Jarno Vanne is a Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on video coding standards, real-time systems, and hardware acceleration, particularly in the context of FPGA implementations and open-source tools. He leads projects involving VVC (Versatile Video Coding), V-PCC (Volumetric Video Coding), and HEVC (High Efficiency Video Coding), with an emphasis on efficiency, low latency, and machine learning integration. Key research interests include point cloud compression, saliency-guided encoding, parallelization schemes, and real-time video communication protocols. His work often addresses challenges in multi-party video streaming, embedded systems, and encryption mechanisms for privacy protection. He has contributed to open-source projects like the UVG dataset, Kvazaar encoder, and CiThruS simulation frameworks. Recent publications highlight advancements in VVC intra encoding optimizations, machine learning-driven partitioning schemes, and FPGA-accelerated solutions for edge computing. His research bridges theoretical video coding algorithms with practical implementations, aiming to improve compression efficiency while maintaining real-time performance.
Hongbo Jiang is a Distinguished Professor and Vice Dean of the College of Computer Science and Electronic Engineering at Hunan University, China. He holds concurrent roles as Director of the Trusted Systems and Networking Key Laboratory of Hunan Province and Director of the Hunan International Technical Cooperation Base for High-Performance Computing and Distributed Systems. His academic journey includes tenures as a Professor at Huazhong University of Science and Technology and a Hong Kong Scholar Research Fellow at The Chinese University of Hong Kong. Education: PhD in Computer Science (Case Western Reserve University, 2008), B.S./M.S. in Mathematics (Huazhong University of Science and Technology, 2002). Research Interests: Distributed systems, mobile computing, smart sensing, wireless networks, IoT, and edge computing. Ongoing projects include mobile/wireless applications, data science in IoT, and edge computing platforms. His work emphasizes practical implementations such as DriverSonar for driving safety and SmileAuth for biometric authentication. Key Achievements: Elected Member of Academia Europaea (2022), Fellow of AAIA, IET, and BCS. Notable awards include the Wu Wenjun Science and Technology Award (2020) and multiple best paper recognitions. Over 100+ publications in top venues like ACM MobiCom, IEEE/ACM Transactions. Professional Contributions: Editorial roles across 8+ journals including IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Conference leadership includes co-founding ACM TURC and EAI ICECI. Active in technical committees for INFOCOM, MOBIHOC, and ICDCS. Labs/Teams: Leads research groups focused on networking, IoT, and edge computing. Current openings for PhD/MSc students and PostDoc researchers with strong mathematical and systems backgrounds.
Brian D. Gregory is a Professor of Biology at the University of Pennsylvania's School of Arts & Sciences. His research focuses on RNA modifications, computational biology, and plant genetics, particularly studying how RNA modifications regulate gene expression in plants and animals. He holds a Ph.D. from Harvard University (2005) and a B.S.A. from the University of Arizona (2000). Research Interests: RNA epitranscriptomics (e.g., m6A, NAD+ caps) RNA secondary structure and protein interactions Genomic approaches to study plant stress responses Development of high-throughput sequencing tools like PIP-seq Recent Work Highlights: Recent studies include analyzing pathogen-induced RNA modifications' role in plant immunity (Plant Cell 2023), global RNA structure/protein interaction mapping, and epitranscriptomic dynamics in drought tolerance. His lab's work bridges computational methods with molecular genetics to uncover post-transcriptional regulatory mechanisms. Lab & Collaborations: The Gregory Lab uses Arabidopsis thaliana as a primary model organism but also explores animal systems. They collaborate with institutions like Cornell University and have developed protocols published in Current Protocols in Molecular Biology. Teaching: BIOL 4231: Genome Sciences and Genomic Medicine BIOL 6010: Communication for Biologists
Adam Doupé is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) and Director of the Center for Cybersecurity and Trusted Foundations (CTF). He holds a Ph.D. and M.S. in Computer Science from the University of California, Santa Barbara. His research focuses on cybersecurity, vulnerability analysis, web security, and hacking competitions. Notable awards include the NSF CAREER Award (2017), Best Teacher Award, and Outstanding Assistant Professor Award from ASU's Fulton Schools of Engineering. Education: Ph.D. and M.S. in Computer Science, UC Santa Barbara (2014, 2009). Research emphasizes automated vulnerability analysis, binary analysis, and cybersecurity education. Key contributions include frameworks like SCAMNet and SENSAI for fraud detection, and tools like Fuzz to the Future for uncovering future vulnerabilities. Recent articles highlight advancements in phishing ecosystem analysis, browser fingerprinting mitigation, and compiler-aware decompilation. Awards reflect his impact in both teaching and research. Advising and grants support his work in secure systems and ethical hacking. He co-leads the SEFCOM lab with Drs. Ahn, Shoshitaishvili, Wang, and Bao, and hosts CTF Radiooo for cybersecurity discussions.
Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.
Dimitris Mitropoulos is an Assistant Professor at the National and Kapodistrian University of Athens (NKUA) in the Department of Business Administration, where he teaches courses on Distributed Ledger Technologies, Data Security and Privacy, Algorithms and Business Analytics, and Introduction to Programming. He also serves as Head of the Reliability Engineering Directorate at the National Infrastructures for Research and Technology (GRNET), Greece's national research and education network organization. Previously, he was a Postdoctoral Researcher in the Computer Science Department at Columbia University. Dr. Mitropoulos received his Ph.D. degree in Secure Software Development Technologies from the Athens University of Economics and Business (AUEB) in 2014. His doctoral research was supported by the Heracleitus II Scholarship, co-financed by the European Union and Greek national funds. He is a member of prestigious professional organizations including ACM, IEEE, and USENIX. Dr. Mitropoulos conducts pioneering research at the intersection of software engineering and cybersecurity, with particular expertise in secure software development, vulnerability analysis, and blockchain security. His work spans multiple dimensions of software security including code injection attacks, infrastructure as code security, smart contract analysis, and dependency management in software ecosystems. His research methodology combines static and dynamic analysis techniques with empirical studies of real-world software systems, particularly focusing on Java, Python, and Solidity ecosystems. His recent work has made significant contributions to understanding security vulnerabilities in modern software development practices and infrastructure management. Dr. Mitropoulos has received numerous prestigious awards for his research contributions, including the Research Excellence Award from NKUA (2025), Distinguished Paper and Artifact Awards at PLDI '22, Best Data Showcase Award at MSR 2018, and multiple postdoctoral research funding scholarships. His work on "Finding typing compiler bugs" was recognized with both Distinguished Paper and Artifact Awards at PLDI '22, highlighting the significance and reproducibility of his research. He has also received recognition for his service to the academic community, including a Certificate of Appreciation from ESEC/FSE '21 for his contributions to conference organization. Dr. Mitropoulos has been actively involved in securing research funding and leading significant research projects. He currently serves as Principal Investigator for the SecOPERA project (2023-Today), funded by the European Commission under Horizon Europe. Previously, he contributed to several major EU and US-funded projects including eSSIF-Lab (2019-2022), FASTEN (2019-2022), PRIViLEDGE (2018-2021), CERTCOOP (2017-2020), PANORAMIX (2016-2019), and TREDISEC (2016-2018). His research has been supported by diverse funding sources including the European Commission's Horizon 2020 program, the National Science Foundation, and the Defense Advanced Research Projects Agency (DARPA). Dr. Mitropoulos plays an active role in the international research community through various leadership positions. He serves on program committees for top-tier conferences including OOPSLA (2026), ICSE (2026), ESEC/FSE (2025), and ISSTA (2025). He has previously served as Workshop Co-Chair for ISSTA 2025 and Student Volunteer Chair for ESEC/FSE 2021. His contributions to mentoring the next generation of researchers include serving as a mentor for the ICSE Student Mentoring Workshop (2022) and supervising Google Summer of Code projects (2017).
