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Zygmunt PizloView profile

Professor

• 3D Shape Perception
• Computational Vision
• Mathematical Psychology
• +4 more

Zygmunt Pizlo is a Professor and Falmagne Endowed Chair in Mathematical Psychology at the Department of Cognitive Sciences, University of California-Irvine. His research focuses on 3D shape perception, computational vision, and the principles underlying human and machine perception. He holds a Ph.D. in Psychology from the University of Maryland and prior degrees in Electrical Engineering from Poland. Pizlo’s work emphasizes symmetry, complexity, and veridicality in shape perception, proposing that the human visual system employs global constraints like symmetry to infer 3D structure from 2D images. His academic lineage traces back to notable mathematicians, and his contributions include pioneering theories on shape constancy, the Traveling Salesman Problem (TSP), and binocular vision models. He co-founded the ViPER Lab, where research explores 3D shape recovery and computational models of perception. Pizlo’s books, such as *3D Shape* (MIT Press, 2008) and *Making a Machine That Sees Like Us* (Oxford, 2014), synthesize his interdisciplinary approach. He collaborates with institutions like the Center for Theoretical Behavioral Sciences and organizes conferences on interdisciplinary vision research. Key themes in Pizlo’s research include the role of symmetry and a priori constraints in perception, the integration of global and local visual cues, and the application of psychological principles to AI. His work bridges cognitive psychology, mathematics, and engineering, aiming to create machines that emulate human visual capabilities.

Jordan GrecoView profile

Research Professor

• Biophotonics
• Photoactive Proteins
• Molecular Electronics
• +6 more

Jordan Greco is an Assistant Research Professor in the Department of Chemistry at the University of Connecticut. He is a member of the Birge Research Group and co-founder of LambdaVision Incorporated, a company focused on developing bacteriorhodopsin-based technologies for medical and industrial applications, including retinal implants and optoelectronic systems. His work bridges fundamental biophysical research with applied engineering, emphasizing protein-based solutions to societal challenges. Greco holds a B.S. in Chemistry and Anthropology from the University of Connecticut (2010), followed by a Ph.D. in Physical Chemistry (2015) and a postdoctoral fellowship (2015–2017) at the same institution. His education and training have equipped him with expertise in molecular spectroscopy, quantum mechanics, and genetic engineering. His research interests encompass theoretical simulations of excited-state properties in biological chromophores and retinylidene proteins, alongside the design of novel biophotonic devices such as protein-based retinal implants, holographic processors, and photovoltaic cells. He employs advanced techniques like time-resolved absorption spectroscopy and differential scanning calorimetry to study photoactive proteins, with recent focus on enhancing their functionality through quantum dot integration and microgravity manufacturing. Greco’s articles emphasize advancements in vision restoration, optoelectronic materials, and space-based biomaterial production. Key themes include optimizing retinal implant pixel arrays, understanding light-harvesting mechanisms in photosynthetic proteins, and developing methods for long-term data storage using photochromic proteins. As part of LambdaVision’s team, his contributions have been supported by grants from NASA and collaborations with Boeing and CASIS. These partnerships aim to leverage microgravity environments for scalable thin-film production of protein-based devices. Greco is affiliated with the Birge Research Group at UConn’s Department of Chemistry and LambdaVision Incorporated. His interdisciplinary approach, combining physical chemistry and engineering, drives innovations in medical technology, energy systems, and biomolecular electronics.

Jonathan RubinView profile

Professor

• Emergency Medicine
• Clinical Informatics
• Public Health
• +3 more

Jonathan Rubin, MD is a Professor and Division Chief of System Informatics and Analytics at the Medical College of Wisconsin's Department of Emergency Medicine. His work focuses on clinical informatics, emergency care optimization, and public health interventions. He has contributed to studies on prehospital care protocols, EMS system efficacy, and community-based health initiatives. Research interests include geospatial analysis of trauma outcomes, asthma management strategies, fire safety interventions, and EMS system performance. His work bridges clinical practice with data-driven solutions for emergency medicine challenges. Publications span emergency medicine innovations, from asthma treatment protocols to evaluating the impact of fire safety programs during EMS calls. Rubin's interdisciplinary approach addresses both acute care delivery and long-term public health strategies.

