Julien Guyon is a researcher at the Applied Probability team of CERMICS (École des Ponts ParisTech), where he joined in September 2022 after 16 years as a quantitative researcher in finance at Société Générale and Bloomberg L.P. He held adjunct professor roles at Columbia University and NYU’s Courant Institute (2015–2022), as well as at Université Paris Diderot and École des Ponts ParisTech. He serves as an Associate Editor for Finance & Stochastics , SIAM Journal on Financial Mathematics , and Journal of Dynamics and Games , and is a Louis Bachelier Fellow. Research Interests: Nonlinear option pricing, volatility modeling, optimal transport, numerical probability, and sports analytics (e.g., FIFA/UEFA competition design). Key Contributions: Developed a fairer FIFA World Cup draw method adopted by FIFA/UEFA, and pioneered joint calibration of S&P 500/VIX smiles using stochastic volatility models. His work bridges financial mathematics and real-world applications in sports. Awards: Louis Bachelier Fellow (2022). Advising & Grants: While specific grants or students are unmentioned, his research has significantly influenced financial markets and sports tournament design through collaborative projects with institutions like CERMICS and his industry work.
Myles H.M. Menz is a researcher at James Cook University (JCU) with a focus on insect ecology, conservation biology, and technological applications in ecological monitoring. His work spans diverse topics including insect migration patterns, pollination dynamics, and the impacts of environmental stressors like pesticides and light pollution. He collaborates internationally on projects involving radar entomology, animal-borne sensors, and ecological genetics. Key research interests include the migration strategies of insects such as hoverflies, moths, and dragonflies, as well as conservation challenges facing endangered species like the orchid Caladenia xanthochila. His studies often integrate cutting-edge technologies (e.g., radar tracking, genomic analysis) to understand ecological processes at both individual and community levels. Notable contributions include demonstrating how hoverflies use sun compass navigation during autumn migration and revealing how insecticide exposure alters gene expression in honeybees. Menz also emphasizes interdisciplinary approaches, such as developing global databases for metacommunity ecology and advocating for landscape-scale ecosystem restoration frameworks. His work bridges applied and theoretical ecology, addressing critical issues like pollinator decline, urban biodiversity, and the ecological consequences of human activities.
Dr. Dorota Jegorow is an Assistant Professor at the Department of Econometrics and Statistics , Institute of Economics and Finance , within the Faculty of Social Sciences at the John Paul II Catholic University of Lublin , Poland. Specializes in Econometrics , Regional Development , and European Cohesion Policy Active in Entrepreneurship , Public Finance , and Digital Technology Applications in socio-economic contexts Recipient of 2022 National Award for research on cryptocurrency volatility
Prof. Edy Tri Baskoro, M.Sc., Ph.D., is a faculty member at the Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology. His academic career spans combinatorics, graph theory, and discrete mathematics, with extensive research on Ramsey graphs, metric dimensions, and graph labelings. Education: Bachelor's from ITB (1987), Master's from University of New England (1992), Ph.D. from University of Newcastle (1996) His research focuses on combinatorial structures, including Ramsey minimal graphs, partition dimensions, irregularity strength, and quadratic embedding constants. Key subfields include tree graphs, path-cycle Ramsey problems, and algorithmic graph theory. Recent publications address edge-locating colorings, unicyclic Ramsey graphs, and applications of graph theory in educational programs. He has contributed to teacher training initiatives in Lombok, Cirebon, and Makassar, as well as textbook development for machine learning. His work involves collaborations in graph theory research and projects like PKR Graph Theory for Nation Building. While no specific awards are documented in the provided text, his contributions to combinatorial research and mathematics education in Indonesia are significant.