David Henderson is the Director of the Cyclone Testing Station (CTS) in the School of Engineering and Physical Sciences at James Cook University, Australia. He has over two decades of experience as a research engineer specializing in the performance of low-rise buildings under extreme wind conditions. He previously served as the CTS Research Fellow and Manager, and was seconded as a Postdoctoral Researcher at the University of Western Ontario, Canada, working on full-scale house testing under simulated wind loads. His work bridges engineering research, disaster assessment, and policy development. David's research focuses on wind engineering, structural resilience, and disaster mitigation. His key interests include cyclonic wind loading, internal and external pressure dynamics in buildings, fatigue failure of structural connections, and the vulnerability of housing to severe wind events. He has conducted post-disaster surveys across Australia and Canada, assessing damage from cyclones, tornadoes, and earthquakes. His research has direct applications in building codes, retrofitting strategies, and community risk reduction. The recent publications highlight a strong trend in understanding and mitigating wind-induced damage to residential structures, particularly through full-scale testing, modeling of pressure dynamics, and fragility assessment of roofing systems. His work spans experimental, theoretical, and policy-oriented domains, with a growing emphasis on climate change adaptation and community resilience. Topics such as internal pressure design, load sharing in roof frames, and retrofitting for wind resistance are central to his contributions. 14 research awards (specific names not listed) Active member of Standards Australia code committees Invited speaker at national and international conferences Media contributor on storm damage and building safety David has led multiple research projects funded by councils and agencies focused on extreme wind mitigation, data systems (SWIRLnet), and community risk reduction. While formal student supervision is not explicitly listed, he collaborates extensively with researchers such as John Ginger, Korah Parackal, and Daniel Smith. He has contributed to major studies involving wind load testing, housing vulnerability modeling, and climate adaptation planning. David is a key figure in the Cyclone Testing Station, leading its full-scale testing program and contributing to the development of software for controlled load and measurement systems. His team conducts wind risk assessments for communities and large installations, incorporating terrain analysis and retrofitting evaluations. The CTS serves as a national resource for wind engineering research and disaster resilience innovation.
Natalia Villanueva-Rosales is an Associate Professor in the Department of Computer Science at The University of Texas at El Paso (UTEP). As Co-Principal Investigator at the NSF-funded Cyber-ShARE Center of Excellence, she leads the iLink Research Group focusing on semantic technologies and smart city initiatives. Ph.D. in Computer Science, Carleton University (2011) M.Sc. in Artificial Intelligence, University of Edinburgh (2005) B.Sc. in Computer Science & Statistics, Universidad Panamericana & CINVESTAV-IPN (2002) Her research bridges Semantic Web technologies with Smart Cities applications, particularly in Water Sustainability and Senior Mobility . Key projects include ontology-based frameworks for freight performance data integration and community-driven smart mobility solutions. Recent publications demonstrate her interdisciplinary approach across Environmental Informatics (2022-2025) and Urban Mobility (2019-2022). She holds editorial and leadership roles in semantic science initiatives while actively mentoring through the ACM-W WICS student group. 2019 HEENAC Education Award 2019 NCWIT Undergraduate Research Mentoring Award Her NSF grants include IRES-1658733 for US-Mexico Smart Cities collaboration and OAC-1835897 for the SWIM water sustainability project. The iLink Research Group under her leadership develops ontological frameworks for cross-domain data integration and trust establishment in collaborative environments.
Karen Hampson is a Senior Lecturer in Optometry at the University of Manchester, serving as the first-year Optics Theme Lead. Her research focuses on adaptive optics systems for vision science, particularly using retinal imaging technology for early diagnosis of neurodegenerative and psychiatric diseases. She is a member of the Consortium for Vision and Oculomics in Psychiatry and co-founder of the European Adaptive Optics Summer School. Education: MPhys (Swansea University, 2000), PhD in Physics (Imperial College London, 2004), Post-Graduate Certificate in Higher Education Practice, and SEDA Professional Development Award. She trained in Transactional Analysis Psychotherapy and mental health first aid. Research interests include adaptive optics applications across vision science, microscopy, and astronomy. She led an EPSRC-funded project on pre-symptomatic disease diagnosis via ocular biomarkers. Key roles include Chair of Optica’s Applications of Visual Science Technical Group (2021–2024) and Associate Editor for Frontiers in Ophthalmology. Teaching contributions include senior laboratory roles at Oxford’s Physics Department and tutorial leadership at Corpus Christie College. Her work aligns with UN SDG targets for health and innovation.