Michael KingView profile

Associate Professor

• Biometrics
• Cyber Identity
• Machine Learning
• +3 more

Dr. Michael King is an Associate Professor in the Department of Computer Engineering and Sciences at Florida Institute of Technology, with a joint appointment at the Harris Institute for Assured Information. He holds a PhD in Electrical Engineering from North Carolina A&T State University (2001). His research focuses on biometrics, cyber identity, and machine learning, particularly addressing challenges in facial recognition accuracy, algorithmic fairness, and adversarial machine learning. Prior to academia, he spent over a decade in the U.S. Intelligence Community, leading research initiatives such as IARPA’s BEST Program. His work spans biometric system design, privacy-preserving techniques, and mitigating demographic biases in AI systems. Education: PhD in Electrical Engineering, North Carolina Agricultural and Technical State University, 2001 Research interests include the technical and ethical dimensions of biometric systems, with an emphasis on improving accuracy across demographics and enhancing privacy. His recent articles analyze factors like interpupillary distance, image illumination, and sunglasses impact on face recognition systems. He has also explored adversarial attacks on AI models and their mitigation strategies. His professional experience includes roles as Intelligence Community Department Lead for the White House’s Subcommittee on Biometrics and Identity Management (2005–2012), showcasing his expertise in bridging academic research with government policy. While no specific grants or awards are listed, his contributions to national security and technology policy are notable. He currently advises students in topics related to biometrics and machine learning, though no named advisees are documented. Labs/Teams: Active in the Harris Institute for Assured Information, focusing on cyber analytics and identity protection technologies.

• Biomedical Engineering
• Automotive Systems
• Computer Vision
• +3 more

Martin Glavin is a Professor at the National University of Ireland, Galway, affiliated with the Department of Electronic & Electrical Engineering within the College of Engineering and Informatics. His research focuses on cutting-edge areas such as biomedical engineering, automotive systems, and computer vision. Key contributions include advancements in image processing for low-light environments, driver gaze analysis for cyclist safety, and optimizing automotive camera systems. He has collaborated extensively with co-authors like Edward Jones and Darragh Mullins, yielding over 70 peer-reviewed publications since 2002. His work spans journals like IEEE Transactions and conferences such as ICC and ICARCV. Research interests include safety-critical object detection for autonomous vehicles, microwave imaging for medical diagnostics, and 5G-enabled V2X communication systems. Glavin's interdisciplinary efforts bridge signal processing, machine learning, and engineering applications, addressing real-world challenges in healthcare and transportation.

• Human-Computer Interaction
• Accessibility
• User Interface Design
• +5 more

Junko Shirogane is an Associate Professor in the Department of Computer Science and Engineering at Waseda University's School of Fundamental Science and Engineering. With over 25 years of academic research spanning from 1998 to 2024, she has established herself as a prominent researcher in human-computer interaction, accessibility, and user interface design. Her extensive publication record demonstrates consistent contributions to the fields of software engineering and human-computer interaction. Dr. Shirogane's research interests focus on Human-Computer Interaction, Accessibility, User Interface Design, Web Accessibility, Software Engineering, and Requirements Engineering. Her work particularly emphasizes designing systems that accommodate users with visual impairments and developing methods to evaluate and improve software usability. She has pioneered approaches for analyzing webpage layouts, visualizing importance areas, and converting color schemes for color-impaired users. Her research bridges theoretical software engineering concepts with practical applications that directly impact user experience. Her publication trends reveal a strong focus on accessibility challenges, with recent work (2020-2024) concentrating on supporting visually impaired users through innovative techniques like reading voice modification, webpage validation visualization, and text highlighting methods. Earlier work (2014-2019) focused more on GUI consistency, scenario generation, and requirements engineering. The breadth of her research spans from fundamental software engineering principles to applied user interface solutions. Dr. Shirogane has maintained a long-standing research collaboration with Yoshiaki Fukazawa (27 joint publications), Hajime Iwata (22 joint publications), and other researchers at Waseda University. This collaboration network has produced numerous publications in prestigious venues including IEICE Transactions on Information Systems, IEEE Access, and major conferences like JCKBSE, ICSOFT, and IUI.

