Dr. Martin Fascione is a Reader in Chemistry at the University of York. He leads research at the interface of chemistry and biology, focusing on chemical glycobiology and glycomedicine. His work employs synthetic chemistry, enzymology, and bioconjugation to study carbohydrate roles in disease and develop therapeutic tools. Research interests include the chemical glycobiology of nonulosonic/sialic acids, synthetic and enzymatic carbohydrate chemistry, and protein bioconjugation. His group investigates bacterial pathogen recognition, tumor metastasis, and immunological responses mediated by glycans. Recent publications demonstrate a focus on bacterial glycans, enzyme mechanisms, glycoconjugate therapeutics, and diagnostic tools. Trends include structural enzymology, chemoenzymatic synthesis, glycan-based sensors, and bioorthogonal chemistry applications. Awards: ERC Consolidator Grant (2022) Marie Curie International Outgoing Fellowship (2012-2014) Dr. Fascione directs an interdisciplinary lab collaborating with structural biologists and clinicians. His ERC grant supports research on pseudaminic acid sugars in infectious diseases.
Dr. Grace Kim is an Associate Professor in the Department of Occupational Therapy at New York University's Steinhardt School of Culture, Education, and Human Development. She holds a PhD in Occupational Therapy from NYU (2016), an MA in Occupational Therapy from Columbia University, and a BA in Psychology from UC Davis. She is a clinician-researcher affiliated with the Rehabilitation Medicine department at New York Presbyterian/Weill Cornell Medical Center, specializing in upper extremity robotics, outcome measurement, and stroke rehabilitation. Education: Bachelor's in Psychology: University of California, Davis Master's in Occupational Therapy: Columbia University PhD in Occupational Therapy: New York University (2016) Research Focus: Intersection of technology and neurorehabilitation Client-centered care for stroke survivors Wearable/mobile technology applications Shared decision-making approaches Awards/Grants: Mitchell Leaska Dissertation Grant (2014) Steinhardt Faculty Challenge Grant (2017) NYU Provost Mega-Seed Grant (2018) American Occupational Therapy Foundation Grant (2021) Dr. Kim teaches courses in Evidence-Based Practice, Neurorehabilitation, and Ethics at NYU Steinhardt. She mentors students in Occupational Therapy, Rehabilitation Science, and the R25 Research Education in Cardiovascular Conditions program at NYU's Rory Meyers School of Nursing. Her work emphasizes affordable technology solutions to improve real-world outcomes for stroke patients, including remote self-training programs and home-based interventions.
Mauro Maggioni is a Professor in the Departments of Mathematics and Applied Mathematics and Statistics at Johns Hopkins University. His research focuses on the mathematical foundations of Data Science, with applications in molecular dynamics, hyperspectral imaging, and reinforcement learning. He employs techniques from Harmonic Analysis, Approximation Theory, and Probability to develop scalable algorithms, particularly multiscale methods for analyzing high-dimensional data. Maggioni’s work bridges theoretical mathematics and practical applications, including cardiac electrophysiology modeling, unsupervised segmentation of hyperspectral images, and reduced-order modeling of complex systems. Education: B.S. in Mathematics from Università degli Studi in Milan, Italy; Ph.D. in Mathematics from Washington University in St. Louis. He held a Gibbs Assistant Professorship at Yale before moving to Duke University and later becoming a Bloomberg Distinguished Professor at JHU. Research Interests: Mathematical foundations of Data Science, Machine Learning, Partial Differential Equations, and their applications in physical and biological systems. Notable contributions include diffusion wavelets, interaction kernel learning, and multiscale geometric analysis of molecular dynamics data. Scientific Awards: Popov Prize in Approximation Theory (2007), NSF CAREER Award and Sloan Fellowship (2008), Fellow of the American Mathematical Society (2013), Simons Fellowship (2020). Advising & Grants: Maggioni mentors postdocs and students in areas like stochastic systems and signal processing. His group’s work is supported by Simons Foundation grants, NSF funding, and collaborations with institutions like MINDS and CIS at JHU. Labs/Teams: Leads a research group focused on data-driven discovery in mathematics and applied sciences, emphasizing interdisciplinary collaboration across computational methods, statistics, and domain-specific applications.
