Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.
Mark D. Gross is a Professor of Computer Science and Director of the ATLAS Institute at the University of Colorado Boulder. His research focuses on modular robotics, tangible interaction design, digital fabrication, and computational design. He co-founded Modular Robotics and Blank Slate Systems, leveraging his expertise in educational technology and maker culture. Education: PhD in Design Theory & Methods from MIT. Academic history includes roles at Carnegie Mellon University and University of Washington Seattle. His work spans architecture, robotics, and human-computer interaction. Research Interests: Modular robotics and computationally enhanced construction kits Tangible interaction and e-textiles Shape-changing interfaces and swarm robotics Sketch-based interaction and digital fabrication Publications highlight advancements in collaborative AR systems, shape-changing interfaces (e.g., LiftTiles, ShapeBots), and accessible technologies like FluxMarker. His work bridges computational tools and creative design processes. Advising: Guided students such as Ryo Suzuki (PhD '20). Entrepreneurial ventures include companies spun off from research. Labs/Teams: Leads projects at the ATLAS Institute, emphasizing interdisciplinary collaboration in robotics, design, and human-centered computing.
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.
Kris Baetens is a Professor in the Department of Psychology Brain, Body and Cognition at Vrije Universiteit Brussel (VUB). His research focuses on the neural mechanisms underlying social cognition, mentalization, and inhibitory control, particularly exploring the role of the cerebellum and prefrontal cortex in these processes. He employs techniques such as transcranial direct current stimulation (tDCS), EEG, and fMRI to investigate cognitive and clinical phenomena. Leading projects like ANI423 (neural correlates of inhibitory control in adolescents) and FWOAL1160 (cerebellum's role in social cognition). Recipient of the EUTOPIA Young Leaders Academy fellowship (2024-2026). Active collaborations in the PRISM network for mental health research. Key research interests include: - Cerebellar contributions to cognitive and social functions - Neurostimulation techniques for mental health interventions - Mentalizing processes in social action prediction - Personality and learning mechanisms His articles consistently analyze the interplay between neural structures like the cerebellum and behavioral outcomes in clinical and cognitive contexts. Recent work emphasizes applications of tDCS in treating alcohol use disorders and disordered eating, highlighting translational research in non-invasive brain stimulation. Advising/Grants: Supervises student research projects and manages grants from FWO and OZR agencies. Labs/Teams: Core member of the PRISM network and involved in the EUTOPIA fellowship initiative.
Dr. Teresa Wang is a Senior Lecturer in Data Science at Monash University's Faculty of Information Technology, specializing in entity/user modeling, relational/structural machine learning, and graph/network analysis. She holds a Ph.D. from the University of Queensland and degrees from Nanjing University. Currently, she directs the Master of Data Science Program and teaches courses like FIT5201 Machine Learning. Her research focuses on social, e-commerce, and health data modeling, with notable projects including the Knowledge Enriched Approach for Effective Personalization (2025–2027) and collaborations on AI in Mental Health and Site Safety. Dr. Wang has co-authored over 59 publications, emphasizing areas like ontology matching and multimodal data analysis. She actively supervises PhD students and contributes to initiatives like the CSIRO Next Generation Graduates Program for clean energy and sustainability. Education: Ph.D. in Computer Science (2017), University of Queensland Master of Computer Science (2013), Nanjing University Bachelor of Software Engineering (2010), Nanjing University Research Interests: Entity modeling, spatio-temporal data analysis, graph mining, recommender systems, and health/medical records mining. She explores applications in social media, e-commerce, and healthcare sectors. Projects: "Knowledge Enriched Approach for Effective Personalization" (2025–2027) "AI for Clean Energy and Sustainability" (2023–2027) "CSIRO Next Generation Graduates Program: AI in Mental Health" (2023–2027) "Large-scale multimodal knowledge management" (2022–2025) Grants & Collaborations: Engaged with CSIRO, Crank Group, and Pola Practice Pty Ltd. Her work aligns with UN SDGs in education and sustainable energy systems. Labs/Teams: Part of the Monash Energy Institute and Monash Data Futures Institute, contributing to interdisciplinary AI and energy research.
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.