Ernad BešlagićView profile

Assistant Professor

• Metrology
• Additive Manufacturing
• Aerodynamics and Wind Energy
• +3 more

Ernad Bešlagić is an Assistant Professor at the Department of Automation and Metrology, Faculty of Mechanical Engineering, University of Zenica (UNZE BA). He holds a Dr. Sc. degree in Polytechnics from the Faculty of Mechanical Engineering in Mostar, awarded in 2021. His academic journey includes a Master's in Metrology (2013) and a Bachelor's in Mechanical Engineering (2002), both from UNZE BA. He has been a faculty member since 2008, transitioning from roles like Senior Assistant to his current position since 2022. Bešlagić’s research focuses on additive manufacturing precision, wind energy systems, and metrology. He has contributed to projects involving 3D printing accuracy, wind tunnel testing for Darrieus turbines, and fatigue analysis of mechanical components. As a co-author of university textbooks and peer-reviewed papers, his work bridges theoretical concepts with practical engineering solutions. He also leads the Citizens' Association 'Education for the new age - STEAM education,' promoting interdisciplinary learning. His professional activities include mentoring students across mechanical engineering disciplines and contributing to national/international conferences. He has collaborated on hardware/software development for wind turbine prototyping and metrology systems, emphasizing real-world applications of engineering principles.

Alpay DORUKView profile

Lecturer

• Information Security
• Cryptology
• Embedded Systems
• +5 more

Alpay DORUK is a Lecturer and the Head of the Cyber Security Department at the Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University. Previously, he served as a Lecturer at Tekirdag Namik Kemal University (2011–2020) and a Research Assistant at Izmir Institute of High Technology (1999–2011). His expertise spans Information Security, IoT, and Embedded Systems, with a focus on ontology engineering, machine learning applications, and sensor networks. Research highlights include developing ontology-based frameworks for IoT sensors and web services, designing wheelchair control systems using image processing, and analyzing superconductor properties via SEM image statistics. He has supervised over a dozen academic projects and one Master’s thesis on facial movement tracking using image processing. Active in academic administration, he coordinated Erasmus and Farabi programs and led departmental initiatives as Department Head. His refereeing roles include peer review for journals like Turkish Journal of Electrical Engineering and conferences such as ICECENG. He has authored/co-authored two books on cybersecurity and computer engineering, and contributed to international projects like the Sayısal Kontrol Sistemleri software development (2006–2010). Recent work emphasizes IoT device monitoring, blockchain-inspired data structures, and machine learning for automotive efficiency analysis. His teaching spans operating systems, software engineering, and agile development, reflecting his blend of theoretical and applied expertise.

• Optimization
• Quantum Computing
• User Interface Design
• +3 more

Niraj Dayama is an Associate Professor in the Department of Information Technology at Arcada University of Applied Sciences, affiliated with the School of Engineering, Culture and Wellbeing. He holds a Doctor of Philosophy. His research focuses on optimization techniques, quantum computing applications, user interface design, and algorithm development for interactive systems. Dr. Dayama's work bridges computational methods with human-centric design challenges. Educational Background: Doctor of Philosophy (PhD), details of academic programs not explicitly stated in provided texts. Affiliations include Arcada UAS with a primary role in Information Technology education and research. Research Interests: Dr. Dayama explores optimization in diverse domains such as quantum computing ecosystems, user interface layout generation, and scheduling problems. His contributions span algorithm design for grid-based layouts, real-time adaptive interfaces, and combinatorial solutions for UI/UX challenges. Recent work emphasizes leveraging quantum computing for problem decomposition and full-stack quantum software development. Publications reflect a shift toward quantum computing and optimization since 2020, complemented by longstanding engagement with layout design and scheduling algorithms. Notable trends include cross-disciplinary approaches merging computational methods with human interaction principles. No scientific awards or grants are explicitly mentioned in the provided texts. Advising roles or student supervision details are not listed.