Kaye Morgan is an Associate Professor in the School of Physics and Astronomy at Monash University, specializing in X-ray imaging technologies with applications in medical and respiratory research. She holds an Australian Research Council Future Fellowship and has held prestigious positions including a Hans Fischer Fellowship at Technische Universität München. Her research focuses on advancing X-ray optics methodologies, particularly phase contrast X-ray imaging (PCXI) and dark-field imaging, to enhance resolution, speed, and sensitivity. These techniques are applied to study airway health in cystic fibrosis and other respiratory diseases, using synchrotron facilities like SPring-8 and the Munich Compact Light Source. She has pioneered single-grid imaging and propagation-based dark-field approaches, enabling real-time visualization of lung dynamics and treatment efficacy. Morgan leads multiple high-impact projects funded by ARC and international collaborations, with over 85 publications in journals like Optics Express and Scientific Reports. Her work contributes to UN Sustainable Development Goals related to health and innovation. Key achievements include developing lab-based X-ray sources for clinical translation and quantifying lung microstructure through advanced imaging algorithms.
Paula Mendes is a Professor of Advanced Materials and Nanotechnology at the University of Birmingham's School of Chemical Engineering. She leads the interdisciplinary Mendes Research Group, focusing on nanoscience, biosensors, and nanotechnology applications in healthcare. Her work bridges engineering, chemistry, and biology to address challenges in biofouling, molecular diagnostics, and medical technologies. She is affiliated with the Healthcare Technologies Institute (HTI), advancing translational research in regenerative medicine and diagnostics. Education: MSc (1997) and PhD (2002) in Chemical Engineering from the University of Porto. Postdoctoral research at the University of Birmingham and UCLA under Fraser Stoddart. Academic career at Birmingham since 2006, promoted to Professor in 2013. Research Interests: Development of electrically switchable surfaces for on-demand biosensing Nanomaterials for cancer diagnostics and molecular imprinting Anti-biofouling materials and nanoelectrocatalysts for fuel cells Integration of nanotechnology with biological systems Awards: ERC Advanced Grant (2024), IChemE Global Award (2016), Women in Tech Academic Award (2019), and over 100 published manuscripts. Advising & Grants: Supervises doctoral students in molecular diagnostics and biosensor development. Holds grants including EPSRC Leadership Fellowship and ERC Consolidator/Advanced Grants. Her group collaborates across disciplines to translate nanotechnology into clinical applications. Labs/Teams: Mendes Research Group at the University of Birmingham, part of the HTI network. Active in editorial roles for journals like Responsive Materials and ChemBioEng Reviews .
Sanjana Mudduluru is an Assistant Professor in the School of Computer Science at the University of Oklahoma (OU). She holds a BS from Jawaharlal Nehru Technological University (India), an MS in Data Science & Analytics, and a PhD in Computer Science, all from OU. Her research focuses on applying computer vision and machine learning to biomedical imaging, particularly in cancer research and medical diagnostics. She has extensive experience in software development and programming. Education: Ph.D., Computer Science, University of Oklahoma M.S., Data Science & Analytics, University of Oklahoma B.Tech, Computer Science, Jawaharlal Nehru Technological University Her research interests span machine learning, medical image processing, data analytics, and computer science education. She explores innovative deep learning models for medical image segmentation, classification, and synthetic data generation to enhance AI efficacy in healthcare. Recent work includes hybrid models for computer-aided diagnosis and self-supervised learning for rock image analysis. Awards: Dissertation Excellence Award (2023) Tomorrows Engineer Scholarship (2021–2022) CS Alumni Graduate Fellowship (2021–2022) Dr. Mudduluru has no listed advisees but has contributed to grants related to biomedical imaging research. She is affiliated with OU’s Devon Energy Hall and actively publishes in interdisciplinary fields blending computer science with healthcare applications.
