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Seung-Jun KimView profile

Associate Professor

• Statistical Signal Processing
• Machine Learning
• Optimization
• +6 more

Dr. Seung-Jun Kim is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). His work bridges statistical signal processing, machine learning, and optimization, with applications to cyber-physical systems like smart grids and biomedical imaging. He holds a Ph.D. from the University of California, Santa Barbara, and degrees from Seoul National University. Education: Ph.D., Electrical & Computer Engineering, University of California, Santa Barbara (2005) M.S. and B.S., Electrical Engineering, Seoul National University, South Korea (1996-1998) Research Focus: Dr. Kim's research emphasizes online/decentralized learning, machine learning for cyber-physical systems, and analyzing complex data interactions. His projects include power grid monitoring via subspace clustering, spectrum cartography for cognitive radios, and CNN-based medical image registration. His work spans interdisciplinary applications such as energy management, biomedical diagnostics, and wireless network optimization. Key Contributions: His recent articles highlight advancements in robust signal processing, kernel-based lifelong learning algorithms, and optimizing systems like smart grids and X-ray mammography. His methodologies address real-world challenges in scalability, adaptability, and data-driven decision-making. Grants & Advising: While specific grant details are not provided, his research portfolio indicates sustained engagement with industry and academic challenges. He mentors students in cutting-edge projects combining theory and application, though student names are not listed here. Labs & Teams: Collaborates on projects involving machine learning, wireless systems, and biomedical engineering through UMBC's interdisciplinary research environment.

William PennyView profile

Professor

• Brain Imaging
• Bayesian Inference
• Dynamical Systems
• +3 more

William Penny is a Professor in Psychology at the University of East Anglia (UEA), School of Psychology. He joined UEA in 2017 after serving as a Professor at University College London (UCL). His research focuses on brain imaging methodologies, particularly analyzing fMRI and EEG data using Bayesian Inference, Dynamical Systems, and Probabilistic Machine Learning. He holds a BEng in Electrical Engineering (Nottingham University, 1988), MSc in Communication Engineering (Imperial College, 1989), and PhD in Artificial Neural Networks (Brunel University, 1993). He has led projects including a Wellcome Trust-funded initiative on brain imaging (2019–2024) and a study on brain function during perimenopause with Braincare Limited (2025–2026). His work spans collaborations in neuroimaging analysis, cognitive modeling, and translational neuroscience. His research outputs emphasize Bayesian methods, dynamic causal models, and computational neuroscience, with 84+ peer-reviewed articles. Key areas include cortical degeneration in Huntington’s disease, diet-cognition links, and neural mechanisms of decision-making. His lab, the UEA Brain Imaging Centre (UBIC), advances multimodal neuroimaging techniques. Professional affiliations include the Wellcome Trust Centre for Human Neuroimaging at UCL and international collaborations. No specific awards are listed, but his contributions to neuroimaging methodology are widely recognized.

• Cognitive Psychology
• Computational Neuroscience
• Memory Systems
• +4 more

Arnold Glass is a Professor in the Department of Psychology at Rutgers, The State University of New Jersey. He holds a prominent role within the School of Arts and Sciences, focusing on computational models of cognitive processes. His research investigates how the brain encodes and retrieves information, particularly in visual recognition, memory systems, and decision-making frameworks. Dr. Glass has contributed extensively to understanding the interplay between neural mechanisms and artificial intelligence, aiming to bridge cognitive science with technological applications. His work spans theoretical and applied domains, including studies on classroom learning dynamics, where he has shown how attention allocation and instructional methods impact academic performance. He has also explored prosumer behavior in energy systems, integrating behavioral economics with smart grid technologies. Glass’s research emphasizes the dual-system model of cognition, linking voluntary action, perception, and neural architecture. Recent publications highlight his exploration of memory systems through tasks like same/different matching and the impact of feedback timing on exam performance. His findings have practical implications for educational strategies and cognitive computing, reflecting his interdisciplinary approach to advancing both theoretical and applied knowledge. While no formal awards are listed, his prolific publication record and cross-disciplinary contributions underscore his influence in cognitive psychology and neuroscience. Advising and grant activities are not detailed in the provided materials, but his research themes suggest active engagement with computational modeling and behavioral studies.