Goran Avlijaš is a researcher affiliated with Singidunum University in Belgrade, specializing in project management, operations research, and retail logistics. He holds a Doctorate in Engineering Management (2011–2016) from Singidunum University, a Master’s in Project Management (2008–2009) from the Faculty of Organizational Sciences, and a Bachelor’s in Management (2003–2007) from the same institution. His research focuses on optimizing project schedules through methods like Earned Value Management and Monte Carlo Simulation, analyzing supply chain efficiency, and exploring gig economy impacts on well-being in Balkan countries. Key research areas include: Project Management Innovation: Developing risk analysis tools (e.g., Event Chain Methodology) and applying earned value metrics to construction projects. Retail Operations: Investigating automated replenishment systems and inventory management challenges in retail environments. Social-Economic Dynamics: Studying gig economy effects on workforce well-being and regulatory impacts on entrepreneurship. His work spans 30+ peer-reviewed articles and conference papers, including contributions to Management , Sustainability , and Frontiers in Psychology . He co-authored textbooks like Project Management and Entrepreneurship for Singidunum University’s curriculum. Active in academic events such as Sinteza and FINIZ conferences, he bridges theoretical research with practical industry applications.
Prof. Tobias Plieninger holds dual appointments as Professor of Social-Ecological Interactions at the Universities of Kassel and Göttingen, Germany, and currently serves as Dean of Research at Kassel’s Faculty of Organic Agricultural Sciences. He specializes in sustainability science focusing on rural landscape dynamics, ecosystem services, and transformative change processes. His work examines intersections between agriculture, forestry, nature conservation, and natural resource management. Education: PhD in Forest and Environmental Sciences (2004, University of Freiburg), Habilitation in Landscape Ecology (Humboldt-Universität zu Berlin). Prior roles include Associate Professorships at the University of Copenhagen and leadership at the Berlin-Brandenburg Academy of Sciences. Research focuses on biocultural landscapes, agroforestry systems, and participatory methods. Notable projects include coordination of the EU’s HERCULES initiative and leadership in IPBES’ Transformative Change Assessment. Recognitions include Clarivate’s Highly Cited Researcher (2019–2022) and the Henriette Herz Fellowship (2022). Editorial roles: Lead Author for IPBES, Associate Editor at Landscape and Urban Planning and People and Nature . Over 200 publications span topics like ecosystem service synergies, high nature value farming, and rewilding strategies. Active in policy engagement through Germany’s Leopoldina Academy and the Joint Programming Initiative on Cultural Heritage. Research Themes: Landscape sustainability, participatory governance, biodiversity in agricultural systems Key Projects: SINCERE (forest ecosystem services), AGFORWARD (agroforestry innovation) Awards: Clarivate’s Highly Cited Researcher, Alexander von Humboldt Foundation fellowship Current initiatives emphasize transdisciplinary approaches, integrating local knowledge with scientific frameworks to address global sustainability challenges.
Dr. Imad El Haddad serves as Group Head of the Molecular Cluster and Particle Processes group at the Laboratory of Atmospheric Chemistry (LAC), part of the Center for Energy and Environmental Sciences at Paul Scherrer Institute (PSI), Switzerland, since 2018. Previously, he held positions as Tenured Scientist and Deputy Head (2018-2019), Senior Scientist in the Smog Chamber group (2015-2018), and Postdoctoral Fellow (2011-2015) at PSI. His research aims to quantify how anthropogenic emissions alter atmospheric pollutant composition and impact Earth's climate and public health through molecular-level analysis using advanced mass spectrometry techniques. His academic background includes: Ph.D. in Atmospheric Chemistry, University of Provence, Marseille (2007-2011) Master's in Environmental Sciences (with distinction, rank 1/9), University of Provence (2006-2007) Master's in General Chemistry (with distinction, rank 1/10), Saint-Joseph University of Beirut (2005-2006) Bachelor of Science in Chemistry (with distinction, rank 1/14), Saint-Joseph University of Beirut (2002-2005) El Haddad's work centers on molecular fingerprinting of atmospheric aerosols , utilizing mass spectrometry (GC/MS, HPLC/APCI-MS2, HPLC/ESI-MS2) to identify primary and secondary molecular markers. He conducts smog chamber experiments to characterize emissions from wood burning, traffic, and cooking processes, determining secondary organic aerosol potential and oxidation state evolution. His group also studies in-cloud aqueous-phase aging and collaborates with global modelers to link aerosol composition to climate forcing and health outcomes like oxidative stress. Recent publications (2025-2024) reveal three dominant trends: (1) rigorous molecular-scale analysis of secondary aerosol formation under varying humidity/temperature, (2) source apportionment breakthroughs in diverse regions (India, Europe, Arctic) using 14C and AMS data, and (3) quantification of health-relevant aerosol properties such as oxidative potential through DTT assays. High-resolution mass spectrometry is a consistent methodological thread across these studies. His scientific awards include: MENRT research fellowship from French ministry of research (2007-2010) Excellence Scholarship (top 1% student, University of Saint Joseph, 2005) Distinction Prize (best student, University of Saint Joseph, 2005) As Group Head, El Haddad oversees the Molecular Cluster and Particle Processes group's research direction and mentorship of junior scientists. While specific grant details are absent from the text, his leadership in multi-institutional publications (e.g., CERN CLOUD, iCUPE) implies active grant management and international collaboration. The group's work bridges laboratory simulations, field deployments, and health/climate modeling to address air pollution complexities. The Molecular Cluster and Particle Processes group develops cutting-edge online/offline mass spectrometers for 1 Hz-resolution atmospheric analysis. They deploy instruments in laboratory smog chamber experiments and global field studies, focusing on molecular marker identification, emission source characterization, and aging process quantification. Collaborations with biochemists and climate modelers extend their impact beyond pure aerosol physics into health risk assessment and policy-relevant climate science.
