Anne-Sophie Chauvin is a Senior Lecturer and Researcher at École Polytechnique Fédérale de Lausanne (EPFL), School of Basic Sciences, within the Institute of Chemical Sciences and Engineering and the Supramolecular Chemistry Laboratory. She actively engages in supramolecular and inorganic chemistry, focusing on f-element (lanthanides and actinides) coordination polymers and luminescent bioprobes for biological and technological applications, including invisible inks and dye-sensitized solar cells. PhD in Bioinorganic Chemistry from University Paris V-René Descartes (thesis on Nitrile Hydratase mimetics) Postdoctoral work at University of Geneva on chiral alcohol configuration analysis Habilitation à Diriger des Recherches (HDR) from University René Descartes (2006) Her research spans Lanthanide and Actinide Chemistry , Luminescence , Coordination Polymers , Metallacages , and Photovoltaic Materials . Recent publications emphasize catalytic spiro stereocenter formation, actinide coordination polymers, and photoredox-enabled biomolecule functionalization. She has supervised PhD students including Andrei Andreichenko , Julien Andrès , Steve Comby , and Aurélien Willauer . Recognitions include Fellowship of the Royal Society of Chemistry (FRSC) and membership in the Swiss Chemical Society (SCS). Current roles include teaching General and Analytical Chemistry to first-year Pharmacy and Biology students at the University of Lausanne (UNIL), overseeing practical sessions, and serving on the EPFL School of Basic Sciences Faculty Council.
Jürgen Bernard is an Assistant Professor of Computer Science at the University of Zurich , leading the Interactive Visual Data Analysis (IVDA) Group . He is associated with the Digital Society Initiative (DSI) and holds a PhD in Computer Science from Technische Universität Darmstadt (2015) with a focus on time-oriented data analysis. His academic journey includes postdoctoral research at TU Darmstadt and the University of British Columbia. Education : Diploma in Computer Science (2009, TU Darmstadt) PhD in Computer Science (2015, TU Darmstadt) Research Interests : Dr. Bernard specializes in interactive visual data analysis , explainable machine learning , and human-centered AI . His work explores time series analysis , multivariate data exploration , and user-driven preference elicitation . He develops visual analytics systems for domains like healthcare , digital humanities , and industrial applications , with a particular focus on responsible AI and transparency in algorithmic systems . Research Trends : His publications emphasize interactive machine learning workflows , visual analytics for healthcare , and time-stamped event sequence analysis . Recent work includes LLM validation frameworks (Human-Data-Model Interaction Canvas) and personalized ranking systems funded by the Swiss National Science Foundation. He integrates temporal data with multivariate analysis across applications from medical manufacturing to chronic disease management . Scientific Recognition : EuroGraphics Young Researcher Award (2022) EuroVis Young Researcher Award (2021) Best Paper Awards at IEEE VIS (2021), EuroVA (2021, 2025) Dirk Bartz Prize (2017), Hugo-Geiger Preis (2016) Teaching & Grants : He teaches Interactive Visual Data Analysis (6 ECTS), Digital Health Seminars , and People-Oriented Computing . Currently leads a SNF Grant on Personalized Visual Analytics for multi-criteria decision support (2024-2028) with ETH Zurich's Prof. M. El-Assady.
