Professor Iwona M. Jasiuk is a multi-disciplinary academic affiliated with the University of Illinois, holding professorships in Mechanical Science and Engineering, Biomedical and Translational Sciences, Bioengineering, Aerospace Engineering, and other departments. She is also affiliated with the National Center for Supercomputing Applications (NCSA), Beckman Institute for Advanced Science and Technology, and the Carl R. Woese Institute for Genomic Biology. Her research focuses on composite materials, bio-inspired structures, additive manufacturing, and computational mechanics, with a strong emphasis on integrating artificial intelligence into materials science. Her work spans topics such as material characterization, metamaterials design, and radiation effects on materials. Notable research areas include thin-ply composites, lattice structures derived from geometric principles, and the mechanical properties of bio-inspired systems like equine hoof walls. She has pioneered the use of deep learning networks for predicting material behavior in complex systems. Professor Jasiuk has received prestigious awards, including the ASME Fellow, SES Fellow, and Vebleo Scientist Award. Her research is supported by collaborations across engineering, biology, and computational fields, leveraging advanced facilities like NCSA for high-performance computing.
Thom de Vries is an Associate Professor at the University of Groningen's Faculty of Economics and Business, based in the HRM & Organizational Behavior department. He also serves as Program Director for the Master of Science in Human Resource Management and holds a lecturer position in Industrial Engineering Management. His expertise focuses on organizational resilience, team boundary spanning, and infrastructure management. He holds a Ph.D. in Business Administration (cum laude) from the University of Groningen (2015), with prior experience as a Business Researcher at TNO and academic leadership roles in program committees. Education highlights include: Ph.D. in Business Administration (cum laude), University of Groningen (2015) Res. M.A. and M.A. in Business Administration (cum laude), University of Groningen (2011, 2009) B.A. in Public Administration, Thorbecke Academie (2007) Research interests emphasize team dynamics in complex environments, particularly: Resilience and adaptability in critical infrastructure organizations Boundary spanning across teams/organizations Design of multiteam systems for complex tasks Disruption management in supply chains Notable projects include the NGinfra-funded ConCorCom initiative studying coordination during infrastructure challenges, and NWO grants exploring resilience and decision-making under uncertainty. His work has earned awards like the Academy of Management Best Paper Award and multiple teaching recognitions. Grants include: NGINFRA/NWO: ConCorCom (Context, Coordination, Competencies) NWO VENI: Team Boundary Spanning in Disruptions NWO: Resilience-Efficiency Balance in Planning Teaching roles span disciplines including Organizational Behavior, Survey Research, and Experimental Design across faculties. He actively supervises research master students and contributes to executive education programs.
Sai Zhang is an Assistant Professor in the Department of Epidemiology at the University of Florida (UF), holding affiliations with the College of Public Health & Health Professions and College of Medicine. He is also an Affiliate Faculty in the J. Crayton Pruitt Family Department of Biomedical Engineering at the Herbert Wertheim College of Engineering. Previously, he was an Instructor at Stanford University School of Medicine and a Research Associate at the VA Palo Alto Epidemiology Research and Information Center (ERIC). Dr. Zhang completed his Ph.D. in Computer Science and Technology at Tsinghua University, followed by postdoctoral training in Dr. Michael Snyder’s lab at Stanford Genetics. His research integrates machine learning, genomics, and precision medicine to uncover genomic bases of complex diseases. Key focuses include developing algorithms for multiomic data analysis, modeling genotype-phenotype relationships, and leveraging deep learning for biological sequence analysis. His work emphasizes cell-type-specific mechanisms in diseases like ALS, coronary artery disease, and neurodegenerative disorders. Notable contributions include frameworks for polygenic risk scoring (e.g., PRS-Net), biomarker discovery for ALS, and tools for time-to-event prediction in neurological diseases. He leads the Zhang Laboratory, advancing computational systems for precision health applications.
Inna Fishman, Ph.D., is a Research Associate Professor at San Diego State University's Department of Psychology within the College of Sciences. Her research investigates brain network organization in autism spectrum disorder (ASD) using multimodal MRI techniques, focusing on developmental trajectories from toddlerhood to adulthood. She directs studies on sensory processing, socioeconomic influences, and neural connectivity patterns in ASD. Research Focus: Dr. Fishman's work bridges social neuroscience and clinical neuropsychology, examining: Early biomarkers of ASD via functional/diffusion MRI Impact of bilingualism and socioeconomic factors on neurodevelopment Sleep disorders and sensory sensitivities in autistic children Aging-related neural changes in adults with ASD Publication Trends: Her recent articles (2021-2025) emphasize: 1) Advanced neuroimaging of ASD across lifespan stages, 2) Machine learning applications for diagnostics, 3) Socioeconomic and environmental modulators of brain development, and 4) Sleep/auditory processing comorbidities. Student Advising & Grants: She mentors doctoral candidates (Lindsay Olson, Jiwandeep Kohli, Bosi Chen) and leads NIH-funded projects including a clinical psychology fellowship for autism evaluation across ages. Laboratory Affiliation: Dr. Fishman co-directs the Brain Development Imaging Laboratories (BDIL), which investigates ASD manifestations through behavioral and neuroimaging approaches.