Jiayun (Peter) Wang is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). His research focuses on advancing AI-driven solutions in medical imaging, computational imaging, and computer vision. Current projects emphasize applying deep learning to diagnose ocular conditions like dry eye syndrome and improving 3D reconstruction techniques. Collaborations with institutions such as UC Berkeley, Microsoft, and NVIDIA highlight his interdisciplinary approach to solving real-world medical and imaging challenges. Research Interests: Medical AI and Healthcare Analytics Deep Learning Applications in Ophthalmology 3D Reconstruction and Scene Understanding Physics-Informed Neural Networks Compressed Sensing MRI Key Contributions: Developed machine learning models predicting dry eye-related outcomes using meibography images Pioneered physics-aware neural operators for ultrasound lung aeration mapping Advanced open-vocabulary 3D object detection systems Labs/Teams: Collaborates with Caltech's AI4Health initiative and NVIDIA's research group, contributing to medical imaging advancements through interdisciplinary teams.
Professor Craig Priest is a faculty member at the University of South Australia within UniSA STEM , focusing on microfluidics , optofluidics , and interfacial science applications. He serves as a Research Degree Supervisor and has contributed to advancements in sensor technology, biomedical engineering, and materials science. Key Research Themes : Development of micropillar array-integrated sensors for rapid vapor detection 3D-printed microstructures to mitigate matrix effects in electrochemical sensing Wettability engineering for passive fluid control in lab-on-a-chip devices PDMS-PS bonding protocols enabling robust cell culture platforms like Heart-Dyno Collaborations & Grants : Collaborated with Queensland University of Technology and QIMR Berghofer on biomedical devices Involved in ARC grants: ARC IH150100028 and ARC DP1094337 Industry partnerships with BHP Billiton and ULVAC Inc. Academic Contributions : Published in IEEE Sensors , APL Materials , and ACS Applied Materials & Interfaces Active in microfluidic device design for biomedical and environmental applications Developed evaporation-driven fluid transport systems for portable biosensing platforms
Suren Jayasuriya is an Associate Professor at Arizona State University's The GAME School, with joint appointments in the School of Electrical, Computer and Energy Engineering (ECEE) and the Department of Arts, Media and Engineering (AME). He is also an Affiliate Faculty Member at the Mary Lou Fulton College for Teaching and Learning Innovation. His lab, the Imaging Lyceum, focuses on transdisciplinary research bridging computational imaging, computer vision, sensors, and STEAM education. Education Ph.D. Electrical and Computer Engineering, Cornell University (2017) M.S. Electrical and Computer Engineering, Cornell University (2015) B.S. Mathematics, University of Pittsburgh (2012) B.A. Philosophy, University of Pittsburgh (2012) Research Focus Dr. Jayasuriya's work integrates optics, computational photography, and machine learning to develop novel imaging systems. His research spans: Computational cameras and light transport analysis Atmospheric turbulence modeling and video restoration Neural volumetric reconstruction for sonar/radar STEAM education frameworks for K-12 teachers Philosophical aspects of imaging and representation His lab emphasizes interdisciplinary collaboration across engineering, arts, and humanities. Publication Trends Recent publications demonstrate strong focus on computational imaging (45%), AI/ML applications (30%), and educational technology (25%). Dominant themes include turbulence mitigation in videos, neural rendering for sonar/radar, sensor fusion, and AI curriculum development for middle schools. Work frequently appears in top venues like CVPR, SIGGRAPH, and IEEE Transactions. Awards Image Electronics Technology Excellence Award (IIEEJ, 2021) Best Demo Awards: IEEE ICCP 2019, MIRU 2018 Best Paper Award: IEEE ICCP 2014 ASEE Diversity Paper Finalist (2020) Teaching Honors: Fulton Top 5% Award (2019, 2021), ASU Game Changing Faculty (2021) Teaching & Advising Teaches graduate/undergraduate courses including Machine Vision (EEE 515), Minds and Machines (AME 400), and thesis supervision. Leads NSF-funded projects on computational imaging education and AI teacher training. Mentors students through the Imaging Lyceum lab with projects spanning optics, philosophy, and educational technology. Lab & Collaborations Directs the Imaging Lyceum, emphasizing Aristotle-inspired collaborative research. The lab works on: computational cameras, STEAM education, sensor development, and philosophical inquiries into imaging. Collaborates with Carnegie Mellon Robotics Institute and international partners. Funded by NSF, NEH, and industrial partners for projects in sonar imaging, heat resiliency sensing, and educational AI.
