Katy Börner is a Professor affiliated with Indiana University, Bloomington, USA. Her research focuses on data visualization, scientometrics, and the science of science, with contributions to tools like Network Workbench (NWB) and Sci2. She leads interdisciplinary projects such as the Human Reference Atlas and explores visualization literacy in education and public health. Her work spans virtual reality applications, biomedical knowledge networks, and AI-driven scientific discovery. Key research interests include mapping scientific collaboration networks, analyzing scholarly publications, and developing visualization frameworks for big data. She collaborates widely with institutions like NIH and VIVO, advancing open science and interdisciplinary research. Her projects often bridge computational methods with human-centric design, enhancing understanding of complex systems in health, technology, and social sciences. Publications highlight innovations in interactive visualization tools (e.g., opioid crisis research networks), data integration (Human Reference Atlas), and AI applications in biomedical research. She emphasizes translating data into actionable insights through visual analytics, impacting policy, education, and healthcare.
Pourang Irani is a Professor and Principal’s Research Chair in Ubiquitous Analytics at the University of British Columbia (Okanagan campus), within the Irving K. Barber Faculty of Science’s Department of Computer Science, Mathematics, Physics and Statistics. Previously, he served at the University of Manitoba for 19 years as a faculty member and Acting Associate Dean of Science. His research focuses on Human-Computer Interaction (HCI), Wearable Computing, and Information Visualization, with an emphasis on designing interactive systems for 'anytime, anywhere' sensemaking using emerging technologies like mixed reality and smart devices. He leads interdisciplinary projects such as the NSERC CREATE grant on Visual and Automated Disease Analytics, training data scientists in health analytics. Education: PhD in Computer Science (University of New Brunswick, 2002), supervised by Dr. Colin Ware. Research Interests: Wearable interfaces (smartwatches, smartrings, and AR/VR) Data visualization for health and pervasive systems Persuasive health technologies and data storytelling Mid-air and hands-free interaction techniques Embodied interaction through social robots Recent Work Trends: Articles emphasize innovations in smartwatch interaction (e.g., bezel-to-bezel gestures), tactile visualizations via skin-dragging, and voice assistant-driven health data queries. Projects like Databiting explore transient personal data exploration, while Data Videos focus on narrative-driven health communication. Grants & Leadership: Principal Investigator of NSERC CREATE Visual and Automated Disease Analytics program. Co-leads UBCO’s Digital Transparency cluster. Active in interdisciplinary teams addressing health informatics and HCI challenges. Labs & Teams: Leads a lab developing prototypes in wearable computing, spatial analytics, and immersive technologies. Collaborates with researchers in medicine, engineering, and data science to translate HCI innovations into practical solutions.
Laura Albert is a Professor of Industrial & Systems Engineering at the University of Wisconsin-Madison and former David H. Gustafson Department Chair (2021-24). She serves as a Fellow of AAAS and IISE, and previously held the INFORMS presidency. Her research focuses on optimizing public-sector systems, with applications in critical infrastructure protection, emergency response, and cybersecurity. She advocates for public engagement through op-eds and blogs like 'Punk Rock Operations Research.' Education: PhD in Industrial Engineering, University of Illinois at Urbana-Champaign (2006) MS in Industrial Engineering, University of Illinois at Urbana-Champaign (2001) BS in Industrial Engineering, University of Illinois at Urbana-Champaign (2000) Research Interests: Dr. Albert’s work bridges operations research and public policy, addressing challenges in emergency medical services, voting system security, law enforcement strategies, and opioid treatment diversion programs. She employs mathematical optimization, game theory, and stochastic modeling to design resilient systems. Awards: INFORMS Impact Prize (2018) NSF CAREER Award (2011) Fulbright Award (2020) AAAS Fellow (2020) Advising & Grants: While explicit student names aren’t listed, her research has been supported by grants from the NSF, Army Research Office, and other agencies. She advises on interdisciplinary projects involving public health, cybersecurity, and disaster management. Labs/Teams: Engaged in collaborative efforts across the College of Engineering, including affiliations with the Electrical & Computer Engineering department. Leads initiatives on resilient infrastructure and emergency response systems.
Dongwoo Kim is a researcher affiliated with Hanyang University, ERICA Campus (Department of Electronics and Communication Engineering) and has previously collaborated with institutions like POSTECH , Chungnam National University , and Microsoft . His work spans interdisciplinary domains in Computer Science and Engineering . Hanyang University, ERICA Campus - Department of Electronics and Communication Engineering POSTECH - Power Analog Electronics & Semiconductor Devices Lab Microsoft Chungnam National University Kim's research focuses on formal verification of automotive control software, deep learning applications in environmental monitoring, 3D modeling for indoor positioning, and machine learning for signal processing. His recent publications highlight advancements in graph neural networks (GNNs), including analyzing oversmoothing and gradient dynamics, as well as developing geometric vision-language models with domain-agnostic encoders. His 15 most recent articles (2023-2025) address topics like: Optimizing hybrid electric vehicle engine performance 3D modeling for indoor localization GNN training stability UAV-based environmental monitoring Algorithm difficulty prediction for programming problems Millimeter-wave antenna design Kim collaborates with researchers in software engineering , signal processing , and environmental science domains. His work intersects formal methods , applied machine learning , and embedded systems research.