Christopher G. Healey is the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics and a Professor in the Department of Computer Science at North Carolina State University. His research spans visualization, data analytics, text analytics, sentiment analysis, machine learning, cognitive psychology, computer graphics, and social media analytics. He has graduated 15 Ph.D. and 26 master's students and secured over $6 million in research funding from agencies including the National Science Foundation, Department of Defense, National Security Agency, Army Research Office, and various industry partners. He has published over 100 peer-reviewed articles and is a senior member of both IEEE and ACM, as well as a member of the NC State Academy of Outstanding Teachers. His research focuses on developing visualization techniques that leverage visual perception to support rapid, accurate, and effective analysis of large, complex datasets. More recently, he has been investigating machine learning for natural language processing and text analytics. His work includes projects on visualizing election results, sentiment estimation for social media, and wildfire narratives using large-scale social media data. His publications demonstrate a strong trend toward integrating machine learning with visualization, particularly for text analytics and social media analysis. He has made significant contributions to visualizing deep neural networks, cyber situation awareness, and pandemic response analytics, showing how visualization can enhance understanding of complex systems and large datasets across multiple domains. IBM Faculty Award (2007, 2008, 2010, 2011, 2012) Senior member, Association of Computing Machinery (ACM) (2007) Senior member, Institute of Electrical and Electronics Engineers (IEEE) (2007) NC State Academy of Outstanding Teachers inductee (2003) National Science Foundation Faculty Early CAREER Award (2001) He has successfully mentored numerous graduate students and secured significant research funding across multiple projects. His work with the Laboratory for Analytic Sciences, National Science Foundation, and Department of Defense demonstrates strong industry and government partnerships. His recent projects focus on visualizing social media narratives, deep neural networks for text understanding, and predictive analytics for large document collections. He leads research groups focused on visualization and analytics, working with teams to develop innovative approaches for data exploration and analysis. His current work continues to push the boundaries of how visualization can be used to enhance understanding of complex data across domains including public health, cybersecurity, and social media analysis.
Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.
Duncan Wilson is a Professor of Connected Environments at the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London. His work bridges academia and industry, focusing on IoT, AI, and spatial analysis to enhance understanding of built and natural environments. Current role: Professor of Connected Environments at UCL Education: PhD in Artificial Intelligence and Machine Vision (UCL, 1997), BEng (Hons) in Electrical Engineering (Loughborough University, 1993) Research interests include: Cognitive computing at the network edge Extraordinary sensory systems for data capture Spatial reasoning and digital twins IoT for healthcare and biodiversity Edge AI and TinyML Recent articles span digital twin development , IoT for biodiversity monitoring , and smart healthcare infrastructure . He has received recognition for collaborative R&D approaches during his directorship at Intel's Sustainable Connected Cities institute. Teaching: Leads MSc Connected Environments and modules on IoT ethics, AI on microcontrollers, and sensor network deployment Projects: IoT Living Lab at UCL, Project Hercules for eye clinic analytics, and Shazam for Bats environmental monitoring Professional activities: Former Director of Intel Collaborative Research Institute (2012-2018), ex-member of Smart London Board (2017-2022)
Eliese-Sophia Lincke is a Junior Professor at the Department of History and Cultural Studies, Freie Universität Berlin, since May 2022. Her work bridges computational methods with Egyptology, focusing on digital tools for studying ancient texts. Bachelor's and Master's in Egyptology, Humboldt-Universität zu Berlin (2007) PhD in "The Conception of Spaces in Language" (TOPOI Cluster, 2012) Research interests include: Digital Humanities : Developing machine learning models for Hieroglyphic, Demotic, and Coptic text processing Linguistic Typology : Analyzing classifier systems in Ancient Egyptian and Sign Languages Spatial Linguistics : Investigating prepositions and spatial adverbs in Egyptian-Coptic Recent publications focus on Neural Lemmatization , OCR for Coptic , and Classifier Semantics , demonstrating her commitment to computational Egyptology. Scientific awards include the Humboldt-Preis 2008 for best Master's thesis and the Prize for Good Teaching 2014 . She has co-organized workshops like "Wege zum Ägyptischen" and served as Co-Editor for Lingua Aegyptia . Her teaching contributes to the Digital Studies of Ancient Texts Master's program.
