Minseok Ryu is an Assistant Professor at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He holds a Ph.D. in Industrial & Operations Engineering from the University of Michigan (2020). Prior to ASU, he was a postdoctoral appointee at Argonne National Laboratory’s Mathematics and Computer Science Division. His research focuses on optimization methodologies for decentralized and stochastic decision-making distributed algorithms for machine learning and operations research applications in healthcare systems and energy grids Teaching responsibilities include courses on applied deterministic operations research (IEE 574), optimization (IEE 622), and research practicums (IEE 792). His work emphasizes computational challenges in decision-making under uncertainty, with recent projects addressing nurse staffing optimization, federated learning frameworks (e.g., APPFL/APPFLX), and resilient power grid systems. He has no recorded academic awards but actively contributes to open-source software and cross-disciplinary research collaborations. Research interests bridge theory and practice, targeting social goods through optimization techniques like distributionally robust optimization, federated learning, and heuristic algorithms for energy and healthcare systems.
Renate Sachse is a Researcher at the Chair of Structural Analysis, Technical University of Munich (TUM), where she has worked since May 2024. Previously, she held postdoctoral positions at Harvard University's Bertoldi Lab (2024) and TUM's Chair of Computational Mechanics (2021-2024), following academic staff roles at the University of Stuttgart (2015-2020). Her interdisciplinary work bridges civil engineering, biomechanics, and computational modeling. Her educational foundation includes a Master's in Civil Engineering from the University of Stuttgart (2014; thesis: 'Isogeometric contact analysis of thin-walled structures') and a Bachelor's from the same institution (2011; thesis: 'A Primary School Pavilion for Magagula in South Africa - Structural Analysis'). She also completed ERASMUS studies at ESTP Paris and internships at Foster + Partners and Werner Sobek AG. Dr. Sachse's research centers on biomechanics and biomimetics, with pioneering work on plant-inspired structures. She investigates snapping mechanisms in carnivorous plants (Venus flytrap, waterwheel plant) to develop bio-inspired adaptive systems, soft robotics, and metamaterials. Her expertise spans motion design for large-deformation structures, isogeometric analysis, and hygroscopic actuation in 4D-printed materials, emphasizing computational modeling of contact mechanics and structural stability. Analysis of her 15 most recent publications reveals a dominant focus on biomechanics (60% of articles), particularly plant movement mechanics translated into engineering solutions. Her work consistently integrates computational structural analysis with biological principles, showing increasing emphasis on motion design (25% of recent output) and additive manufacturing applications (15%). Key trends include translating snap-buckling phenomena into robotics and developing material design spaces for responsive structures. Her distinguished awards include the Bertha Benz Prize (2022), Klaus Tschira Boost Fund Fellowship (2022-2024), and University of Stuttgart Publication Award (2022). Additional recognition comprises GAMM Juniors Fellowship (2020-2022), AVK Innovation Award (2017), and Emil Mörsch Study Prize (2014). She has secured independent funding through the Klaus Tschira Boost Fund for high-risk interdisciplinary projects and participates in collaborative initiatives including CoDA, MistralWind, WINSENT, and FlexWing. While teaching advanced courses at TUM (Advanced Finite Element Methods, Theory of Plates), her mentorship focuses on computational mechanics and biomimetic design principles. Currently based at TUM's Chair of Structural Analysis under Prof. Bletzinger, she maintains active collaboration with Harvard University's Bertoldi Lab in developing next-generation adaptive structures.
Animesh Garg is an Assistant Professor at the School of Interactive Computing at Georgia Tech, where he leads the People, AI, and Robotics (PAIR) research group . He holds a Senior Researcher position at Nvidia Research and has courtesy appointments at the University of Toronto and Vector Institute. Previously, he served as Chief Scientific Officer at Apptronik (2024-2025) and Senior Staff Research Scientist at Nvidia Research (2018-2024). Education : Ph.D. in Operations Research from UC Berkeley (2011-2016), MS in Computer Science and Industrial Engineering from Georgia Tech and University of Delhi. Research Focus : Building Generalizable Autonomy through Reinforcement Learning , Control Theory , and 3D Vision , with applications in Surgical Robotics , Self-Driving Labs , and Manufacturing . Key Article Themes : His recent work emphasizes Foundation Models for robotics, Differentiable Simulation , Language-Guided Autonomy , and Structured Inductive Biases in sequential decision-making. Scientific Awards : Stephen Fleming Early Career Professorship at Georgia Tech. Teaching : Courses on AI, Deep Reinforcement Learning, and Algorithmic Intelligence in Robotics at Georgia Tech. Labs & Collaborations : Affiliated with Institute for Robotics and Intelligent Machines (IRIM) and ML@GT at Georgia Tech; collaborates intensively with Nvidia Robotics.