Anke Bosse is a Professor at Alpen-Adria-Universität Klagenfurt, holding positions in the Faculty of Cultural and Educational Sciences and the Department of Linguistics and Literature. She leads the Robert Musil Institute for Literary Research and the Carinthian Literary Archive. Her research focuses on literary writing processes, cultural memory, German literature from the 18th to 21st centuries, and intermediality. She has contributed to over 35,000 publications, with recent work spanning robotics, legal commentaries, and educational theory. Her current projects include studies on media literacy and archival practices. Bosse’s work bridges literary analysis with interdisciplinary approaches, emphasizing the intersection of cultural heritage and modern digital methods. Education: Not explicitly listed in the provided text, but inferred through her academic rank and publications. Research Interests: Editions of literary works, archival methodologies, intertextuality, and transnational cultural studies. Her recent articles explore topics like multi-robot systems and legal frameworks for startups, reflecting her interdisciplinary reach. Grants & Projects: Leads projects such as the citizen science initiative #NoFakeFacts! and contributes to legal commentary on tax and corporate law. Active in collaborative research with institutions like the Austrian Research Promotion Agency (FFG). Labs/Teams: Directs the Robert Musil Institute, a hub for literary research and archival work in Carinthia.
Erika L.C. King is an Associate Professor of Mathematics and Computer Science at Hobart and William Smith Colleges (HWS), where she has been a faculty member since 2001. She earned her Ph.D. and M.S. from Vanderbilt University and her A.B. from Smith College. Her office is located in Lansing Hall, and she can be reached at eking@hws.edu or (315) 781-3355. Dr. King specializes in graph theory with research interests focusing on domination theory of graphs, well-covered graphs, and zero forcing in graphs. Her scholarly work has explored various aspects of graph structures, including vertex-magic edge labelings, plane triangulations, and 4-regular, 4-connected, claw-free graphs. She has supervised numerous undergraduate research projects through the HWS-REU program, mentoring students like Rayan Ibrahim, Rebecca Jackson, and others who have co-authored publications with her. Her recent publications demonstrate a continued focus on domination theory and well-covered graphs, with her 2024 paper 'Well-Forced Graphs' representing the latest development in this line of research. Her work spans both theoretical developments and practical applications of graph theory concepts. Dr. King is actively involved in the mathematical community through memberships in the Association for Women in Mathematics, Mathematical Association of America, and American Mathematical Society. She has organized departmental colloquia and supported students attending conferences like the Nebraska Conference for Undergraduate Women in Mathematics. She has taught a wide range of mathematics courses from introductory calculus to advanced topics in graph theory and abstract algebra. Her teaching portfolio includes MATH 110 (Discovering in Mathematics), MATH 130-131 (Calculus I-II), MATH 204 (Linear Algebra), MATH 232 (Multivariable Calculus), MATH 278 (Number Theory), and multiple sections of MATH 313 and MATH 571 (Graph Theory).
Jeffrey W. Alstete serves as Professor in the Management Department at Iona University's LaPenta School of Business, where he teaches strategic management, organizational behavior, and small business management courses. His academic leadership includes previous roles as Associate Dean in the School of Business, where he directed AACSB accreditation and launched online MBA programs. His educational background features an Ed.D. from Seton Hall University, MBA and MS from Iona University, and BS in Business Administration from St. Thomas Aquinas College. Professional experience spans academic administration, corporate training program development, and financial analysis roles at Valley National Bank and Property Evaluation Services. Alstete's research focuses on business strategy implementation, knowledge management systems, higher education administration, and entrepreneurial development. His work examines simulation-based learning effectiveness, neurodiverse student engagement, and organizational memory systems, with particular emphasis on practical applications for business education and strategic decision-making. His publications demonstrate consistent scholarly output across management journals, with recent work analyzing crisis leadership dynamics, generational entrepreneurship patterns, and disruptive innovation learning frameworks. The research trajectory shows increasing integration of educational technology with traditional management theory. Br. William B. Cornelia Distinguished Faculty Award (2023) Best Empirical Paper Award, Eastern Academy of Management (2023) Catherine McCabe Award for Teaching Excellence (2014) Literati Club Outstanding Paper Award (2002) ACHE National Research Grant (1995) As Co-Editor of Quality Assurance in Education and Editorial Board member for Benchmarking: An International Journal , Alstete contributes to academic discourse while maintaining active research partnerships. His work with student business simulation teams has produced multiple global top-100 rankings, demonstrating practical application of his pedagogical theories. Current projects explore intelligent agent applications in knowledge management and neurodiverse learning accommodations in management education.
