Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.
Dr. Karl Bertling is a Senior Lecturer in the School of Electrical Engineering and Computer Science at The University of Queensland (UQ). His research focuses on pioneering imaging and sensing techniques using laser feedback interferometry (LFI), particularly with terahertz quantum cascade lasers (QCLs). Key areas include early melanoma detection, agricultural photonics, and near-field terahertz imaging of nanomaterials. He holds a PhD in Engineering from UQ (2012) and has authored over 140 publications in journals like Optics Express and IEEE Transactions . His work spans diverse applications: from biomedical imaging to cultural heritage preservation, leveraging LFI for non-destructive analysis. Collaborations include projects with institutions like the Queensland Brain Institute and industry partners. Bertling’s expertise bridges materials science, photonics, and quantum technologies, with contributions to THz nanoscopy and quantum device characterization. Research interests include: Terahertz QCL-based imaging and sensing Biomedical applications: skin pathologies and cancer detection Agricultural monitoring via terahertz hydration sensing Nanostructure analysis using THz nanoscopy Grants and funding: Multiple Australian Research Council (ARC) grants and industry partnerships support his work. Ongoing projects explore THz photonics for precision agriculture and quantum material characterization.
Associate Professor Jungsoo Kim holds a position in the School of Architecture, Design and Planning at the University of Sydney, specializing in Building Science. His research focuses on occupant-building interactions, particularly how environmental factors influence user behavior and energy demand. He teaches courses in architectural science and building performance. Key affiliations include membership in: NatHERS Technical Advisory Committee CSIRO's Thermostat Behavior Expert Group IEA-EBC Annexes 87, 69, and 66 NABERS Technical Working Group International Society of Indoor Air Quality and Climate Research interests span Indoor Environmental Quality (IEQ), occupant behavior modeling, building performance assessment, and translating research into building codes. Recent grants include studies on decarbonizing multi-residential buildings and work-from-home environments' impact on productivity. His lab, the IEQ Lab, explores acoustic comfort and thermal adaptation in workplaces and residential contexts. Notable work includes developing probabilistic behavioral models for HVAC usage and advancing adaptive thermal comfort theory.
David J. Reinkensmeyer is a Professor at the University of California, Irvine (UCI), holding appointments in the Department of Mechanical & Aerospace Engineering (The Henry Samueli School of Engineering), Anatomy & Neurobiology (School of Medicine), and Biomedical Engineering. His research focuses on neurorehabilitation engineering, developing robotic and sensor-based technologies to enhance motor recovery after neurological injuries such as stroke and spinal cord injury. He leads interdisciplinary efforts in robotic therapy, sensor design for movement assessment, and computational models of motor learning. Key areas include: Design of robotic devices for upper/lower extremity rehabilitation Development of wearable sensors to monitor home exercise programs Studying motor adaptation and proprioception in clinical populations Optimizing neurorehabilitation interventions through computational modeling His work integrates biomechanics, machine learning, and clinical neuroscience to create practical solutions for disabling movement disorders. Recent projects explore scalable mRehab systems, data-driven diagnostics, and real-time feedback technologies. Funding sources include NIH grants (e.g., R01 HD062744) and industry collaborations. Over 200 peer-reviewed publications and numerous patents reflect his impact in translating engineering innovations into clinical practice.
Frank E. Talke is the CMRR Endowed Chair Professor in the Department of Mechanical and Aerospace Engineering at UC San Diego. His research focuses on medical device technology and information storage systems. He has contributed to advancements in hard disk drive tribology, thermal flying height control, and biomedical innovations like intraocular pressure sensors and 3D-printed endoscopes. Talke holds over 350 publications and 11 patents, with honors including the ASME Medal, Tribology Gold Medal, and membership in the National Academy of Engineering. Education: Diplom-Ingenieur (1965, University of Stuttgart), M.S. and Ph.D. in Mechanical Engineering (1966, 1968, UC Berkeley), honorary doctorate from Technical University of Munich (2005). Research interests span interdisciplinary fields combining mechanical engineering, materials science, and precision instrumentation. Current projects include medical device development (e.g., biofilm-resistant catheters, detachable bronchoscopes) and information storage tribology. His work emphasizes translational applications in both engineering and healthcare sectors. Key Awards: ASME Medal (2008), Tribology Gold Medal (2010), Honorary ASME Membership (2018). Grants and Funding: Extensive industry and academic collaborations in disk drive technology and biomedical engineering. Labs/Teams: Leads the Center for Memory and Recording Research (CMRR), fostering interdisciplinary research in data storage and medical devices.