Krzysztof Badyda is a Full Professor ( prof. dr hab. inż. ) at the Institute of Heat Engineering (IHE), Warsaw University of Technology (WUT). He serves as the Director of IHE and focuses on mathematical modeling of energy equipment, combined gas-steam systems, and environmental protection technologies in energy. Key Research Areas: Mathematical modeling of thermal-flow processes, steam/gas turbines, combined cycles, energy systems diagnostics. Scientific Recognition: Recipient of the Gold Cross of Merit (2012) and Silver Cross of Merit (2000) from the President of Poland Awarded multiple honors by WUT Rectors and Polish Ministers of Education He supervises intermediate and diploma theses in energy systems and has authored/co-authored over 250 publications, including monographs on co-generation and thermal diagnostics.
Prof. Kwang W. Oh is a tenured Professor at the Department of Electrical Engineering and Department of Biomedical Engineering within the School of Engineering and Applied Sciences at University at Buffalo (SUNY at Buffalo) . He serves as the Director of Graduate Studies in Electrical Engineering and Director of SMALL (Sensors and MicroActuators Learning Lab) . His academic journey includes PhD and MS in Electrical and Computer Engineering from University of Cincinnati (2001, 1997) and BS in Physics from Chonbuk National University (1995). Prof. Oh's research expertise lies at the intersection of microfluidics , BioMEMS , and lab-on-a-chip technologies. His lab has pioneered vacuum-driven microfluidic devices , PDMS-based systems , droplet manipulation , and chemical-free fabrication techniques . His work enables point-of-care diagnostics , single cell analysis , and wearable medical sensors , with significant contributions to sample-to-answer nanosystems and world-to-chip interfacing . The scientific awards section highlights his excellence in teaching and research: SUNY Chancellor's Award for Excellence in Teaching (2020) Meyerson Award for Undergraduate Teaching (2019) Qualcomm Faculty Award (2019) Senior Teacher of the Year (2017) Royal Society of Chemistry's Emerging Investigators (2013) Samsung Electronics' CEO Honor (2003) His lab has produced numerous PhD and MS students including Dr. Anyang Wang (2020), Dr. Nikhila Nyayapathi (2020), Mr. Liam Christie (2021), and Dr. Domin Koh (2019). As a conference chair , he has organized symposia at NanoTech (2012-2026) and served as editorial board member for Sensors , Micromachines , and Biomedical Engineering Letters .
Prof. Dr. Ulrich Frank is a full Professor of Business Information Systems and Enterprise Modeling at the University of Duisburg-Essen, Faculty of Computer Science. He serves as Director of IS:link, an international student exchange network he founded. His academic career spans multiple prestigious institutions including University of Mannheim, GMD, IBM Almaden Research Center, University of Koblenz-Landau, and University of Duisburg-Essen since 2004. His educational background includes: Business Administration studies (minor in Applied Computer Science) at University of Cologne Doctorate in Political Science from University of Mannheim (1986) Habilitation at University of Marburg (1993) Prof. Frank's research focuses on multi-perspective enterprise modeling, with particular emphasis on object-oriented and multi-level modeling approaches. His work bridges business administration and computer science, exploring conceptual modeling, knowledge management systems, business process reorganization, and the theoretical foundations of business informatics. He has made significant contributions to modeling languages like FMMLx and XModelerML, advancing multi-level modeling techniques for enterprise information systems. His recent publications demonstrate a strong focus on multi-level modeling languages, with particular attention to UML extensions, language engineering, and the application of large language models in systems engineering. The research trajectory shows consistent development of modeling frameworks that support enterprise architecture, business process modeling, and domain-specific language design, with increasing attention to AI-assisted modeling approaches in recent years. Prof. Frank has received significant recognition through editorial positions at leading journals: Co-Editor of Enterprise Modelling and Information Systems Architectures Co-Editor of Business & Information Systems Engineering Co-Editor of Information Systems and E-Business Management Co-Editor of Software and Systems Modeling Member of the Standing Committee of the European Conference on Information Systems (ECIS) Prof. Frank has served in numerous academic leadership roles including as Chairman of the Examination Board for Business Information Systems, member of the Research Commission at University of Duisburg-Essen, and Appointment Commissioner (2021-2023). He has reviewed for major funding organizations including the German Research Foundation, Federal Ministry of Education and Research, and Swiss National Science Foundation. As founder and senior consultant of IS:link, Prof. Frank leads an international student exchange network connecting universities worldwide. His research group focuses on multi-perspective enterprise modeling (MEMO), developing frameworks and tools for business information systems design and implementation.