Chris Develder is an Associate Professor with the research group IDLab in the Department of Information Technology (INTEC) at Ghent University - imec, Ghent, Belgium. He received his MSc degree in computer science engineering and PhD in electrical engineering from Ghent University in Jul. 1999 and Dec. 2003 respectively (as a fellow of FWO). He has held research visitor positions at UC Davis, CA, USA (Jul.-Oct. 2007) and at Columbia University, NY, USA (Jan. 2013 - Jun. 2015). Prof. Develder leads two research teams within the Internet Technology and Data Science Lab (IDLab): one focused on converting text to knowledge (NLP, primarily information extraction using machine learning), and another on data analytics and machine learning for smart grids. His Text-to-Knowledge (T2K) research group has a strong track record in information extraction across various domains including news, human resources, and biomedical applications, as well as text classification tasks such as sentiment analysis. More recently, the group has expanded into conversational agents and generative models for educational applications. With his team, Prof. Develder has published over 200 papers in international journals and conferences including EMNLP, CoNLL, EACL, ACL, ECIR, CIKM, WSDM, WWW, and NIPS. His recent publications demonstrate a growing focus on practical applications of NLP in healthcare (personality style recognition from speech, biomedical adverse drug event extraction), education (question generation, gap-filling exercises), and labor market analysis (career path prediction, skill extraction). His work bridges theoretical advances in machine learning with real-world applications across multiple domains. Prof. Develder actively supervises PhD students and has co-supervised numerous successful doctorates, including Maarten De Raedt (2024), Semere Kiros Bitew (2024), Yiwei Jiang (2024), Amir Hadifar (2023), and Klim Zaporojets (2022). His former students have gone on to work at organizations including EarlyTracks, Zoom, Nokia Bell Labs, Clarivate, and various academic institutions.
Jiří Kosinka is an Associate Professor (Tenure Track) at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Scientific Visualization and Computer Graphics research group. His roles include coordinating and lecturing in Computer Graphics and Advanced Computer Graphics courses, as well as serving as an editor for journals like Computer-Aided Design and Graphical Models . Academic Position: Associate Professor, Tenure Track Affiliations: Bernoulli Institute, Faculty of Science and Engineering Research Group: Scientific Visualization and Computer Graphics Education PhD in Mathematics (2006), Charles University, Prague MSc in Mathematics (2002), Charles University, Prague Research Interests Kosinka's work focuses on geometric modeling, computer graphics, and image processing. He develops algorithms for subdivision surfaces, numerical quadrature, and fluid simulation, with applications in surgical planning and medical visualization. His research bridges theoretical contributions with practical implementations in CAD systems and real-time rendering. Conference Contributions Co-organizer of DGMM 2025 (Discrete Geometry and Mathematical Morphology) in Groningen Program Chair for AniNex 2022/2023 (Next Generation Computer Animation) IPC member for SGP, SPM, Pacific Graphics, and other key conferences Editorial Roles He serves on the editorial boards of Computer-Aided Design and Graphical Models , and has guest-edited special issues in Computer Aided Geometric Design . Labs & Teams He leads the Scientific Visualization and Computer Graphics group, collaborating on projects like BoneStory (3D surgical planning) and fluid dynamics simulations. His lab focuses on advancing geometric algorithms and their real-world applications.
Kento Sato is a researcher specializing in High-Performance Computing (HPC), with a focus on checkpointing systems, data compression, and parallel computing optimization. His work addresses challenges in fault tolerance, algorithmic efficiency, and resource management in large-scale computing environments. Collaborating with institutions like the Joint-Laboratory of Extreme Scale Computing, he explores trade-offs between compression efficiency and hardware costs, as well as automatic variable identification for checkpointing. His contributions span theoretical advancements and practical implementations, with notable publications in venues such as SC, IPDPS, and the International Journal of High Performance Computing Applications. Key Research Themes: Checkpointing protocols, lossy compression for scientific data, HPC workflow optimization. Long-term Collaboration: Regular co-authorship with experts like Satoshi Matsuoka and Martin Schulz. Publications consistently highlight innovations in fault tolerance mechanisms, adaptive hardware design, and scalable algorithms for machine learning and distributed systems.