Dr. Rong-Hao Liang is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with both the Future Everyday Group (Department of Industrial Design) and the Signal Processing Systems Group (Department of Electrical Engineering). His research bridges intelligent sensing systems and user interface technology for ubiquitous computing and embodied human-computer interaction . He co-organized international ACM conferences (CHI, UIST, DIS) and has over 70 peer-reviewed publications and 10 patents. PhD in Computer Science (2014) and MSc in Electrical Engineering (2010) from National Taiwan University Founded GaussToys Inc. in 2015, focusing on magnetic-field sensors Cross-appointed to Electrical Engineering in 2021 His research explores intelligent sensing systems , tangible user interfaces , and physiological sensors for real-world challenges. Key trends in his work include ubiquitous health monitoring (e.g., preterm infants), wearable technology , and innovative interaction design . Articles like GaussBits and NFCStack demonstrate his focus on magnetic and RFID-based tangible systems . Scientific awards include the ACM CHI 2013 Best Paper Award , 2014 Honorable Mentions , and the ACM SIGGRAPH Asia 2012 Emerging Technologies Prize . He mentors passion-driven projects in user interface design and embedded systems , emphasizing technical rigor and creativity. His STRAP project (2020–2025) addresses heart disease prevention via big data and AI . Labs and teams include the Future Everyday Group and Signal Processing Systems Group , with collaborations across healthcare , education , and technology startups . His work aligns with UN Sustainable Development Goals , particularly good health and well-being .
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)
Prof. Dr. Petra Schwille is a Director at the Max Planck Institute of Biochemistry and former C4 Professor of Biophysics at Dresden University of Technology . Her work spans molecular and cellular biophysics, synthetic biology, and single-molecule techniques. Academic disciplines: Natural sciences, biological sciences, physical sciences Key roles: Editorial Board member (Nature Methods, Biophysical Journal), Governing Council of Biophysical Society Research Focus includes membrane biophysics, protein interactions, and microfluidic systems. Her publications emphasize Fluorescence Correlation Spectroscopy (FCS) , receptor-ligand dynamics, and self-organization in bacterial cell division. Developed in vitro models for spatial regulation in cells Explored calmodulin availability and morphogen gradient formation Scientific Recognition includes prestigious awards like the Gottfried Wilhelm Leibniz Prize (2010) and the Biofuture grant (1998) . Max Planck Fellow (2005) Young Investigator Award (2003) Leadership & Service involves roles such as Dean of Studies for Nanobiophysics at TU Dresden and Vice Dean of the Dresden International Graduate School for Biomedicine and Bioengineering (DIGS-BB) . She also contributes to editorial and advisory boards in biophysics and science policy.