Marco Di Renzo is a CNRS Professor (Directeur de Recherche Titulaire) at University of Paris-Saclay, affiliated with CentraleSupelec and the Signals and Systems Laboratory (L2S). He serves as Coordinator of the Communications Networks Area at the DigiCosme Laboratory of Excellence and Editor-in-Chief of IEEE Communications Letters. His academic leadership includes membership in the Ph.D. School on ICT Admission Committee at Paris-Saclay University. His educational background includes a Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L'Aquila, Italy (2003, 2007), and a Habilitation à Diriger des Recherches from University Paris-Sud (2013). Laurea (cum laude), Electrical Engineering, University of L'Aquila (2003) Ph.D., Electrical Engineering, University of L'Aquila (2007) Habilitation à Diriger des Recherches, University Paris-Sud (2013) Di Renzo's research focuses on next-generation wireless communications, particularly reconfigurable intelligent surfaces (RIS), 6G technologies, and stochastic geometry modeling. His work bridges theoretical communication theory with practical implementations in cellular networks, millimeter-wave communications, and ultra-wide band systems. Recent publications demonstrate leadership in holographic metasurfaces, integrated sensing and communication (ISAC), and AI-empowered network design, establishing him as a pioneer in electromagnetic wave manipulation for future networks. His award-winning publications span RIS-aided communications, channel modeling, and security frameworks. Analysis of his recent work reveals consistent focus on three pillars: (1) fundamental electromagnetic theory for wave manipulation, (2) practical RIS implementations across frequency bands, and (3) integration with AI for network optimization. His articles frequently address industrial applications including factory automation and space-air-ground networks. Di Renzo's scientific recognition includes: IEEE Fellow (2020) and IET Fellow (2020) Highly Cited Researcher (Web of Science, 2019) SEE-IEEE Alain Glavieux Award (2017) Multiple Best Paper Awards (IEEE ICC, EURASIP) Nokia Foundation Visiting Professorship (2020) As Principal Investigator for CNRS, he coordinates multiple Horizon 2020 projects including SURFER, PathFinder, and MetaWireless. His leadership extends to serving as Project Coordinator for H2020 5Gwireless, 5Gaura, MAPNET, and REDESIGN. With over 350 publications, 17,000+ citations, and h-index of 66+, his research group maintains strong industry partnerships with Nokia and other telecommunications leaders. Di Renzo directs the Signals and Systems Laboratory (L2S) at Paris-Saclay and coordinates the DigiCosme Excellence Lab's Communications Networks Area. His team specializes in electromagnetic modeling for wireless networks and has pioneered the European Telecommunications Standards Institute (ETSI) Industry Specification Group on RIS. The group maintains active collaborations with Aalto University (Finland), University of Technology Sydney (Australia), and University of L'Aquila (Italy).
Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.
Junier Oliva is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill and Lead Faculty of the Master of Applied Data Science program. His research focuses on machine learning, artificial intelligence, and nonparametric statistics, particularly in high-dimensional density estimation, sequential modeling, and learning from complex/structured data. He holds a B.S., M.S., and Ph.D. in Computer Science from Carnegie Mellon University, with prior industry experience at Yahoo! and Uber ATG. Research Interests: Machine learning, artificial intelligence, nonparametric statistics, deep learning, statistical data mining, signal processing, kernel methods, and scalability. His work bridges machine and human learning via collective approaches, emphasizing simple yet flexible models for massive datasets. Awards/Grants: $592K AIM-AHEAD/NIH Grant for Human+AI Collaboration $594K NSF Grant for Scientific Discovery $500K NSF Grant for 'Machine Detectives' Project ACM BCB Best Paper Award (2022) for transparent single-cell classification work Labs/Teams: Director of the LUPA Lab, which develops machine learning techniques for holistic data understanding across domains like healthcare, earth science, and computer vision.