Jan Olav Høgetveit is an Associate Professor in the Department of Physics at the University of Oslo (UiO), within the Faculty of Mathematics and Natural Sciences. He also serves as Head of Research & Development in the Department of Biomedical and Clinical Engineering at Rikshospitalet, Norway’s national hospital. His work bridges physics and clinical practice, focusing on medical instrumentation. Education: Bachelor of Electronic Engineering (Technical Cybernetics), Oslo University College, 1993 Master of Electronics, University of Oslo (Department of Physics), 1997 Ph.D. in Physics (Technology Applications for Medical Devices), University of Oslo, 2008 Research Interests: Høgetveit specializes in biomedical instrumentation and clinical engineering, particularly in surgical technology and wireless communication impacts on medical devices. His work addresses challenges like real-time physiological monitoring during heart-lung machine use, non-invasive blood glucose detection, and bioimpedance-based viability assessment of organs. He emphasizes interdisciplinary collaboration between engineering and medicine to enhance patient safety and surgical outcomes. Scientific Contributions: His research trends span bioimpedance applications in ischemia/reperfusion injury, machine learning for surgical decision support, and electrosurgery safety. He has explored ventilator optimization during pandemics and implant-related thermal risks. Contributions highlight both hardware development (e.g., optically isolated current sources) and software innovations (e.g., neural networks for viability prediction). Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: Høgetveit received a 1998–2001 research council scholarship. As Head of R&D since 2001, he oversees translational projects. No formal advisees/students listed, though he collaborates extensively with teams on device development and clinical trials. Labs & Teams: Affiliated with UiO’s Department of Physics and Rikshospitalet’s Biomedical and Clinical Engineering department. Active in the Electronics research group at UiO. Engages with multidisciplinary teams addressing surgical instrumentation and physiological monitoring challenges.
Dr. Sundaresan Jayaraman is a Professor at the School of Materials Science and Engineering, Georgia Institute of Technology, and Founding Director of the Kolon Center for Lifestyle Innovation. His research focuses on converging textiles with computing, notably pioneering the concept of 'Fabric is the Computer.' Key contributions include the Smart Shirt (Wearable Motherboard™), featured in LIFE Magazine and archived at the Smithsonian. He has secured $16M+ in research funding from NSF, DARPA, and industry. His work spans smart textiles, respiratory protection systems, and computer-aided manufacturing. Awards include the 1989 Presidential Young Investigator Award and the 2018 Textile Institute Research Publication Award. He holds ten U.S. patents and serves on editorial and advisory boards for journals like the Journal of the Textile Institute. Professional roles include leadership in National Academies committees on manufacturing and personal protective equipment. Education & Early Career: Dr. Jayaraman’s career began at Software Arts, Inc. (developers of VisiCalc) and Lotus Development Corporation, where he contributed to early spreadsheet and equation-solving software. His PhD research led to TK!Solver, a pioneering equation-solving program. Research Interests: His work bridges engineering and healthcare through smart textiles, wearable biomedical systems, and advanced manufacturing. Current projects address respiratory protection systems, wearable sensor networks, and personalized healthcare technologies. He emphasizes interdisciplinary collaboration to address societal challenges in health, security, and quality of life. Publications & Impact: Over 100 refereed papers and book chapters highlight his contributions to textile informatics, healthcare wearables, and manufacturing automation. Recent articles focus on next-generation respiratory protection devices and continuous fit monitoring systems. Past innovations include the Wearable Motherboard™ and sensor-integrated garments for vital signs monitoring. Awards & Recognition: In addition to his NSF and Textile Institute honors, he received the Georgia Technology Research Leader Award (2000) and Distinguished Alumni Award from A.C. College of Technology (2019). He is a Fellow of the Textile Institute and founding member of IEEE Technical Committees on Biomedical Wearables. Labs & Teams: Leads the Kolon Center for Lifestyle Innovation and collaborates with industry partners on textile-based computing solutions. His lab’s work on 3D-printed respiratory devices and smart garments exemplifies cutting-edge translational research.
Azhar Zam is an Associate Professor of Bioengineering at NYU Abu Dhabi (NYUAD) and associated faculty at NYU Tandon School of Engineering's Biomedical and Electrical Engineering departments. He holds a B.Sc. from University of Indonesia, M.Sc. from University of Luebeck (Germany), and Ph.D. from Friedrich-Alexander-University Erlangen-Nuremberg (Germany). His research focuses on developing smart optical devices for medical imaging/diagnostics, including laser surgery, OCT, photoacoustics, and AI-driven imaging systems. He leads the Laboratory for Advanced Bio-Photonics and Imaging (LAB-π) at NYUAD and has authored 85+ publications/patents. Education: Bachelor of Science, University of Indonesia M.Sc. Biomedical Engineering, University of Luebeck Ph.D. Engineering, Friedrich-Alexander-University Erlangen-Nuremberg Research Interests: Innovations in biomedical optics, optical-based smart sensors, AI-enhanced diagnostics, and miniaturized medical imaging systems. His work integrates advanced optical technologies with surgical robotics and clinical applications. Professional Contributions: Associate Editor for Frontiers in Photonics Biophotonics section; Reviews Editor for Frontiers in Ophthalmology Retina section. Previously held positions at University of Basel (Assistant Professor), University of Waterloo, and other institutions globally. Labs & Teams: Directs NYUAD's LAB-π lab focusing on bio-photonics innovations. Collaborates across NYU's global network and international partners.
Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.
Professor Peter Chin is a Professor of Engineering at Dartmouth College and Director of the Learning, Intelligence + Signal Processing (LISP) Lab. He holds affiliations with the Thayer School of Engineering and serves as Associate Editor of IEEE Transactions on Computational Social Systems. His research bridges signal processing, machine learning, game theory, and differential geometry, with applications in cybersecurity, healthcare, and network analysis. Education: Bachelor of Science in Electrical Engineering, Computer Science, and Mathematics from Duke University (1993) Doctor of Philosophy in Mathematics from MIT (1998) Research Interests: Chin’s work focuses on fundamental questions at the intersection of machine learning, game theory, and signal processing. His lab explores topics like adversarial defense mechanisms, topological machine learning, and computational neuroscience. Recent projects include cybersecurity resilience modeling, medical imaging enhancements via GANs, and multi-agent reinforcement learning frameworks. Publications Trends: His most recent articles address cutting-edge challenges in cybersecurity (e.g., autonomous defense systems), medical AI (e.g., Alzheimer’s classification), and adversarial robustness. A notable 2025 focus is on quantitative resilience modeling for cyber defense, reflecting growing demand for AI-driven security solutions. Awards: Faculty Scholar Award, Duke University George Sherred III Award, Duke University Julia Dale Memorial Award, Duke University Grants & Leadership: Recipient of DARPA cybersecurity research grants Co-chair for SPIE/DSS Cyber Sensing Conference (2013–2020) Developed novel compressive sensing microscope for biological imaging LISP Lab: This interdisciplinary lab pioneers projects like nFlip (multiplayer security game models) and topological machine learning frameworks, emphasizing practical applications of theoretical advancements.
Sergio Barbero is an Associate Researcher at the Visual Optics laboratory of the Instituto de Óptica (CSIC), Spain, under the supervision of Prof. Susana Marcos. He holds a BSc in Physics from the University of Zaragoza (1999) and a PhD in Visual Sciences from the University of Valladolid (2004), which earned him the Doctoral Thesis Extraordinary Award (2005). His research focuses on optical aberrations, intraocular lens design, wavefront measurement techniques, and gradient-index modeling of ocular structures. Barbero has collaborated with international groups at Indiana University (USA), University of Houston (USA), and Australian institutions. His work includes pioneering studies on crystalline lens tomography, corneal ablation algorithms, and novel wavefront sensing methods. He has authored 16 peer-reviewed publications and contributed to a US patent on wavefront reconstruction techniques. His research spans three core areas: (1) intraocular lens design using analytical tools, (2) gradient-index modeling of the human eye, and (3) in vivo measurement of crystalline lens aberrations. He has secured grants from the Spanish government (I3P-CSIC), NIH (USA), and Fulbright fellowships. Barbero has presented 33 scientific talks/posters, including invited lectures, and maintains an h-index of 9. His work bridges fundamental optics with clinical applications in ophthalmology.
Paola Ayala is a Professor at the Faculty of Physics of the University of Vienna, specializing in the Electronic Properties of Materials . Her research focuses on nanomaterials, particularly carbon nanotubes, graphene, and carbyne, exploring their electronic, magnetic, and optical properties. She leads the Doctoral College Advanced Functional Materials (DCAFM) (2020–2025), fostering interdisciplinary training in nanotechnology. Key research areas include nitrogen doping of carbon nanotubes, magnetic coupling in nanoclusters, and sensor applications of nanocomposites. She has pioneered studies on confined carbyne synthesis and the environmental stability of 1D nanocarbons. Ayala’s work bridges theoretical modeling (e.g., DFT simulations) and experimental techniques like Raman spectroscopy and XPS analysis. Her 2017 Matilde Hidalgo Prize recognizes contributions to nanomaterials science. She actively promotes STEM equity, co-authoring reports on women in physics in Austria and Ecuador. Ayala has supervised over 97 publications since 2007, with recent emphasis on functional nanomaterials for energy, sensing, and biomedical applications. Notable projects include developing flexible formaldehyde sensors and investigating magnetic properties of iron nanoclusters. She collaborates globally, presenting at conferences like the 2024 UNIVIE NanoteC Symposium and the 2023 International Nanotechnology Congress.