Donald Rio holds the Richard and Rhoda Goldman Distinguished Chair in the Biological Sciences and is a Professor of Biochemistry, Biophysics, and Structural Biology. He is affiliated with the Division of Biochemistry and Molecular Biology and the Center for Integrative Genetics. His lab focuses on nucleic acid transactions, including transposable element mobilization (P elements) and RNA binding protein mechanisms controlling alternative splicing. Research highlights include studies on THAP9 proteins in humans/zebrafish, cryo-EM structural analysis of transposase-DNA complexes, and splicing regulation in neurodegenerative diseases like ALS and Parkinson’s. His work combines biochemical, genetic, and computational approaches, including the development of the Junction Usage Model (JUM) for splicing analysis. Research interests span transposition mechanisms linked to HIV integration, immune system recombination, and evolutionary genome dynamics. His team investigates how RNA binding proteins like hnRNPA1 influence splicing in disease contexts, with projects involving CRISPR-based models and patient RNA-seq data analysis. Collaborations include studies on splicing accuracy across tissues and age, and the impact of splicing defects in neurodegenerative disorders. Key awards include the Goldman Chair. His lab’s contributions bridge fundamental molecular mechanisms with translational applications in genetic disease modeling and drug discovery. Recent work focuses on isogenic stem cell models (iSCORE-PD) for Parkinson’s research and structural biology insights into transposase function. Grants and projects involve NIH funding for ALS splicing studies and collaborations with institutions like the Buck Institute. His lab actively publishes in top journals such as Genome Research , PNAS , and Nature , with a strong emphasis on cryo-EM and bioinformatic methods.
Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center. Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered. Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI. Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies. Her scientific contributions have been recognized with multiple honors: Best Paper Award, Honorable Mention at CHI 2025 (two papers) Best Paper Award at CHI 2024 Best Paper Award, Honorable Mention at FAccT 2023 Best Paper Award, Honorable Mention at HCOMP 2022 Best Paper Award, Honorable Mention at CHI 2021 Best Paper Award, Honorable Mention at CHI 2014 Outstanding Paper Award at IUI 2019 Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development. As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.
Christiana Mavroyiakoumou is a Courant Instructor/Assistant Professor at the Courant Institute of Mathematical Sciences, New York University. She specializes in fluid dynamics and fluid-structure interactions, with a focus on vortex dynamics, membrane flutter, and bio-inspired systems. Her research integrates modeling, numerical simulations, and experimental insights to study phenomena such as bird flock formations and fish swimming hydrodynamics. Mavroyiakoumou holds a Ph.D. from the University of Michigan (2022), an M.Sc. from the University of Oxford (2017), and a B.Sc. from Imperial College London (2016). Education: PhD in Applied & Interdisciplinary Mathematics, University of Michigan (2017–2022) MSc in Mathematical Modeling and Scientific Computing, University of Oxford (2016–2017) BSc in Mathematics, Imperial College London (2013–2016) Her research interests span fluid-structure interactions, vortex dynamics, and collective locomotion. She investigates how fluid flows mediate interactions between bodies, such as the aerodynamics of bird formations and the hydrodynamics of flapping foils. Her work bridges theoretical models with experimental observations, contributing to both fundamental science and bio-inspired engineering. Mavroyiakoumou has received prestigious awards including the Joseph B. Keller Fellowship (NYU), Peter Smereka Award (U-M), and ProQuest Distinguished Dissertation (U-M). She actively engages in academic service, organizing conferences and mentoring students. Her teaching experience includes courses on mathematical modeling, differential equations, and algebra at NYU and the University of Michigan. Key Research Themes: Flow-mediated collective behavior and instability mechanisms Vortex wake interactions and their role in locomotion Membrane dynamics in inviscid and viscous flows She collaborates with experimentalists like Leif Ristroph and Jun Zhang at NYU's Applied Math Lab, focusing on experimental validation of theoretical models. Her recent work explores self-amplifying waves in bird formations and the aerodynamic origins of flight coordination.