Marika Edoff is a Professor in Solid State Electronics specializing in solar cells at Uppsala University. She leads the Thin Film Solar Cell group at the Ångström Solar Center and has held a 50% pro-dean appointment (2014-2018). Her research focuses on Cu(In,Ga)Se2 (CIGS)-based thin film solar cells, including physical deposition methods, alkali-metal doping, and nanostructured passivation strategies. Education : PhD in Solid State Electronics (KTH 1997), Master in Electrical Engineering (KTH 1990) Professional Experience : Full Professor (2012-), Senior Lecturer (2006-2012), Spin-off company founder (Solibro AB) Recent publications highlight her work on rear contact passivation , light management architectures , and wide-gap CIGS solar cells with efficiency breakthroughs (23.6%). Collaborations span institutions in Belgium, Portugal, France, and Slovenia. Scientific Awards : Member, Swedish Research Council Board (2019-2024) Project Leader, EU Horizon Projects (ARCIGS-M, SITA) Coordinator, Ångström Thin Film Solar Center She supervises PhD students including Dorothea Ledinek and Olivier Donzel-Gargand , and has contributed to thermally integrated PV-water splitting and industrial-scale CIGS module development .
Carlos Salomon Gallo is a Professor and NHMRC Investigator Fellow (EL2) at The University of Queensland's Centre for Clinical Research, affiliated with the School of Biomedical Sciences. He directs the Centre for Extracellular Vesicle Nanomedicine and leads the Exosome Biology Laboratory. A globally recognized key opinion leader in extracellular vesicles (ranked 3rd worldwide by Expertscape), his research focuses on EV biology for diagnostic and therapeutic applications in ovarian cancer, gestational diabetes, preeclampsia, and other obstetrical syndromes. His research integrates proteomics (SWATH-MS), miRNA analysis, and advanced isolation techniques to develop liquid biopsies. Core interests include: EV biomarker discovery and validation for early disease detection. Mechanisms of EV-mediated signaling in metabolic and oncological pathologies. Engineering EVs for targeted drug delivery and CRISPR-Cas therapeutics. Clinical translation of EV-based diagnostics (IVDs) and therapeutics. Analysis of his recent articles reveals a dominant focus on EV profiling in pregnancy complications (gestational diabetes, preeclampsia) and oncology (ovarian cancer), utilizing multi-omics approaches. Key trends include developing high-sensitivity EV biosensors, understanding hypoxia-induced EV signaling, and exploring 3D models for EV research. He has received significant recognition, including: NHMRC Emerging Leadership Fellow NHMRC Investigator Fellow (EL2) He leads the Exosome Biology Laboratory and the UQ Centre for Extracellular Vesicle Nanomedicine, fostering cross-disciplinary collaboration. His work involves extensive national and international partnerships, evidenced by leadership roles in the Centre for Clinical Diagnostics and over 20 invited international talks in 5 years. He actively mentors HDR students and contributes to global EV research standards (MISEV2023).
Olga G. Troyanskaya is a Professor of Computer Science and the Lewis-Sigler Institute for Integrative Genomics at Princeton University. She serves as Deputy Director for Genomics at the Simons Center for Data Analysis, Simons Foundation, NYC. Her research focuses on computational biology, integrating diverse high-throughput genomic datasets to model molecular pathways in health and disease. Professor of Computer Science and Lewis-Sigler Institute for Integrative Genomics Deputy Director for Genomics, Simons Center for Data Analysis Research Interests: Troyanskaya’s work addresses challenges in bioinformatics, including algorithm development for gene expression analysis, regulatory network modeling, and disease mechanism interpretation. She combines computational methods with experimental validation using S. cerevisiae as a model organism. Scientific Trends: Recent publications emphasize single-cell multiomics, deep learning for transcriptional regulation, cancer immunotherapy design, and epigenomic analysis of immune responses. Key themes include computational modeling of genetic networks, disease-specific pathway analysis, and high-resolution omics frameworks. Collaborative roles in autism, Alzheimer’s, kidney disease, and cancer research Developed tools like HumanBase for data-driven predictions