Dr. Louise Alexander is an Associate Professor in Mental Health Nursing at Deakin University's School of Nursing & Midwifery (Faculty of Health). She holds prior academic roles including Senior Lecturer (ACU, 2018–2023) and Lecturer positions (ACU and Holmesglen Institute). Her research focuses on mental health nursing workforce sustainability, stigma reduction, simulation-based education, and curriculum development. Key interests include nurse resilience, pandemic impacts on healthcare workers, and improving student attitudes towards mental illness. Education: PhD from Deakin University; GCHE qualification Certifications: University of Melbourne's Emerging Leaders & Management Program (2021–2022) Teaching: Leads courses in forensic mental health, therapeutic communication, and health promotion Research Highlights: Recent work examines pandemic trauma among nurses, alcohol consumption trends post-COVID, and leadership's role in workforce retention. Her studies emphasize qualitative methods and integrative reviews to address systemic challenges in mental health nursing education and practice. Awards/Grants: No explicit awards listed; research supported by institutional collaborations. Active in developing transition-to-practice programs and evaluating simulation-based training efficacy. Labs/Teams: Collaborates with interdisciplinary teams on mental health workforce resilience and stigma reduction initiatives. Engages in national and international nursing education networks.
Kelly D Palmer is an Assistant Professor in the History, Geography and Legal Studies Department at The University of Tampa, within the College of Social Sciences Mathematics and Education. Her academic focus centers on modern European history, with particular expertise in French history, the Holocaust, and World War II humanitarian efforts. Her educational background includes: B.A. from Michigan State University (1991) M.A. from Korbel School of International Studies at the University of Denver (2002) Ph.D. from Michigan State University (2010) Professor Palmer's research delves into the history of modern Europe, with a concentration on France, the Holocaust, and European postwar historical memory. She is currently completing an article on the American Friends Service Committee and Jewish rescue in World War II France, and another on Roswell McClelland's work with the American Friends Service Committee and War Refugee Board. Her upcoming project examines women humanitarian workers in the American Friends Service Committee during WWII. Her teaching covers World History from 1500, the Holocaust, Twentieth-Century Europe, and other European history courses. Her notable scientific awards and grants include: Chosen as a university-wide applicant for the 2023 National Endowment of the Humanities Summer Stipends Program Pollock Research Grant (2021) Grant from the Undergraduate Research and Inquiry Committee for an inquiry-based course (2020) College of Social Sciences Mathematics and Education Award for Outstanding Teacher (2018-2019) UCDALI Professional Development Grant (Spring 2016) CU Online Course Development Grant (Fall 2015) Nominee for College of Arts and Letters at the University of Colorado of Denver, Teaching Excellence Award (2013-2014) Dissertation Completion Fellowship, College of Social Science, Michigan State University (2010) Kussy Scholarship for Study of the Holocaust, James Madison College, Michigan State University (2008) International Studies Program Pre-dissertation Research Fellowship, International Studies Program, Michigan State University (2007) Muelder-Lowe Graduate Award, Department of History, Michigan State University (2007) Summer Research Enhancement Fellowship, Department of History, Michigan State University (2007) Summer Research Fellowship, Department of History, Michigan State University (2006) Summer Research Language Fellowship, Department of History, Michigan State University (2005) Somers Award for Excellence and Creativity in Teaching, Center for Integrative Studies in the Arts and Humanities, Michigan State University (2005) Recruitment Fellowship, Department of History, Michigan State University (2003-2004) Professor Palmer has secured significant grant funding for her research and teaching. Notable grants include: Pollock Research Grant (2021) for her research on WWII humanitarian efforts. Undergraduate Research and Inquiry Committee Grant (2020) for an inquiry-based course. UCDALI Professional Development Grant (2016) CU Online Course Development Grant (2015) She also mentors students through an internship program with the Florida Holocaust Museum, facilitating student placements and collaborative educational events. Professor Palmer collaborates closely with the Florida Holocaust Museum, where she has developed an internship program for students and co-organizes speaker events and educational activities. This partnership serves as a key platform for her students' experiential learning and community engagement.