Dr. Yan Chen is an Associate Professor in Engineering at The Polytechnic School, Arizona State University (ASU), where he founded and directs the Dynamic Systems and Control Laboratory (DSCL). His academic journey includes a Ph.D. in Mechanical Engineering from The Ohio State University (2013), an M.S. in Mechanical Engineering from Rice University (2009), and dual M.S. and B.S. degrees in Control Science and Engineering (with honors) from Harbin Institute of Technology, China (2006, 2004). Ph.D., Mechanical Engineering, The Ohio State University, 2013 M.S., Mechanical Engineering, Rice University, 2009 M.S., Control Science and Engineering (Honors), Harbin Institute of Technology, China, 2006 B.S., Control Science and Engineering (Honors), Harbin Institute of Technology, China, 2004 Dr. Chen's research spans multiple critical areas in modern vehicle technology, with primary focus on design, modeling, estimation, control, optimization, and safety of dynamic systems. His work specifically targets connected and automated ground vehicles, electric/hybrid vehicles, multi-agent mobile systems, energy systems, and mechatronic applications. Recent research has emphasized tire blowout modeling and control, vehicle safety systems, and flocking control for multi-vehicle coordination. His laboratory actively develops innovative control frameworks that integrate machine learning with traditional control methods to enhance vehicle safety and performance. Analysis of Dr. Chen's recent publications (2023-2025) reveals a strong emphasis on safety-critical control systems for automated vehicles, particularly focusing on tire blowout scenarios, vehicle flocking behavior, and multi-agent coordination. His work increasingly integrates learning-based approaches with traditional control theory, demonstrating a shift toward more adaptive and robust control frameworks. The research spans both theoretical developments in control theory and practical applications in automotive systems, with growing attention to satellite-based localization and energy management for electric vehicles. 2020 SAE Ralph R. Teetor Educational Award 2019 DSCC Automotive and Transportation Systems Best Paper Award NSF-PFI grant on Development and Integration of Tire Blowout Modeling and Control in Advanced Driver Assistance Systems (2024) Dr. Chen has successfully advised multiple graduate students, including recent PhD graduate Dr. Ao Li who joined General Motors. His research has been generously funded by major federal agencies including NSF, DOE, ONR, and ACA, as well as industrial partners such as General Motors, Intel, SRP, and MathWorks. Current research projects focus on tire blowout modeling, vehicle safety systems, and automated vehicle coordination. He serves as Associate Editor for several prestigious journals including IFAC Mechatronics and IEEE Transactions on Vehicular Technology, and chairs the ASME Automotive and Transportation Systems Technical Committee. The Dynamic Systems and Control Laboratory (DSCL) at ASU is a thriving research environment focused on cutting-edge vehicle control systems. The lab actively recruits 1-2 PhD students annually with strong backgrounds in vehicle dynamics, control theory, and optimization. Current research directions include tire blowout modeling, vehicle safety systems, multi-agent coordination (flocking control), and energy optimization for electric vehicles. The lab maintains strong industry connections, particularly with automotive companies like General Motors, ensuring research relevance to real-world applications.
Dominique de Werra is an Honorary Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), affiliated with the Department of Mathematics within the Faculty of Basic Sciences. He holds an Engineering degree and a Doctorate in Operations Research from EPFL. His career includes roles as Full Professor (1979–2008), Vice-President (1991–2000), and Dean of International Relations (2000–2004). He has served as President of IFORS (2010–2012) and EURO (1987–1988), and led academic networks like CLUSTER and EURECOM. His research focuses on Operations Research, Combinatorial Optimization, Graph Theory, and applications in scheduling, logistics, and multidisciplinary fields. He has authored over 200 technical publications, co-authored textbooks like Operations Research for Engineers , and edited numerous journal special issues. Awards include Honorary Doctorates from Paris-Dauphine, Poznan, and Fribourg, as well as the EURO Gold Medal (1995) and Distinguished Service Medal (2012). de Werra has supervised over 140 master’s theses and 350 student projects. He has held visiting professorships worldwide and served on editorial boards of journals like Discrete Applied Mathematics and European Journal of Operational Research . His contributions span academic leadership, conference organization, and interdisciplinary collaborations in archaeology, zoology, and engineering.
