data mining, artificial intelligence, and optimization techniques applied to medical imaging, financial systems, and energy forecasting. He has supervised 12+ graduate theses and holds editorial roles in journals like Journal of Business Analytics . Recent publications (2023–2024) emphasize hybrid AI models for healthcare diagnostics, dynamic financial decision systems, and sustainability in supply chains. He contributes to projects like sensor-based predictive maintenance and pharmaceutical demand forecasting.

Juan Diego Gutiérrez GallardoView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +3 more

Juan Diego Gutiérrez Gallardo is an Assistant Professor at the Universidade de Santiago de Compostela, specializing in applying Artificial Intelligence to diverse domains. His research emphasizes optimizing low-cost adaptations of base models for specialized tasks, particularly in medical imaging and educational technology. He holds a Doctorate in Modeling and Experimentation from the Universidad de Extremadura (2022), following degrees in Computer Engineering and a Master’s in Secondary Education. Education: BSc in Computer Engineering (2010), MSc in Computer Engineering (2013), Master’s in Education (2016), PhD in Modeling and Experimentation (2022). Research Interests: AI-driven medical imaging, machine learning optimization, and leveraging AI in educational evaluation. His work focuses on reducing computational costs while enhancing model adaptability. His recent articles explore SAM-based medical image segmentation, audio classification via EnCodec latent spaces, and the impact of ChatGPT on engineering education. He has authored over 20 computer science books and translated 10 technical works from English to Spanish. Awards include the JENUI 2023 Best Work Award for impactful research. Teaching responsibilities include 'Technological Tools for Business' and 'Digital Technologies for Cultural Management.' He actively contributes to reproducibility frameworks in data science and hybrid recommendation systems for media.