Albert Lau is an Associate Professor of Civil and Environmental Engineering at the Norwegian University of Science and Technology (NTNU), located in Trondheim, Norway. He specializes in railway engineering, structural dynamics, and transportation systems. Lau holds leadership roles as the Study Program Leader for the MSc in Road, Railway, and Transportation Engineering, overseeing curriculum development and program coordination. His research focuses on railway track design, dynamic modeling of train-track interactions, and infrastructure maintenance, with projects such as the MeTinT initiative (Measurement with Train in Regular Traffic). He has extensive experience supervising master’s and PhD students, and his work emphasizes innovation in rail infrastructure and sustainable transportation solutions. Education and Professional Background: Lau earned his PhD from NTNU in 2018, focusing on numerical simulations of railway turnouts. Prior roles include Postdoc (2018–2020) and Assistant Professor (2017–2018) at NTNU, and teaching at Oslo Metropolitan University (2020). His industry experience includes roles as a Design Engineer (2010–2012) and Project Engineer (2013–2014) in Malaysia, where he managed construction projects and structural design. Research Interests: Lau’s work spans railway track dynamics, infrastructure health monitoring, and machine learning applications in transportation. Key projects include developing digital twins for railway test sites and analyzing ground displacement impacts on track anomalies. His contributions to the Road, Railway and Transport Group at NTNU aim to advance rail safety and efficiency through interdisciplinary approaches. Teaching and Outreach: Lau coordinates courses such as TBA4225 (Railway Engineering) and BA6012 (Fundamental Railway Technology). His outreach includes expert commentary on railway incidents, such as an interview on NRK (2024) discussing potential causes of a train accident. Current initiatives focus on revitalizing regional rail services and optimizing train positioning systems.
Jason M. LaBelle is a Professor of Anthropology at Colorado State University (CSU), affiliated with the College of Liberal Arts. He serves as Director of the Center for Mountain and Plains Archaeology (CMPA) and Curator of the Archaeological Repository of CSU (AR-CSU). His research focuses on hunter-gatherer societies, particularly in the Intermountain West, emphasizing subsistence, mobility, and pre/post-contact Native American cultures. His work spans environments from the Great Plains to high alpine regions, with specialties in Clovis/Folsom cultures, communal hunting practices, and lithic technology. LaBelle teaches courses in archaeology, lithic technology, and public archaeology. He oversees CMPA projects funded by federal agencies like the National Park Service and the Bureau of Land Management, supporting student training in fieldwork, lab analysis (lithics, faunal studies), and report writing. His lab houses extensive collections from Colorado’s South Platte and Colorado River Basins, including alpine artifacts. He actively engages with tribal partners and the public through outreach, conferences, and NAGPRA coordination. LaBelle’s recent research includes studies on lithic quarries, ice patch archaeology, and Bayesian chronology modeling. His publications address prehistoric mobility, site chronology, and cultural resource management. He values interdisciplinary collaboration and student mentorship, aiming to bridge academic and applied archaeology.