Elinor Benami is an **Assistant Professor** in the Agricultural and Applied Economics Department at Virginia Tech. She holds affiliations with the VT Remote Sensing & Global Change Center, the Center for Advanced Innovation in Agriculture, and Stanford’s RegLab. Her research focuses on environmental and development economics, leveraging satellite imagery and machine learning to enhance disaster financing and environmental compliance. She earned a B.A. from UNC Chapel Hill, a Ph.D. from Stanford University, and a postdoc at UC Davis. **Research Interests**: Climate risk management, agricultural resilience, remote sensing applications, and policy design for sustainable agriculture. Current projects include NASA-funded work on Moroccan irrigation and drought financing, and evaluating U.S. environmental compliance using AI. **Awards/Grants**: Led a $650K NASA Harvest grant, part of a $80M climate-smart agriculture initiative, and received the VT Early Career Scholarly Impact Award Nominee. Active in policy, including advising the EPA on environmental compliance algorithms. **Teaching**: Courses include 'Remote Sensing in Social Sciences', 'Climate Risk Management', and 'Environmental and Sustainable Development Economics'. Mentors students at all levels, emphasizing computational skills and social impact. **Affiliations**: NASA Harvest, VT Remote Sensing IGEP, and the Alliance for Climate-Smart Agriculture. Collaborates with global institutions on drought financing and satellite data applications.
Dr. Marcel Dettling is a Group Lead in Data Analysis and Statistics at the ZHAW School of Engineering , focusing on predictive analytics, applied statistics, and complex data analysis. He also serves as a Lecturer at ETH Zurich , teaching advanced statistical methods. Education : PhD in Mathematics (2000-2004), ETH Zurich Postdoc in Applied Statistics (2004-2006), Johns Hopkins University His research spans predictive analytics (regression, classification, time series), data mining, and applications in health economics, transportation safety, social sciences , and business analytics . Recent work includes pharmaceutical cost group analysis for Swiss healthcare and predictive maintenance for marine vessels. Selected publications highlight his expertise in flight trajectory modeling , deep learning error mitigation , and statistical frameworks for rehabilitation finance . His projects address diverse fields like crowdworking in nursing, energy optimization for shipping, and customer behavior prediction.
Swati Aggarwal is a Professor in Artificial Intelligence at the Faculty of Logistics, Molde University College (HiMolde). Her research focuses on AI applications in healthcare, ethics, cognitive development, and neural networks. She holds a PhD in Neutrosophic Neural Networks, a Master's in Information Technology, and a Bachelor's in Computer Science and Engineering. Previously, she was a Marie Curie Postdoc Fellow at NTNU, working on AI models for cognitive assessment in infants (AIM_COACH project). Research Interests - AI in Health/Medicine - Ethics in AI and Societal Impact - EEG/BCI for Cognitive Assessment - Machine Learning and Deep Learning Publications Her recent work spans AI ethics, BCI applications, adversarial attacks, and healthcare diagnostics. Notable contributions include EEG-based infant perceptual monitoring (2025) and malaria detection via EfficientNet (2023). She also explores cross-lingual adversarial robustness and blockchain in hospitality systems. Labs/Teams - ABC-AI: Applied, Basic, and Conscientious AI Group - Virtual Technologies and Learning Research Group
Prof. Matt Pritchard is a Professor in Earth & Atmospheric Sciences at Cornell University, based at Snee Hall. His research focuses on volcanology, geodesy, and remote sensing, with a particular emphasis on using satellite data to monitor volcanic activity, deformation, and glacial interactions. He leads studies on global volcanic systems, including Indonesia's Semeru and Raung volcanoes, Chile's Cordón Caulle, and Bolivia's Uturuncu, applying techniques like InSAR, SAR, and thermal imaging. Key research interests include volcanic eruption dynamics, magma-hydrothermal systems, and the integration of multi-sensor datasets. He has contributed to developing tools like Hotspotter for automated volcanic thermal feature detection and has explored planetary volcanism (e.g., Venus). His work bridges geophysics, glaciology, and computational methods, addressing both Earth and extraterrestrial systems. Prof. Pritchard has received recognition such as the William Bowie Lecture (2022, 2023). His projects often involve international collaborations, including the CEOS Volcano Demonstrator initiative and the EarthDEM/ArcitcDEM projects. He also engages in geothermal energy research and seismic monitoring in Ithaca, NY.