Luigi De Russis is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) within Politecnico di Torino . He serves as Deputy Director of DAUIN and is a member of the PIC4SeR (PoliTO Interdepartmental Centre for Service Robotics). His academic roles focus on Human-Computer Interaction , Digital Wellbeing , and Artificial Intelligence applications. Research interests: Accessibility, Conversational agents, Developers tools, Digital wellbeing, Intelligent user interfaces, Internet of Things Teaching: Courses in Human-AI Interaction, Web Applications, and Computer Vision at undergraduate and graduate levels Leadership: Vice-President of ACM SIGCHI (2024-), Executive Committee member (2021-2024) His research explores: Digital wellbeing education for teens through gamified systems AI-assisted UI design tools Smart home interaction via multimodal commands End-user development for self-control technologies Integration of accessibility guidelines in AI systems Recent article trends show a focus on generative AI for interface design, attention-capturing heuristics, and educational systems for step-by-step learning. He has received the Most Influential Paper Award (2024) and Best Late Breaking Results Award (2025) from ACM SIGCHI. Scientific awards: Award of Scientific Excellence, University of Salamanca (2011) Most Influential Paper Award, International Conference on Intelligent Environments (2024) Best Late Breaking Results Paper Award, ACM SIGCHI Symposium (2025) As advisor, he supervises PhD students in Artificial Intelligence and Computer Engineering , focusing on topics like user-centered AI, generative models, and digital self-control interfaces. He leads the ELITE research group and contributes to commercial projects including TEIA (AI tourism) and MAPP (interactive museums).
Phu Nguyen is an Associate Adjunct Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His academic background includes a Ph.D. in Civil Engineering from UC Irvine (2014), an M.S. in Engineering Science from the University of Melbourne (2008), and a B.Sc. in Civil Engineering from Bach Khoa University HCMC Vietnam (2003). Education Ph.D., University of California, Irvine, 2014 M.S., University of Melbourne, 2008 B.Sc., Bach Khoa University, 2003 Nguyen’s research focuses on flood modeling and forecasting, with a strong emphasis on satellite-based precipitation estimation. He has developed systems like CONNECT for analyzing large-scale rainfall systems, RainSphere for integrated satellite data tools, iRain for real-time rainfall observations, and DataPortal for on-demand data processing. His work leverages machine learning, GIS, and remote sensing technologies to improve hydrologic and disaster management applications. Recent publications highlight his integration of deep learning and satellite infrared/microwave data to enhance precipitation estimation accuracy. Key contributions include bias correction frameworks, tropical cyclone detection models, and evaluations of climate data records like PERSIANN-CCS-CDR. Nguyen is actively affiliated with the Center for Hydrometeorology & Remote Sensing (CHRS) at UC Irvine, where he contributes to advancing satellite precipitation methodologies and their hydroclimatic applications.
Mehmet Koyutürk serves as the Andrew R. Jennings Professor in the Department of Computer and Data Sciences at Case Western Reserve University's Case School of Engineering, with additional affiliation as a Member of the Cancer Genomics and Epigenomics Program at the Case Comprehensive Cancer Center. His computational research bridges algorithm development with biological applications, focusing on network-structured data analysis to address complex biomedical challenges. Dr. Koyutürk earned his Ph.D. in Computer Science from Purdue University following B.S. and M.S. degrees in Electrical Engineering and Computer Engineering from Bilkent University. His primary research domains include high-throughput biological data analysis, systems/network biology methodologies, data mining algorithms, and scientific computing optimization, with particular emphasis on phosphorylation networks, genomic interactions, and multi-omics integration. Recent publication trends reveal expanding applications of his network science expertise into Alzheimer's disease phosphoproteomics, bipolar disorder biomarker discovery, and intimate partner violence analysis, while maintaining core contributions to graph neural networks and biological link prediction. His group actively develops open-source analytical tools like RokaiXplorer for phospho-proteomic data accessibility. Scientific Recognition Andrew R. Jennings Professorship Dr. Koyutürk leads multiple NIH-funded initiatives including R01-LM012980 for phosphoproteomics analysis, U01-CA198941 (BD2K program) for big network integration, and R01-LM011247 for GWAS enhancement, complemented by NSF CAREER Award CCF-0953195. He serves on the steering committee for CWRU's Systems Biology and Bioinformatics graduate programs and as Associate Editor for IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), with extensive collaboration through Mark Chance's Center for Proteomics and Bioinformatics. His laboratory specializes in developing scalable algorithms for biological network analysis, currently advancing projects on kinase-substrate association prediction, co-phosphorylation network characterization in cancer, and network-based approaches to intimate partner violence data mining, with strong emphasis on translating computational methods into biomedical insights through open-source software dissemination.