David MarcovitzView profile

Associate Professor

• Educational Technology
• Digital Citizenship
• Technology Integration in Schools
• +3 more

David Marcovitz serves as Associate Dean of the School of Education at Loyola University Maryland, where he holds the position of Associate Professor and Chair of the Education Specialties Department. As founding Director of Graduate Programs in Learning Design & Technology, he has shaped the program since its inception in 1997 and teaches core courses including Multimedia Design, Digital Communication, and Technology Leadership. His academic credentials include a Ph.D. in Educational Technology from the University of Illinois at Urbana Champaign, with research focused on technology support in elementary schools. Prior professional experience encompasses high school computer science instruction and technology specialist roles. Dr. Marcovitz's research explores critical intersections of technology and equity , with primary interests in digital citizenship, the second-level digital divide, and social justice frameworks in educational technology. His work examines how technology connects students beyond classroom boundaries while addressing systemic access barriers and ethical implementation challenges. His publication trajectory (2006-2022) demonstrates evolving focus from foundational technology integration toward contemporary issues of social justice, mobile learning (BYOD), and copyright frameworks. Recent scholarship increasingly addresses equity implications of technology deployment, reflecting broader shifts in educational technology discourse toward inclusive and critical approaches. Recognition includes the Microsoft Community Contributor Award (2012) and six consecutive Microsoft PowerPoint MVP Awards (2005-2010), highlighting practical contributions to educational software implementation. As program director and faculty member, he has mentored graduate students in Learning Design & Technology while developing curriculum that bridges theoretical frameworks with practical leadership skills. His professional service includes membership in the International Society for Technology in Education and Maryland Society for Educational Technology, supporting field-wide knowledge exchange.

Darren NicholsonView profile

Professor

• Human-Computer Interaction
• Virtual Teams
• Virtual Experiences (VR/AR)
• +2 more

Dr. Darren Nicholson is a Professor at Rowan University's William G. Rohrer College of Business, specializing in human-computer interaction, virtual teams, and information systems pedagogy. He holds a Ph.D. in Management Information Systems from Washington State University and has received multiple teaching awards, including Professor of the Year and the Teaching Wall of Fame for Teaching Excellence. His research explores technology-enhanced learning, virtual collaboration, and enterprise systems. Nicholson's work emphasizes innovative pedagogy, with publications investigating role-play exercises, blockchain applications in education, and learning style adaptability. His recent articles demonstrate a focus on student engagement methodologies and emerging tech integration. Notable honors include: Rohrer College of Business Professor of the Year Innovation in Teaching Scholarship (Rohrer Advisory Board) Teaching Wall of Fame for Teaching Excellence He actively contributes to curriculum development and mentors students through experiential projects, though specific grant/advisee details aren't provided in the source text.

Julie SzendreyView profile

Professor

• Consumer Behavior
• Financial Socialization
• Marketing Education
• +3 more

Julie Szendrey is a Professor of Business at Walsh University, holding degrees from the University of Dayton (B.M.E., M.B.A.) and Anderson University (D.B.A.). Her research focuses on consumer behavior, financial socialization processes, and the intersection of family dynamics with financial decision-making. Key areas of interest include frugality measurement, generational financial influence, and marketing education methodologies. Dr. Szendrey's work explores how familial communication and resources during adolescence shape financial behaviors in young adulthood, as well as perceptions of economic mobility. She has also contributed to pedagogical innovations, such as integrating VITA tax assistance programs into marketing courses and utilizing public county auditor data for student research projects. Her publications span topics from digital emotional literacy in corporate communication to the impact of video games on academic performance. Though no specific awards or grants are documented, her scholarship emphasizes practical applications of marketing research and interdisciplinary educational approaches.

Ardhendu BeheraView profile

Professor

• Computer Vision
• Deep Learning
• Multimodal AI
• +4 more

Ardhendu Behera is a Professor of Computer Vision & AI at Edge Hill University and co-director of the Intelligent Visual Computing Research Centre. He holds a post-doctoral background from the University of Leeds and has contributed to interdisciplinary research in AI-driven healthcare, autonomous systems, and defense applications. His work bridges computer vision with multimodal AI, emphasizing real-world impact through collaborations with institutions like the University of Bristol, IISc Bangalore, and UCL. Prof Behera’s research spans deep learning, healthcare diagnostics, and autonomous vehicle systems. He has pioneered AI tools for dementia monitoring (via social robotics and multimodal data) and developed algorithms for traffic scene analysis, driver behavior recognition, and medical imaging. His recent projects include breast cancer detection networks and plant disease recognition systems using transfer learning. Key Awards: Fellow of the UK Higher Education Academy (HEA) Editorial Roles: Associate Editor for IEEE Transactions on Image Processing Outreach: Media coverage on BBC News, ITV, and The Times for dementia research; keynote speaker at NCVPRIPG 2019 and ICIoT 2019 His research emphasizes interdisciplinary collaboration, with over 100 peer-reviewed publications in top-tier venues like CVPR, ECCV, and IEEE journals. He actively mentors students in PhD/MRes programs focusing on AI and computer vision applications.