Hannah van Zanten is a Full Professor in Earth Systems and Global Change at Wageningen University & Research, specializing in sustainable food systems, regenerative agriculture, and biodiversity conservation. Her work emphasizes circular food systems, livestock production optimization, and environmental impact mitigation. She has received multiple awards, including the Storm-van der Chijs award (2015) and several Best Oral Presentation accolades at academic conferences. Her research spans topics like protein upcycling, soil biodiversity, and the environmental implications of livestock feed. She supervises PhD projects on regenerative agriculture, circular food transitions, and ecosystem services in South American grasslands. Recent projects include redesigning European food systems to enhance food security under climate change and modeling circularity impacts. Key research interests include: sustainable diets, land-use efficiency, and the integration of biodiversity conservation with agricultural practices. She has published extensively on topics like earthworm farming, circular protein systems, and the compatibility of animal-sourced foods with circular principles. Awards: 5 major prizes for academic contributions, including innovation in animal sciences and sustainability. Grants/Projects: Leading 19 active projects, including EU-funded initiatives on sustainable livestock and circular food system modeling. Labs/Teams: Collaborates with interdisciplinary teams on projects like SUSFANS (Sustainable Food Systems) and Re-Livestock (resilient livestock systems).
Elena Grigorescu is a Professor at the University of Waterloo, Department of Computer Science. She holds a Ph.D. from the Massachusetts Institute of Technology (2010), an M.S. from MIT (2006), and a B.A. from Bard College (2004). Her research focuses on sublinear-time algorithms, error-correcting codes, computational complexity, and learning theory. She explores foundational aspects of algorithms with constraints on time/space, privacy-preserving computation, and applications in graph theory and optimization. Her work includes advancements in spanner algorithms for network design, differential privacy in sublinear-time settings, and learning-augmented approaches for online optimization. Recent publications address trace reconstruction, privacy-utility trade-offs, and combinatorial optimization techniques. Grigorescu is actively involved in conferences like APPROX/RANDOM and IEEE Foundations of Computer Science, contributing to algorithmic theory and practical implementations. Her research emphasizes theoretical rigor while addressing real-world challenges in data analysis and distributed systems. No awards or formal advisees are explicitly listed in the provided information.
Arthur Bousquet is an Associate Professor of Mathematics at Lake Forest College, affiliated with the Math and Computer Science department. He holds a PhD in Applied Mathematics from Indiana University (Bloomington, IN) and a MS in Engineering in applied mathematics and scientific computing from SuP Galilee Engineering School (Paris, France). His research focuses on numerical methods for partial differential equations, including finite volume and finite element techniques, with applications to geophysical fluid dynamics, climate modeling, and biomedical problems like viral shell mechanics. Notable areas include shallow water equations, phase field modeling, and computational methods for atmospheric dynamics. Bousquet has published extensively on topics such as numerical weather prediction, electrokinetic equations, and virus nanoindentation modeling. His work often combines theoretical analysis with computational simulations to address complex systems in fluid dynamics and materials science. He has received the Rothrock Award for teaching excellence (2014) and held research fellowships including an NSF Graduate Fellowship (2009-2013). His teaching includes courses like Computational Mathematics, Multivariable Calculus, and Real Analysis.
Dr. Abbas Ziafati Bafarasat is a Chartered Town Planner and Senior Lecturer in Town Planning at Oxford Brookes University, managing the Certificate in Spatial Planning Studies. He holds a PhD in Planning & Landscape from the University of Manchester (2015) and conducted postdoctoral research at TU Dortmund, Germany. His expertise spans five national contexts, with a focus on strategic urban design, sustainable cities, and policy integration. He has supervised numerous Master’s and doctoral students and transitioned from private practice to academia. Education: PhD in Planning & Landscape, University of Manchester (2015) Postdoctoral studies at TU Dortmund, Germany MA in City & Regional Planning, AD in Law, BSc in Geography Research Interests: His research focuses on achieving healthy and sustainable cities through frameworks like strategic urban design and behavioral sustainability indicators. He pioneered concepts such as 'start-it-yourself urbanism' and developed a 99-indicator system for healthy cities. His work emphasizes policy integration, regional governance, and community-driven solutions. Advising & Grants: Supervised successful completion of doctoral and Master’s theses External examiner for postgraduate programs Labs/Teams: He contributes to the Planning, Policy and Governance (PPG) research group at Oxford Brookes, focusing on urban sustainability and policy innovation.