Sumit Chopra is an Associate Professor at the Grossman School of Medicine , affiliated with the Department of Radiology at New York University. His work focuses on integrating machine learning and artificial intelligence with medical imaging to enhance diagnostic accuracy and clinical decision-making. Research interests include: Deep learning applications in prostate cancer imaging and MRI reconstruction Development of open-access medical imaging datasets (e.g., FastMRI Prostate) Improving biopsy decision strategies via representation learning AI-driven Alzheimer's disease risk prediction using electronic health records Advancements in radiologic assessment for pancreatic cystic lesions Email: Sumit.Chopra@nyulangone.org
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Don Lafreniere is Professor of Geography and GIS at Michigan Technological University, where he also serves as Graduate Director and Director of the Geospatial Research Facility. He is affiliated with the Department of Social Sciences in the College of Sciences and Arts. His interdisciplinary research integrates GIS, historical data, and community engagement to study urban environments, population health, and postindustrial landscapes. PhD, Geography, University of Western Ontario BS, History, Eastern Michigan University BS, Geography, Eastern Michigan University His research interests include Historical GIS, Deep Mapping, Public Participatory GIS, children's health and lifecourse epidemiology, deindustrialization, and urban health. He leads the Keweenaw Time Traveler and Historical Environments Spatial Analytics Lab (HESAL), focusing on creating spatiotemporal models of historical urban change. His recent publications (2016–2023) reflect a strong trend in integrating GIS with historical, archaeological, and public health data, particularly in industrial and postindustrial cities. Themes include environmental justice, cumulative hazards, community heritage, and spatial narratives, often using deep mapping and historical spatial data infrastructures. He has received major funding from the National Endowment for the Humanities (NEH), National Science Foundation (NSF), and Social Sciences and Humanities Research Council (SSHRC), serving as Principal Investigator or Co-PI on projects such as the Keweenaw Time Traveler, GRACE, and Three Centuries of Francophone Migration. These grants support transdisciplinary, community-engaged, and public-facing scholarship in the spatial humanities. Labs and initiatives include the Geospatial Research Facility, HESAL, and the Keweenaw Time Traveler, which combine geospatial technologies with historical research and public education.
Brian Ingalls is a Professor in the Department of Applied Mathematics and cross-appointed to Biology at the University of Waterloo. His research applies mathematical and control-theoretic approaches to biological systems, including genetic regulatory networks, microbial communities, and cellular metabolism. Institutional Affiliation: Faculty of Mathematics, University of Waterloo Contact: bingalls@uwaterloo.ca His work focuses on systems biology and synthetic biology , particularly sensitivity analysis of biochemical networks, optimal experimental design, and mathematical modeling of cellular processes. Research funding comes from NSERC and CIHR . Notable contributions include the textbook Mathematical Modeling in Systems Biology (MIT Press, 2013) and the Ingalls Quantitative Cell Biology Lab , which investigates intracellular and intercellular network dynamics through computational and experimental methods. Key Collaborations: iGEM Waterloo, Chemical Engineering, and international synthetic biology networks Advising: Mentored 15+ graduate students and postdocs across applied math, biology, and engineering fields
Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.
Alejandro F. Villaverde is a Ramón y Cajal research fellow in the Department of Systems & Control Engineering at the School of Industrial Engineering, University of Vigo, Spain. He also serves as a Research fellow at CITMAga since 2022. Previously, he worked as a postdoctoral researcher at IIM-CSIC from 2016-2020. His research focuses on the modeling of dynamical systems with particular emphasis on biological applications. Villaverde earned his PhD in Systems and Control Engineering from University of Vigo between 2005 and 2009. His academic career has centered at Spanish institutions with a strong interdisciplinary approach bridging engineering, mathematics, and biology. His primary research interests include systems biology, control theory, and mathematical modeling, with specialized expertise in structural identifiability, observability analysis, and computational tools for dynamic modeling of biological systems. Villaverde's work addresses fundamental challenges in building reliable mathematical models of complex biological processes, with applications spanning immunology to microbial communities. His theoretical contributions have practical implications for improving model reliability and predictive power in biological research. Villaverde has published extensively in top journals including PLOS Computational Biology, Bioinformatics, and IEEE/ACM Transactions on Computational Biology. His recent publications (2023-2025) reveal a consistent research trajectory focused on developing theoretical frameworks for biological model analysis, creating practical software tools, and applying these methods to cutting-edge problems. His work shows particular strength in identifying and addressing fundamental limitations in modeling approaches, especially regarding parameter identifiability and model observability constraints. Among the top 2% Scientists Worldwide 2024 (Stanford University list) Recognition as one of the EEI's top valued instructors at University of Vigo's School of Industrial Engineering Villaverde leads multiple significant research projects including DYNAMO-bio (funded by Ministry of Science, Innovation and Universities), SICOMORO (focusing on symmetries in biological communities), and PREDYCTBIO. His group actively develops open-source software tools such as STRIKE-GOLDD for structural identifiability and observability analysis. The laboratory, part of the BICO research group, includes several researchers and students working on various aspects of dynamic modeling in biology, with recent additions including Mahmoud Shams Falavarjani, Adriana González Vázquez, and multiple interns working on specialized projects.