Hasti Seifi is an Affiliated Associate Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Human-Centred Computing. Her research focuses on haptics, augmented reality, and human-robot interaction. Institution: University of Copenhagen Department: Department of Computer Science Section: Human-Centred Computing Research interests include: Designing innovative haptic feedback systems Exploring tactile experiences in augmented reality Developing human-robot interaction frameworks Creating generative models for haptic design Investigating social touch technologies Advancing mid-air and ultrasound haptic interfaces Recent publications demonstrate a strong focus on: Generative haptic modeling for AR/XR systems Human-robot interaction dynamics Text input in extended reality environments Visual-haptic multisensory integration Ultrasound mid-air haptic design tools Social touch technologies
Yu Lan is a Research Fellow at the Yale School of Public Health , specializing in spatial epidemiology and health geography . Her work integrates genomic data (e.g., WGS) with geographic information systems (GIS) to analyze transmission patterns of infectious diseases like COVID-19 and tuberculosis . Education: PhD in Geography, University of North Carolina at Charlotte MA in Geography, University of North Carolina at Charlotte Research Interests focus on space-time disease modeling , infectious disease transmission , and data-driven public health tools . She develops web-based systems for real-time disease surveillance and environmental risk assessment, including tools for private well contamination and urban neighborhood dynamics . Scientific Awards include the SISMID Scholarship (2024) , Student Honors Paper Competition Finalist (2023) , and David Woodward Digital Map Award (2021) . Collaborations include work with the Ted Cohen Lab and researchers like Joshua Warren and Eric Delmelle . Her publications emphasize genomic-spatial integration and cluster detection algorithms for diseases such as tuberculosis and SARS-CoV-2.
Jennifer Ryan is a Professor of Numerical Analysis and Division Head of Numerical Analysis, Optimization, and Systems Theory at the Department of Mathematics, KTH Royal Institute of Technology. Her research focuses on designing and developing numerical schemes to extract accuracy from simulations, particularly through superconvergence properties and computational efficiency improvements. She applies these techniques to applications such as imaging, fluid visualization, and plasma dynamics. Education: PhD in Applied Mathematics, Brown University; MS in Mathematics, Courant Institute; BA in Applied Mathematics, Rutgers University. Professional Activities: Member of editorial boards for BIT Numerical Mathematics, ESAIM:M2AN, and Communications on Applied Mathematics and Computation; Steering committee member of AWM's Women in Numerical Analysis and Scientific Computing (WINASc). Her publications emphasize discontinuous Galerkin methods, SIAC filtering, and applications in fluid dynamics. She has served on multiple grant review panels and received awards for diversity and inclusion initiatives. Grants: Principal Investigator for projects funded by the Swedish Research Council, NSF, and US Air Force Office of Scientific Research. Awards: Fellow of UK Higher Education Academy, DAAD Fellowship, and Householder Fellowship.
Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and Department of Computer Science at the University of California, Irvine. His academic journey includes a B.S. in Computer Science from the University of Massachusetts Amherst (1983), an M.S. in Computer Science from The George Washington University (1991), and a Ph.D. in Computational Sciences and Informatics from George Mason University (1997). Prior to UCI, he served as Assistant Professor at George Mason University (1997-1999) and Senior Fellow at The Neurosciences Institute (1999-2007). University of California, Irvine (2007-present) George Mason University (1997-1999) The Neurosciences Institute (1999-2007) His research focuses on neurorobotics , exploring how embodied cognition and biologically plausible neural models can enhance robotic systems. Key areas include spiking neural networks , neuromodulation , path planning , and interactive tactile robots for therapeutic applications. His work bridges neuroscience , robotics , and cognitive science , with applications in autonomous vehicles , neuroprosthetics , and AI explainability . Recent publications emphasize spiking neural networks for navigation , neuromodulated attention , and neuromorphic hardware integration. The development of CARLsim, a GPU-accelerated spiking neural network simulator now in version 6.0, represents a major technical contribution. His team's work on socially assistive robots like CARL-SJR targets therapeutic applications for autism and ADHD. Scientific Awards IJCNN 2020 Best Paper Award Finalist for Best Student Paper at IJCNN 2018 Best Paper Award at IEEE IJCNN 2009 Grants include National Science Foundation funding for neural models of decision-making (2009). His lab (Cognitive Anteater Robotics Laboratory) develops systems that use large-scale brain simulations for autonomous behavior , with applications in adaptive robotics , sensorimotor learning , and neuroethology . Current projects explore neuromodulatory influences on attention systems and cognitive flexibility .
Garreth Tigwell is an Assistant Professor in the School of Information at RIT, co-directing the CAIR Lab with Dr. Kristen Shinohara. His research focuses on accessibility in digital design, particularly for disabled users, addressing challenges faced by novice and expert creators. His work spans topics like accessible prototyping tools, cultural considerations in design, and inclusive mixed reality interfaces. Education: BSc in Psychology, University of Dundee, 2012 MSc (Distinction) in User Experience Engineering, University of Dundee, 2014 PhD in Human-Computer Interaction (HCI), University of Dundee, 2019 Research Interests: Designing accessible digital systems for blind, deaf, and low-vision users Adaptable user interfaces for mixed reality and textured surfaces Cultural dimensions in accessibility pedagogy Authentication methods for visually impaired users Articles Trends: Recent work emphasizes AR/VR accessibility, cultural design frameworks, and haptic authentication. His studies often involve collaborations with global researchers and industry partners. Awards: Best Paper (MobileHCI 2022) CHI Honorable Mention (2023, 2024) NSF-funded research projects Advising & Grants: Active in mentoring graduate students and securing grants. His lab focuses on born-accessible AI tools and inclusive design education. Teaches courses like HCI Research Methods and Future Interactions. Labs/Teams: Co-leads the CAIR Lab, which develops technologies to bridge accessibility gaps in digital design and prototyping.
Prof. Stefan Eisebitt is a Director at the Max-Born-Institut für Nichtlineare Optik und Kurzzeitspektroskopie and holds a Professorship in Experimental Physics at the Technische Universität Berlin. His research focuses on ultrafast magnetization dynamics, nanoscale structure analysis, and novel imaging techniques using coherent XUV/X-ray spectroscopy. He leads the Transient Electronic Structure and Nanoscience group and is involved in cutting-edge projects involving femtosecond laser-driven X-ray sources and spintronic materials. Education and Career: He obtained his Diplom (1992) and Ph.D. (1996) from Cologne University, followed by postdoctoral research at the University of British Columbia and Forschungszentrum Jülich. He became a Privatdozent at Humboldt-Universität Berlin (2005) and held professorships at TU Berlin (2008–2015) and Lund University (2012–2015) before his current role since 2015. He leads the Functional Nanomaterials joint research group between Helmholtz-Zentrum Berlin and TU Berlin. Research Interests: His work spans transient electronic structure, ultrafast optical manipulation of magnetization, nanoscale material characterization, and advanced coherent imaging methods. Key techniques include XUV/X-ray spectroscopy, laser-driven plasma sources, and femtosecond time-resolved studies. Professional Roles: He chairs the Physikalische Gesellschaft zu Berlin and the Elettra Scientific Advisory Council. He has held leadership roles in the European XFEL Scientific Advisory Committee and the Komitee für Forschung mit Synchrotronstrahlung (KFS). His lab develops state-of-the-art setups for ultrafast X-ray scattering and holography.