FRANCO SCARSELLI is a Full Professor at the University of Siena, affiliated with the Department of Information Engineering and Mathematical Sciences. His primary research focuses on Graph Neural Networks (GNNs), machine learning applications in IoT, blockchain, bioinformatics, and medical imaging. He has contributed extensively to the theoretical foundations of GNNs, including their expressive power and VC dimensions. His teaching roles include courses on Advanced Machine Learning for the Master's program in Artificial Intelligence and Automation Engineering, as well as Information Systems for undergraduate Management Engineering students. He has been actively involved in curriculum development since at least 2021/2022. Research highlights include interdisciplinary work on agrifood supply chain traceability using IoT and blockchain, molecular property prediction with GNNs, and semantic analysis of diffusion models. Key collaborations involve institutions like the University of Siena and industry partners in smart logistics and healthcare. His publications span over two decades, with recent contributions emphasizing the theoretical underpinnings of GNN architectures and their applications in dynamic graphs, medical diagnostics, and industrial fault detection. He has also pioneered open-source tools like GNNKeras for graph neural network implementations.
Dr. Keisuke Okumura is a Visiting Professor at the University of Cambridge (as a JSPS overseas fellow) and a researcher at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. He holds a Ph.D. in Artificial Intelligence from Tokyo Institute of Technology (2023), supervised by Prof. Xavier Défago. His research focuses on multi-agent systems, particularly in path planning and coordination for autonomous agents, leveraging techniques from planning, search algorithms, machine learning, and distributed computing. Research Interests: His work addresses challenges in multi-agent pathfinding (MAPF), real-time trajectory optimization, and scalable solutions for large-scale robotic systems. He explores hybrid approaches combining sampling-based methods with search algorithms, as well as fault-tolerant offline planning strategies. Key areas include dynamics-aware trajectory deformation, time-independent execution frameworks, and machine learning integration for enhanced pathfinding efficiency. Publications: His recent work emphasizes advancements in algorithms like LaCAM and D4orm, targeting real-time performance and scalability. Themes include optimizing multi-robot motion, integrating diffusion models for trajectory refinement, and addressing challenges in large-scale automation. His articles reflect a blend of theoretical contributions and practical implementations in robotics and autonomous systems. Affiliations: Alongside his visiting role at Cambridge’s Department of Computer Science and Technology, Dr. Okumura contributes to AIST’s research initiatives. His collaborations span academic and industrial partners, focusing on applied robotics and intelligent systems.
Liang Zheng is a Senior Lecturer in the School of Computing at The Australian National University (ANU). He holds a Computer Science Futures Fellowship and an ARC DECRA Fellowship. His research focuses on computer vision applications such as person re-identification and medical image understanding, alongside fundamental challenges in dataset-level learning and synthetic data analysis. Zheng has contributed to influential datasets like Market-1501, PRW, and MARS, advancing person re-identification and multi-camera tracking. He has served as Area Chair for CVPR, ECCV, and ACM Multimedia, and is an Associate Editor for IEEE T-CSVT. Education: PhD (Electrical Engineering) from Tsinghua University (2015), Bachelor of Science (Life Science) from Tsinghua University (2010). His research integrates deep learning and generative models, addressing challenges in image generation, adversarial robustness, and multi-agent systems. Notable awards include the Computer Science Futures Fellowship (ANU) and ARC DECRA Fellowship (2020). Key contributions include pioneering work on re-identification datasets and methods, as well as advancements in cross-modal retrieval and domain adaptation. Ongoing research emphasizes scalable models, synthetic data generation, and ethical AI practices.