Dr. William Zamboni is a Professor at the UNC Eshelman School of Pharmacy and Director of the UNC Advanced Translational Pharmacology and Analytical Chemistry (ATPAC) Lab. His research focuses on translational pharmacology, optimizing anticancer therapies through pharmacokinetics, pharmacodynamics, and precision medicine. Key areas include nanoparticle drug delivery, overcoming tumor delivery barriers, and immune system interactions with nanomedicines. He collaborates with institutions like the UNC Lineberger Comprehensive Cancer Center and Carolina Institute of Nanomedicine. His lab specializes in analytical methods for drug quantification and preclinical/clinical studies of liposomal agents, antibodies, and ADCs. Research highlights include developing solid-phase separation (SPS) for nanoparticle analysis, evaluating mononuclear phagocyte system (MPS) biomarkers, and optimizing drug regimens for special populations (e.g., obesity, inflammatory diseases). The ATPAC Lab provides bioanalytical services, including LC-MS/MS assays and PK/PD modeling. Dr. Zamboni’s work emphasizes bridging preclinical findings to clinical applications, with a focus on enhancing anticancer drug efficacy and reducing toxicity.
Emanuele (Manuel) Trucco is a Professor of Computing and holds the NRP Chair of Computational Vision in the School of Science and Engineering at the University of Dundee. He is also an Honorary Clinical Researcher at NHS Tayside and previously served as an Adjunct Professor at the Chinese Academy of Sciences (2018–2021). His research is centered on computational vision and medical image analysis, particularly in retinal imaging and its applications in systemic disease detection. PhD, Electronic Engineering, University of Genoa (1990) MSc, Electronic Engineering, University of Genoa (1984) Manuel Trucco's research focuses on computer vision and medical image analysis , with a strong emphasis on retinal image analysis for early detection of diseases such as diabetes, cardiovascular conditions, stroke, dementia, and neurodegenerative disorders. He co-directs the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina) initiative, a collaborative effort between the Universities of Dundee and Edinburgh. This platform enables automated, multi-modal analysis of retinal images and has been used in biomarker studies across the UK and internationally. His work integrates deep learning , artificial intelligence , and biomedical engineering to develop non-invasive, scalable diagnostic tools. Industrial collaborations include Canon Medical, OPTOS plc, NIDEK, and Epipole plc, while institutional partners include the Royal College of Ophthalmologists and the UK Biobank Eye and Vision Consortium. Recent publications highlight a strong trend in using AI and deep learning to extract clinical insights from retinal images, including predicting cardiovascular outcomes in diabetic patients, estimating biological age, and analyzing retinal vasculature changes under physiological stress. His work bridges computer science, ophthalmology, and public health, contributing to precision medicine and health equity. His scientific contributions have been recognized through fellowships: FRSA (Fellow of the Royal Society of Arts) FIAPR (Fellow of the International Association for Pattern Recognition) Trucco has led or co-led major research projects, including a £7M NIHR grant on precision medicine for diabetes (Dundee-Chennai), a £1.1M EPSRC grant on vascular dementia biomarkers (PI), the 3M-Euro ITN "REVAMMAD", and several PhD studentships sponsored by OPTOS, NIDEK, SINAPSE, and Toshiba. He has served on the organizing and program committees of major international conferences such as MICCAI and the European Conference on Computer Vision. He is a key member of the VAMPIRE research team and the UK Biobank Eye and Vision Consortium , contributing to large-scale data analysis efforts in vision and systemic disease. His work is at the forefront of AI-driven healthcare innovation, with real-world applications in early disease detection and personalized medicine.
Gordon Ramage is a Professor of Infection Prevention and Control at Glasgow Caledonian University's School of Health & Life Sciences. He holds a B.Sc. (Hons) in Medical Microbiology from Edinburgh University (1996) and a Ph.D. in Prosthetic Joint Infections from Queen's University Belfast (1999). After postdoctoral work in North America (2000-2003), he held academic positions at GCU and University of Glasgow Dental School before returning to GCU in October 2023. Education: B.Sc. (1996), Ph.D. (1999) Academic Roles: Lecturer (2004), Senior Lecturer (2007), Professor (2012) His research focuses on biofilm infections , particularly Candida auris persistence in hospitals, antifungal resistance , and biofilm disruption strategies like phage therapy. Recent projects address dry surface biofilms, wound healing applications, and oral microbiome analysis. Research trends show sustained activity in biofilm pathogenesis (2001-2025) with 228 total outputs, including high-impact work on C. albicans (38%) and aspergillus (75%). Scientific Recognition: FRCPath (Royal College of Pathologists) FECMM (European Confederation of Medical Mycology) Chair, ESCMID Biofilms Study Group (2021-2025) Active in supervising students and leading grants like BIDOPT (Phage Therapy) and Assembly of Practical Evidence Base for C. auris . Affiliated with GCU's ReaCH group and SHIP research cluster.