Claudia Quaiser-PohlView profile

Professor

• Developmental Psychology
• Educational Psychology
• Gender Studies
• +6 more

Prof. Claudia Quaiser-Pohl is a Professor of Developmental Psychology and Psychological Diagnostics at the University of Koblenz, serving as Head of the Department of Developmental Psychology and Psychological Diagnostics and Vice President for Research and Transfer. She holds a Habilitation (2003) and PhD (1995) in Psychology, with prior studies in Human Medicine and Psychology. Her academic leadership roles include Dean of the Department of Educational Sciences (2014–2022) and Scientific Director of the Ada Lovelace Project (since 2010), promoting women in STEM. Her research focuses on spatial cognition, gender differences in STEM participation, and educational psychology, with over 150 publications. She has led initiatives like the Women Career Center and the Graduate School of Gender Research. Her work integrates cross-cultural perspectives, diversity management, and digital education challenges. Educational Background: Habilitation in Psychology, Otto von Guericke University Magdeburg (2003) PhD in Philosophy (summa cum laude), Heinrich Heine University Düsseldorf (1995) Diploma in Psychology (very good), University of Bonn (1990) Undergraduate studies in Psychology, Philipps University Marburg (1984–1987) Research Interests: Developmental and spatial cognition Gender differences in STEM education and careers Educational technology and digitalization in schools Cross-cultural psychology, especially in Kenya and Poland Mentoring and diversity management in academic contexts Leadership & Initiatives: Scientific Director, Ada Lovelace Project (Rhineland-Palatinate STEM Women Hub) Women Career Center at University of Koblenz-Landau Graduate School of Gender Research (2016–2020) Recent Research Trends: Focus on mental rotation performance across ages/genders, digital interventions for smartphone addiction, and cultural influences on psychological constructs. Recent studies explore STEM participation barriers for women and the role of spatial skills in educational outcomes. Grants & Advising: Led multiple funded projects on gender equality in STEM and educational digitization. Advised doctoral candidates in the ProBi Doctoral Program in Educational Research (2016–2021). Labs/Teams: Coordinates interdisciplinary teams in the Ada Lovelace Project and collaborates with institutions in Ghana, Kenya, and the US (e.g., Harvard, MIT).

• AI for Law Enforcement
• Community Safety
• Digital Forensics
• +4 more

Campbell Wilson is an Associate Professor in the Department of Data Science & AI at Monash University, serving as founding co-director of the AiLECS Research Centre. His research bridges technical and socio-technical aspects of AI应用于 law enforcement and community safety, with a focus on digital forensics, machine learning, and ethical AI frameworks. He has held leadership roles including Deputy Head of the Caulfield School of IT and Associate Dean (International). Education: PhD in Computer Science (Monash University, 2003), Master of Computing (1996), and Bachelor of Science in Applied Mathematics (1993), all from Monash University. Research interests include AI applications for law enforcement, cybersecurity, bioinformatics, and information retrieval. He leads projects like 'Improving Legal Frameworks for CSAM Prosecutions' and 'Detecting Threats in Temporal Networks', collaborating with agencies like Victoria Police and the British Asian Trust. Teaching commitments include chief examining roles for units such as FIT2100 Operating Systems and FIT5166 Information Retrieval Systems. He actively supervises PhD students focusing on AI for law enforcement and community safety. Labs/Teams: AiLECS Research Centre focuses on AI-driven solutions for law enforcement challenges. Projects emphasize ethical AI deployment and forensic data analysis.

Niels TaatgenView profile

Professor

• Cognitive Modeling
• Artificial Intelligence
• Human Behavior
• +4 more

Niels Taatgen is a Professor of Cognitive Modeling at the University of Groningen , affiliated with the Faculty of Science and Engineering and the Bernoulli Institute . His research focuses on human multitasking , cognitive architectures , mental fatigue , and skill acquisition . He has received significant recognition, including the Teacher of the Year award at the University of Groningen in 2016 and an ERC grant in 2011 for multitasking research. His recent publications span neuroscience , artificial intelligence , and educational technology , with a focus on visuo-motor learning , language modeling , and adaptive working memory . His work often integrates fMRI , cognitive modeling , and spiking neural networks to explain human behavior and improve AI systems. Scientific Awards: Teacher of the Year, University of Groningen (2016) His research group explores multitasking strategies , attentional control , and brain-inspired computing , with applications in medical education , human-computer interaction , and cognitive training .

Chris TaylorView profile

Professor

• Computer Vision
• Medical Image Analysis
• Machine Learning
• +4 more

Chris Taylor is a Professor of Medical Biophysics and Computer Science at the University of Manchester, holding joint appointments in the Division of Informatics, Imaging & Data Sciences (Faculty of Biology, Medicine and Health) and the School of Computer Science (Faculty of Science and Engineering). He serves as Associate Vice President for Digital Strategy & Innovation. His research focuses on computer vision, medical image analysis, and healthcare technology, with contributions to technology transfer and industry partnerships. Education: BSc (1967), PhD (1972) in Computer Image Analysis from the University of Manchester. Notable Roles: Former Head of the School of Computer Science (2004–2008), Chair of EPSRC Healthcare Technologies Strategic Advisory Team. Research interests include developing AI-driven medical imaging tools, nailfold capillaroscopy, and IoT applications in healthcare. He has pioneered technologies for systemic sclerosis diagnostics and mHealth solutions. Key achievements include five company spin-offs, OBE (2000), and multiple fellowships in engineering and medical societies.