Marina von Keyserlingk is a Professor in Applied Biology within the Faculty of Land and Food Systems at the University of British Columbia (UBC). She serves as Director of the UBC Dairy Education and Research Centre and leads the renowned UBC Animal Welfare Program, one of the largest and most respected animal welfare science programs globally. Her work has significantly influenced dairy farming practices worldwide, particularly in the areas of dairy cow and calf welfare. Dr. von Keyserlingk's research focuses on animal behavior, housing, and management practices and how these contribute to the health and welfare of dairy cattle. Her work spans multiple dimensions of animal welfare science, including: Dairy cattle behavior and cognition Cow-calf separation practices Pain assessment and management in farm animals Public perceptions of farm animal welfare Alternative dairy farming systems Welfare assessment methodologies Her most recent research examines pain responses in calves, lameness assessment techniques, effects of environmental enrichment on calf cognition, and public attitudes toward dairy farming practices. This work demonstrates a strong trend toward integrating scientific assessment of animal welfare with public values and perceptions, recognizing that sustainable animal agriculture must address both scientific and societal concerns. Dr. von Keyserlingk has received numerous prestigious awards for her contributions to dairy science and animal welfare: Elanco Award for Excellence in Dairy Science (2013) Metacam Bovine Welfare Award (2013) Canadian Animal Industries Award in Extension & Public Service (2012) 26th Annual World Buiatrics Congress Keynote Speaker (2010) She has supervised numerous graduate students, including Dr. Lexis Ly who recently completed her PhD in 2025. Dr. von Keyserlingk also teaches undergraduate courses including "Animals and Society" and "Research Methods in Applied Animal Biology." Her research program has secured significant funding that supports multiple postdoctoral fellows, graduate students, and research staff working within the UBC Animal Welfare Program. The UBC Animal Welfare Program, which she helps lead, is currently recruiting PhD students interested in improving the lives of dairy cattle and the people who care for them. The program continues to be at the forefront of animal welfare science, conducting research that has practical applications for improving animal care worldwide.
Dr. Bin Tang is a Professor in the Department of Computer Science at California State University, Dominguez Hills. He holds a Ph.D. in Computer Science from Stony Brook University (2007) and dual M.S. degrees in Computer Science and Materials Science from the same institution. His research focuses on algorithmic solutions for data placement in networks, with applications in robotic sensor systems and cloud data centers. He has led multiple NSF-funded projects including 'Edge-Based Approach to Robust Multi-Robot Systems' and 'Optimal Resource Allocation in Policy-Driven Data Centers'. Dr. Tang mentors students in research competitions and has supervised numerous graduate theses. He teaches courses in operating systems, algorithms, computer networks, and cloud computing.
Nebiyou Tilahun is an Associate Professor and Director of Graduate Studies in the Department of Urban Planning and Policy at the University of Illinois at Chicago (UIC), within the College of Urban Planning and Public Affairs (CUPPA). He leads the Mobility Urban Systems and Equity Lab , focusing on equitable transportation solutions. His roles include teaching courses such as Transportation Planning Methods, Spatial Statistics, and Plan Making Studio. Dr. Tilahun holds a PhD in Civil Engineering from the University of Minnesota (2010), with earlier degrees in Civil Engineering (B.Sc., 2001; M.Sc., 2005). His career includes post-doctoral research at UIC’s Urban Transportation Center and the University of Minnesota’s Humphrey School of Public Affairs, as well as professional experience at the Washington State Department of Transportation. Research Interests : His work bridges transportation equity, urban planning, and policy evaluation. Key areas include: Transport accessibility and equity Automated traffic enforcement (e.g., speed/red-light cameras) Social networks and travel behavior Disability and mobility challenges Intergenerational poverty and spatial mobility Recent Research Trends : His publications emphasize equity in urban systems, such as analyzing racial disparities in traffic stops, evaluating automated camera efficacy, and exploring how residential choices shape young adults’ travel patterns. He also investigates transit accessibility gaps in Chicago and the role of technology in urban informatics. Labs/Teams : Directs the Mobility Urban Systems and Equity Lab, which develops tools like the Chicago Accessibility Explorer to visualize transit equity. Collaborates on projects like Seeing Cities Through Big Data , applying data science to urban planning challenges. Grants/Advising : While specific grants are not detailed here, his lab’s work implies funding in transportation equity and technology. No advisees are listed in the provided materials.
Dr. Li Chen is an Alfred and Helen Lamson/BORSF Endowed Associate Professor in the School of Computing and Informatics at the University of Louisiana at Lafayette. She leads the CELESTIAL research lab, focusing on distributed systems and networking for machine learning and AI. Her research interests include federated learning, cloud computing, and resource optimization. Dr. Chen holds a Ph.D. from the University of Toronto and has received awards such as the NSF EPSCoR RII Track-4 grant and the BoRSF Endowed Professorship. Education: Ph.D. (2018), M.A.Sc. (2015) in Electrical and Computer Engineering from University of Toronto; B.Eng. (2012) in Computer Science from Huazhong University of Science and Technology. She also visited Hong Kong Polytechnic University (2013-2014). Research spans federated learning frameworks (e.g., SEAFL, FedClust), cloud resource scheduling (e.g., Hadar, HarmonyBatch), and applications in weather forecasting (e.g., MMST-ViT). Her work is supported by NSF, Louisiana BoRSF, and industry partners like XRMedix. Awards include the Alfred and Helen Lamson/BORSF Endowed Professorship (2024-2027), NSF EPSCoR grant (2024-2026), and best paper recognitions at IEEE conferences. She advises a diverse group of graduate students and has supervised alumni now in academia and industry. Teaching includes courses on computer networks, operating systems, and distributed systems. She organizes workshops and tutorials (e.g., 2023 Summer Tutorial on ML & Meteorology) and serves on conference committees such as INFOCOM and IWQoS.