Prof. Ivan Martinovic is a Professor of Computer Science at the University of Oxford's Department of Computer Science, holding a Fellowship at the institution. He specializes in cyber-physical systems security, wireless network security, and behavioral biometrics. His research focuses on authentication mechanisms, intrusion detection, and trade-offs between security and performance in systems like satellite communications, EV charging infrastructure, and aviation networks. Education: PhD (TU Kaiserslautern); MSc (TU Darmstadt, Germany). Prior roles include postdoctoral research at UC Berkeley (2011) and UC Irvine (2009–2010), supported by a Carl-Zeiss Foundation Fellowship (2009–2011). He has also been an associate lecturer at TU Kaiserslautern. Research Interests: Cyber-physical systems security, wireless networks, behavioral biometrics (e.g., continuous authentication via physiological signals), robust communication protocols, and analysis of security vs. performance trade-offs in distributed systems. Technologies include software-defined radios, NFC/RFIDs, and EEG/eye-tracking devices. Scientific Awards: Carl-Zeiss Foundation Fellowship (2009–2011). Advising & Grants: No explicit student listings; however, his work involves interdisciplinary collaborations and has been funded by government and industrial grants. His research spans labs and teams focused on satellite cybersecurity, smart infrastructure security, and biometric systems. Labs/Teams: Engages with groups exploring satellite communication security, EV charging infrastructure vulnerabilities, and behavioral authentication systems, though specific lab names are not disclosed in the text.
Professor Michael Milford is a robotics and computer vision expert at Queensland University of Technology (QUT), serving as Joint Director of QUT's Centre for Robotics. His research bridges robotics, neuroscience, and computer vision, focusing on biologically inspired navigation systems for autonomous vehicles and drones. He has pioneered projects like SeqSLAM and RatSLAM, emphasizing the synergy between biological intelligence and robotic systems. Research Interests: Milford explores navigation algorithms inspired by animal behavior, energy-efficient neural networks, and autonomous systems. His work aims to create robots capable of operating in dynamic environments through interdisciplinary collaboration with institutions like MIT, Harvard, and NASA's Jet Propulsion Laboratory. Awards & Recognition: Awarded the 2019 Batterham Medal and a $2.7M Australian Laureate Fellowship for his project on GPS-independent positioning systems. His work has produced highly cited papers in robotics and computer vision, including breakthroughs in visual SLAM and place recognition under varying conditions. Teaching & Collaboration: Milford mentors students in robotics and AI, launching initiatives like the STEM Storybook to inspire youth. He collaborates globally, emphasizing cross-disciplinary research to bridge gaps between fundamental and applied sciences. Labs & Projects: Leads QUT's Centre for Robotics, advancing technologies for autonomous systems. His projects explore neuromorphic computing, SLAM systems, and bio-inspired navigation, with applications in defense, transport, and environmental monitoring.
Calin Belta is the Brendan Iribe Endowed Professor of Electrical and Computer Engineering and Computer Science at the University of Maryland, College Park. He is affiliated with the Institute of Systems Research (ISR) and the Maryland Robotics Center (MRC), and holds a Research Professor position at Boston University's College of Engineering. His work bridges control theory, formal methods, and machine learning to ensure safety in cyber-physical and data-driven systems, with applications in robotics, autonomous driving, and systems biology. Research Interests: Focus on dynamics and control theory, formal methods for verification and control synthesis, robotics, autonomous systems, and synthetic biology. Recent projects include PROGENIC (collaborating with MIT, UChicago, and UDelaware) and safety-critical control for heterogeneous robotic teams. Key Achievements: General Chair of the 2025 MRC Symposium, recipient of AFOSR Young Investigator Award (2008), NSF CAREER Award (2005), and IEEE Fellow. His work on formal methods for autonomous systems has led to impactful tools for safety assurance in robotics and AI. Grants: NSF EFRI PROGENIC grant (2024), multiple industry partnerships. Advising: Mentored students like Wenliang Liu (PhD 2024, now at Amazon), and collaborator Marius Kloetzer (shared HSCC Test of Time Award 2025). Labs/Teams: Maryland Robotics Center, Institute for Systems Research, and Boston University collaborations.
Dr. Saad Khan is a Senior Lecturer in Cyber Security at the Department of Computer Science, School of Computing and Engineering, University of Huddersfield, United Kingdom. He is an active researcher and educator, supervising multiple PhD students and contributing to government-funded cybersecurity projects with Innovate UK, DCMS, and DASA. He is also a Fellow of the Higher Education Academy and serves on program committees for major conferences. His research focuses on intelligent systems for cyber security and digital forensics. Key areas include Security Information and Event Management (SIEM), access control, authentication, vulnerability assessment, anomaly detection, and image forensics. He aims to develop automated software tools that enhance digital infrastructure resilience against modern cyber threats. The recent publications reflect a strong trend in applying machine learning and AI to cybersecurity challenges, particularly in IoT security, zero-day attack detection, and human-centric security awareness. His work bridges technical innovation with practical implementation in real-world environments. Scientific Awards: Fellow of the Higher Education Academy Dr. Khan actively supervises PhD students and contributes to research grants through collaborations with UK government agencies. He has led work in three major funded projects and regularly reviews for top-tier journals and conferences. He is a member of the Centre for Cybersecurity at the University of Huddersfield, where he collaborates on interdisciplinary research initiatives focused on secure digital transformation and intelligent defense systems.