• Robotics and Automation
• Plant Disease Detection
• Spectral Imaging
• +3 more

Gerrit Polder is a Researcher at Wageningen University & Research, affiliated with the Robotics and Automation department (PE&RC). His work focuses on advancing technologies for plant disease detection, spectral imaging, and robotics in agricultural systems. He has contributed to projects such as OPTIMA, which aims to improve disease management in perennial crops and open-field vegetables using integrated pest management and smart camera systems. His research interests include machine learning applications in agriculture, non-destructive plant phenotyping, and the development of automated systems for crop monitoring. Key areas include spectral imaging for quality assessment, deep learning for disease detection, and 3D plant segmentation techniques. PhD supervision: Co-promotor for projects on 4D plant phenotyping, pre-symptomatic disease detection, and machine vision in hydroponic agriculture. Key contributions: Over 160+ publications, including patents on 3D plant reconstruction and smart camera systems. Affiliations: Active in international collaborations, such as EU-funded OPTIMA, and frequently presents at conferences on spectral imaging and precision agriculture. Recent work emphasizes the integration of spectral imaging and AI for early disease detection in crops like grape, apple, and carrot, as well as automated quality assessment in tomatoes and kiwifruit. His research bridges robotics, computer vision, and agricultural science to enhance sustainable farming practices.

Savvas VassiliadisView profile

Professor

• Energy Harvesting
• Wearable Technologies
• Textile Engineering
• +4 more

Savvas Vassiliadis is a Professor in the Department of Electrical and Electronics Engineering at the University of West Attica. He holds additional roles as Institutional Coordinator of the Erasmus+ Program and has served as Director of a Section, Head of the Department of Electronics Engineering, and member of various administrative councils. His educational background includes a PhD from the National Technical University of Athens, alongside earlier degrees in Textiles, Electronics, and Electrical and Computers Engineering. His research focuses on interdisciplinary fields such as wearable technologies, energy harvesting through textile-based systems, and materials science. Notable areas include triboelectric generators, electromagnetic shielding of textiles, and applications for visually impaired individuals. His work also spans textile mechanics, IoT integration, and smart fabrics with thermochromic properties. Recent publications (2022–2024) highlight advancements in leather-based triboelectric systems, cyber resilience frameworks, and NFC-enabled wearable devices. He has contributed to over 70 peer-reviewed articles, emphasizing sustainable energy solutions and functional textile innovation. His academic contributions are further reflected in roles organizing conferences like AITAE 2018 and in e-textile educational methodologies. No scientific awards are explicitly listed, though his extensive publications and administrative roles underscore his academic leadership. He has advised numerous projects but no named students are documented here. His work bridges textile engineering with electronics, addressing both technical and societal challenges through innovative material science and wearable technology.

Darren KoenigView profile

Assistant Professor

• Visual Optics
• Physiological Optics
• Ocular Disease
• +3 more

Darren Koenig is an Assistant Professor of Optometry at the Illinois College of Optometry, where he joined the faculty in 2018. He teaches clinical methods, procedures labs, and optics courses for 1st and 2nd-year students. His prior experience includes positions at MCPHS University School of Optometry, University of Houston College of Optometry, Brook Army Medical Center, and Lackland Air Force Base. Dr. Koenig holds an OD from Nova Southeastern University College of Optometry and a PhD in Physiological Optics and Vision Science from the University of Houston College of Optometry. His research focuses on geometric, physical and visual optics, vision quality in aging populations, and optical/neurological limits to visual function. His publications demonstrate expertise in adaptive optics, visual psychophysics, and age-related vision changes. Key research trends include innovations in optical measurement techniques and understanding physiological changes in vision across the lifespan. Awards & Honors: Bausch + Lomb Ezell Fellow Ruth L. Kirschstein National Research Service Award National Eye Institute/ARVO Travel Grant Minnie F. Turner Memorial Fund Award Beta Sigma Kappa Honor Society Professional Organizations: Fellow of the American Academy of Optometry with memberships in AOA, Optical Society of America, ARVO, and AAAS.