Neil Champness is the Norman Haworth Professor of Chemistry at the University of Birmingham. He holds a prestigious academic position following roles at the University of Nottingham, including Professor of Chemical Nanoscience (2004-2020). His research focuses on supramolecular chemistry, crystal engineering, and metal-organic frameworks (MOFs). Champness leads a group pioneering studies on molecular self-assembly, surface chemistry, and functional materials. Education & Career - Began academic career with Teaching Fellowships at the University of Nottingham (1995) and Southampton (1994). - Became Lecturer in Inorganic Chemistry at Nottingham (1998), progressing to Reader (2003) and full Professor (2004). - Currently heads the Champness Group at Birmingham, established in 2021. Research Interests Champness’s work spans: - Design of porous materials (MOFs, HOFs) for gas storage and catalysis. - Surface self-assembly of 2D supramolecular frameworks. - Photoresponsive materials and molecular rotaxanes. - Chemical synthesis under constrained conditions. His group emphasizes interdisciplinary approaches, linking chemistry with materials science and nanotechnology. Awards & Recognition 2019: Elected Fellow of the European Academy of Sciences 2020: EPSRC Established Career Fellowship 2016: Royal Society of Chemistry Surfaces & Interfaces Award 2011: Thomson Reuters Highly Cited Researcher 2006: Corday-Morgan Medal (Royal Society of Chemistry) Advisory Roles & Grants - Editorial roles include Chem, Crystals, and CrystEngComm. - Served on Royal Society panels, Irish Research Council, and IUPAC. - Secured major grants from EPSRC and Royal Society. Labs & Collaborations His Birmingham group collaborates globally, with visiting professorships in Japan, Australia, and Brazil. Research is supported by advanced facilities in crystallography and surface chemistry.
Roxane Caron is an Associate Professor at the École de travail social (School of Social Work) within the Faculty of Arts and Sciences at the Université de Montréal. She holds affiliations with the Centre d'études et de recherches internationales (CÉRIUM) and the CIUSSS du Nord-de-l'Île-de-Montréal – Hôpital du Sacré-Cœur. Her research focuses on refugee women's experiences, transnational social work, and decolonial methodologies. She teaches courses such as SVS-6425 (International Social Work) and supervises graduate students in social work and international studies. Her research expertise includes refugee camp dynamics, gendered migration, and intersectional theory. Key projects include the Clinic Mauve initiative addressing LGBTQI+ migrant health and the Transnationalism and Psycho-Social Well-Being project. She has led or co-led over 20 research grants funded by agencies like the CRSH and FRQSC, emphasizing community partnerships and equity. Award-winning educator, Caron's work bridges academic research, clinical practice, and activism. Her recent publications explore ethical frameworks in social work education and refugee integration challenges. She collaborates internationally on migration studies, particularly in the Middle East and Quebec.
Igor Mezić is a Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara. His research focuses on operator-theoretic analysis of nonlinear dynamical systems, with applications in microfluidics, nanotechnology, and biotechnology. He holds affiliations with the Institute for Collaborative Biotechnologies and the California Nanoscience Institute. Education: MS in Mechanical Engineering, University of Rijeka, Croatia PhD in Mechanical Engineering, California Institute of Technology Research Interests: Mixing and separation in fluids, particle dynamics at micro/nano scales, Atomic Force Microscope (AFM) dynamics, and complex systems theory. His work bridges physical phenomena with mathematical modeling for device design and improvement. Awards: Early Career Award (NSF) Alfred P. Sloan Fellowship George S. Axelby Award (IEEE) United Technologies Special Achievement Prize J.D. Crawford Prize (SIAM) Advising & Grants: Supported by NSF Early Career Award. Active in mentoring through interdisciplinary research groups focusing on fluid dynamics and nanotechnology. Labs & Teams: Leads research through the Mezić Group (mgroup.me.ucsb.edu), collaborating on projects spanning microfluidic systems, biotechnology applications, and multiscale dynamics.
Guofeng Cao is an Associate Professor in the Department of Geography at the University of Colorado . His research integrates GIScience , GeoAI , geostatistics , and remote sensing to develop advanced methodologies for analyzing heterogeneous geospatial data and modeling complex spatiotemporal patterns. Focus areas: Uncertainty-aware geographic knowledge discovery, land cover/land use dynamics, spatiotemporal bias analysis, geospatial cyberinfrastructure development Applications: Natural hazards, environmental science, public health, global change studies Recent publications emphasize generative adversarial networks for climate downscaling, neural processes for uncertainty modeling, and fusion transformers for disaster assessment. His work combines deep learning with Bayesian inference to address scalability challenges in geospatial data processing. Scientific Recognition : NASA and USDA grants for spatiotemporal research Advising : Mentoring graduate students in geospatial data science Laboratory : Leads the STAR lab (Spatiotemporal Pattern Analysis & Research)