Harikesh S. Wong is an Assistant Professor of Biology and Core Member at the Ragon Institute of MGH, MIT, and Harvard. His research focuses on understanding how immune responses are controlled in tissues to balance host protection against threats like pathogens and tumors while avoiding excessive damage. He combines immunology, microscopy, computational methods, and gene manipulation to study immune response regulation in intact tissues. Education: PhD in 2016 from University of Toronto; BSc in Biochemistry from McMaster University (2010) His lab investigates mechanisms of immune homeostasis, including regulatory T cell feedback circuits and mesoscale T cell antigen discrimination. Recent work explores autoimmune disease susceptibility linked to IL-2 feedback circuit fragility and the role of commensal bacteria in liver immune zonation. Key findings include demonstrating how local regulatory T cells prune self-activated T cells and how interleukin 2 circuitry variations influence autoimmune risk. Articles highlight interdisciplinary approaches to dissect immune system control mechanisms. No scientific awards explicitly mentioned. Grants and advising details are not provided in the text. Labs/Teams: Wong Lab at the Ragon Institute focuses on immune system design principles and disease-related breakdowns in control mechanisms.
Professor David Dupret is a Professor of Neuroscience and MRC Investigator at the University of Oxford, where he also serves as a Tutorial Fellow in Biomedical Sciences at St Edmund Hall. His work takes place within the MRC Brain Network Dynamics Unit, part of the Nuffield Department of Clinical Neurosciences, and he is affiliated with the Department of Physiology, Anatomy and Genetics. David completed his Ph.D. in Neuroscience at the Institute François Magendie (INSERM, University of Bordeaux, France), receiving the French Neuroscience Association's 2007 Ph.D. Year Prize. He joined the MRC Anatomical Neuropharmacology Unit in 2007 as a Visiting Fellow, funded by the Institute of France and the International Brain Research Organisation. In 2009, he became an MRC postdoctoral scientist and Junior Research Fellow at St Edmund Hall, progressing to MRC Programme Leader Track scientist in 2011 and tenured MRC Programme Leader in 2014. Professor Dupret's research focuses on the circuit-level mechanisms of memory-guided behavior, with particular emphasis on neural dynamics of memory circuits during active waking behavior and sleep. His laboratory employs in vivo multichannel recordings and optogenetic manipulation of neuronal ensembles to investigate how hippocampal networks organize memory processes. His work has revealed fundamental insights into how memory circuits operate during both waking behavior and sleep states, particularly regarding hippocampal ripple activity, dentate spikes, and offline reactivation processes. Analysis of Professor Dupret's recent publications reveals a consistent focus on hippocampal network dynamics and memory processes. His work spans from basic neural circuit mechanisms to applications in neurodegenerative conditions like Alzheimer's disease. A notable trend is the integration of computational approaches with experimental neuroscience to understand how neural assemblies encode and retrieve memories. His team has made significant contributions to understanding how dentate spikes support memory flexibility and how hippocampal ripple diversity organizes neuronal reactivation during offline states. French Neuroscience Association's 2007 Ph.D. Year Prize Foundation Louis D. Research Fellowship (2007) International Brain Research Organisation Fellowship (2008) FENS-Kavli Network of Excellence Scholar (2016) Boehringer Ingelheim-FENS Research Award (2018) Elected to membership of Academia Europaea (2024) Professor Dupret has secured substantial research funding through his MRC Programme Leader position and has mentored numerous researchers who appear as co-authors on his publications. His laboratory, the Dupret Group, operates within the MRC Brain Network Dynamics Unit, collaborating extensively with other research groups including the Sharott Group, Magill Group, and Denison Group. Current research directions include investigating how memory circuits maintain flexibility while resisting extinction, exploring the relationship between neural coactivity patterns and memory organization, and developing computational models of hippocampal function. His team is actively pursuing future work on the mechanisms underlying memory persistence and the neural basis of flexible memory recall.
Daniel Hyde is an Associate Professor in the Department of Psychology at the University of Illinois Urbana-Champaign, affiliated with the College of Liberal Arts & Sciences and the Neuroscience Program. His research explores the nature and development of abstract conceptual knowledge through behavioral and neural measures. PhD in Psychology from Harvard University Hyde investigates cognitive development from infancy to adulthood, focusing on quantitative reasoning , spatial reasoning , and psychological reasoning using techniques like event-related brain potentials (ERPs) , functional near-infrared spectroscopy (fNIRS) , and behavioral assessments. His recent work examines how symbolic number knowledge builds on non-symbolic foundations and how neural sensitivity to mental states in infancy predicts later theory of mind abilities. Hyde's publications demonstrate a consistent focus on numerical cognition, multisensory integration, and developmental neuroscience. He leads the Brain and Cognitive Development Lab , participates in global initiatives like ManyNumbers and ManyBabies , and collaborates across disciplines to apply developmental insights to education and public health contexts.