Samuel KaskiView profile

Professor

• Machine Learning
• Probabilistic Modelling
• Artificial Intelligence
• +5 more

Samuel Kaski is a Professor of Artificial Intelligence and Machine Learning at Aalto University and the University of Manchester. He leads the Finnish Center for Artificial Intelligence (FCAI) and the Manchester Centre for AI Fundamentals (AI-FUN). His research focuses on probabilistic modeling, Bayesian inference, collaborative AI, and applications in health, biology, and user interaction. He holds roles such as Director of the ELLIS Unit Helsinki and Founding Director of the ELLIS Institute Finland. Research interests include foundational machine learning, distribution shifts, generative models, and human-AI collaboration. He has pioneered work on Bayesian experimental design, simulation-based inference, and AI-assisted drug discovery. His projects span interdisciplinary collaborations in synthetic biology, cognitive science, and healthcare. Recent publications highlight advancements in amortized Bayesian methods, robust learning, and multi-agent systems. Notable awards include the Turing AI Fellowship (2021) and the Aalto Pioneering Excellence Award (2022). Over 36 PhD students and numerous postdocs have been mentored by Kaski, with many securing faculty positions. His teams operate across institutions, emphasizing open-source tools and impactful applications. Key labs include FCAI, ELLIS Finland, and AI-FUN, fostering innovation in AI fundamentals and societal impact.

Pedro LopesView profile

Associate Professor

• Human Computer Interaction
• Virtual and Augmented Reality
• Wearable Computing
• +4 more

Pedro Lopes is an Associate Professor in the Computer Science Department at the University of Chicago. His research focuses on Human-Computer Integration, exploring interfaces that integrate directly with the human body, such as muscle stimulation wearables and sensory substitution systems. He leads the Human-Computer Integration Lab and collaborates with groups like the Systems Group and CERES Center for Unstoppable Computing. Key research areas include wearable computing, haptics, and sustainable computing. His work has been recognized with awards including multiple CHI/UIST Best Papers, Sloan Fellowship, and the IEEE VGTC Virtual Reality Significant New Researcher Award. Notable projects include devices that enhance multitasking efficiency, reduce electronic waste, and create thermal/olfactory illusions. Awards highlight impactful contributions to HCI, including innovations in EMS applications, sustainable design, and brain-computer interfaces. Pedro teaches courses on human-computer interaction, interactive device engineering, and circuit design. His lab actively engages in interdisciplinary collaborations, advancing technologies that merge biology with computing for future human-compatibility.

Toru SekinoView profile

Professor

• Ceramics
• Low-dimensional nanomaterials
• Environmentally friendly materials
• +4 more

Prof. Toru Sekino is a Professor at Osaka University's Institute of Scientific and Industrial Research (ISIR), leading the Advanced Hard Materials Research laboratory. He holds a Doctor of Engineering from Osaka University (1997) and has served as ISIR Director from 2020-2024. His research focuses on advanced ceramics and nanomaterials, emphasizing multifunctional composites, photocatalytic materials, and environmentally sustainable processes. Key contributions include titanium oxide nanotube synthesis and bioactive glass development. Awards include the 2022 IUMRS-Frontier Materials Award and the 2016 Minister of Education Technology Award. He chairs committees in materials science and holds editorial roles in academic journals. Education: PhD (Materials Engineering, Tohoku University, 1997), MEng (1991), BEng (1988). Research spans over 470 publications and 13 patents. Current projects include low-temperature sintering processes and self-healing ceramics. Collaborates with global institutions on nanomaterials and energy applications.

• Neurology
• Alzheimer's Disease
• EEG Analysis
• +4 more

Eliezer Sternberg, MD is an Assistant Professor in the Department of Neurology at UMass Chan Medical School and T.H. Chan School of Medicine. His research focuses on neurodegenerative diseases, EEG analysis, and clinical neurology. He has authored studies on Alzheimer's disease, Parkinson's tremors, and cognitive neuroscience. Education: BS in Neuroscience (Brandeis University), MD (Tufts University School of Medicine). Research highlights include investigating seizure patterns in Alzheimer's patients, developing EEG grading standards, and exploring multitasking neural mechanisms. Collaborations involve gamma wave stimulation trials and delirium assessment methods. His work has been cited in geriatrics and neurology contexts. No formal awards listed but publications show significant interdisciplinary impact. Active in clinical and translational research networks including collaborations with neuroimaging and cognitive neuroscience teams.