Peter BexView profile

Professor

• Vision Science
• Clinical Ophthalmology
• Neuroscience
• +5 more

Peter Bex is Chair and Professor of Psychology at Northeastern University's College of Science, leading the Translational Vision Lab. His research bridges basic visual neuroscience and clinical ophthalmology, focusing on sensory processing under real-world conditions and developing diagnostic/therapeutic tools for blinding diseases like AMD, Glaucoma, and Amblyopia. He holds a PhD in Visual Neuroscience and has pioneered adaptive vision testing methods like AIM (Angular Indication Measurement). His lab collaborates with institutions like the Boston Museum of Science to advance eye movement and attention research. Research interests include: 1) Real-world vision modeling using dynamic natural scenes, 2) Neurological basis of visual deficits in amblyopia and cerebral visual impairment, 3) Development of tablet-based diagnostic tools for color vision and stereopsis. Recent work explores how event knowledge influences gaze patterns and the neural correlates of visual search in impaired populations. Over 50 peer-reviewed articles span vision science, neuroscience, and clinical ophthalmology. Notable contributions include discovering how peripheral optical quality predicts myopia development and demonstrating dorsal/ventral stream differences in CVI patients. His lab's innovations include fusion-range testing via eye tracking and gaze-contingent paradigms for studying scotoma effects. Grants and collaborations support translational research, with emphasis on maximizing residual vision in visually impaired populations. Active projects include developing brain-vision diagnostic systems and exploring tactile-augmented perception for low-vision rehabilitation.

• Control Engineering
• Robotics
• Mechatronics
• +3 more

Stephen Mascaro is an Associate Professor (Lecturer) in the Department of Mechanical Engineering at the University of Utah, where he has served since 2005. He currently holds the role of Director of Robotics Studies, effective January 2024. His academic journey includes degrees from Clarkson University (BS in Mechanical Engineering and BA in Physics, 1995), and advanced degrees from MIT (MS 1997, PhD 2002 in Mechanical Engineering). His research focuses on control engineering, mechatronics, robotics, and sensor systems. Notable contributions include fingernail imaging for tactile force sensing, robotic tendon modeling, and biomimetic actuators. He has secured grants such as the NRI-Small grant for grasp force research. His work bridges robotics, biomedical engineering, and haptics, with applications in surgical robotics, human-robot interaction, and sensor development. Mascaro teaches courses in Mechatronics and System Dynamics, emphasizing hands-on learning. He actively mentors FIRST Robotics teams and engages in community outreach, including mentoring high school robotics competitions. His awards include the 2024 Top 15% Instructor Award from the University of Utah. His lab develops innovative sensors and robotic systems, integrating principles from biomechanics and materials science. Current projects include real-time tactile sensing via deep learning and robotic tendon repair simulation. His work is published in IEEE Transactions, Journal of Dynamic Systems, and other leading journals, with over 40 peer-reviewed articles since 1998.

• Visual Perception
• Cognitive Neuroscience
• Computer Vision
• +3 more

Richard Murray is a Full Professor in the Department of Biology at the Faculty of Science. His research focuses on visual perception, particularly lightness constancy, and explores how humans and AI models perceive lightness in varied environments such as virtual reality (VR), flat-panel displays, and real-world settings. He investigates the interplay between natural lighting cues, rendering artifacts, and perceptual mechanisms, employing deep learning models and psychophysical experiments. His work bridges computer vision and neuroscience, analyzing mid-level lightness illusions, intrinsic image decomposition, and decision spaces in complex scenes. Murray has developed novel visualization techniques like the 'noise prism' and contributed to VR display calibration methodologies. His research often addresses discrepancies between human perception and computational models, emphasizing the limitations of current AI in replicating human visual constancy. No scientific awards or grants are explicitly listed in the provided information. His advising activities and student collaborations are not detailed here. Laboratory or team affiliations are not specified, though his work suggests involvement with multidisciplinary teams in vision science and computational modeling.