Dr. Rasmus Ibsen-Jensen is a Lecturer in Computer Science at the University of Liverpool. Previously, he held a Postdoctoral position at IST Austria under Krishnendu Chatterjee and completed his PhD under Peter Bro Miltersen. Research Focus: Algorithmic game theory, strategy complexity in two-player zero-sum games, control flow graph algorithms, edit distance for automata, and theoretical biology applications. Teaching: Module Coordinator for second-year courses in database development (COMP207), C++ programming (COMP282), and industrial placement (COMP299). His work bridges computational game theory and formal verification, with recent publications exploring memory constraints in partial-information games, algebraic path properties in concurrent systems, and evolutionary spatial dynamics. While no scientific awards are explicitly mentioned in the provided text, his contributions to algorithmic complexity and interdisciplinary research (e.g., theoretical biology) highlight his academic impact.
Xiaoming Hu is a Professor at the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH Royal Institute of Technology (Kungliga Tekniska Högskolan) in Stockholm, Sweden. Born in Chengdu, China, he received his B.S. degree from University of Science and Technology of China in 1983, followed by M.S. and Ph.D. degrees from Arizona State University in 1986 and 1989 respectively. After serving as a research assistant at the Institute of Automation, Chinese Academy of Sciences (1983-1984), he was a Gustafsson Postdoctoral Fellow at KTH (1989-1990) before becoming a faculty member. His educational background includes: B.S. in Engineering, University of Science and Technology of China, 1983 M.S. in Engineering, Arizona State University, 1986 Ph.D. in Engineering, Arizona State University, 1989 Xiaoming Hu's research primarily focuses on multi-agent systems, nonlinear feedback stabilization, nonlinear observer design, and sensing and active perception. His work bridges theoretical control theory with practical applications in robotics and autonomous systems. He has made significant contributions to geometric control theory, mathematical systems theory, and nonlinear systems analysis and control. His research often involves developing theoretical frameworks for distributed control, formation control, and cooperative behavior in multi-robot systems. Professor Hu's publication record shows a consistent research trajectory with numerous high-impact publications in top-tier journals like Automatica, IEEE Transactions on Automatic Control, and Systems & Control Letters. His research has evolved from fundamental control theory to more applied problems in robotics and multi-agent systems, while maintaining strong mathematical foundations. Recent work shows increasing focus on safety-critical control, inverse problems in estimation, and networked systems. His scientific contributions include: Development of theoretical frameworks for multi-agent coordination and formation control Advances in nonlinear observer design for robotic systems Contributions to geometric control theory and systems theory Research on distributed estimation and control algorithms Applications of control theory to robotics and autonomous systems Professor Hu teaches several advanced courses including Mathematical Systems Theory, Geometric Control Theory, and Nonlinear Systems: Analysis and Control. He has supervised numerous degree projects at both undergraduate and graduate levels in mathematics, optimization, systems theory, and scientific computing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of control theory.
Associate Professor Lasantha Meegahapola is a Deputy Head of Department (Teaching & Learning) at RMIT University's School of Engineering in Melbourne, Australia. He holds an IEEE Senior Membership and serves as an Associate Editor for several prestigious journals, including IEEE Transactions on Power Systems and IET Renewable Power Generation. His research focuses on Power System Stability with Renewable Integration, Microgrid Control, and Smart Grid Technologies, addressing challenges like voltage stability, inverter-based grid dynamics, and renewable energy penetration. He has supervised 16 PhD students to completion and published over 200 articles. Key contributions include identifying stability issues in microgrids and advancing grid-forming inverter control strategies. His work aligns with UN Sustainable Development Goals 7 (Clean Energy), 9 (Infrastructure), and 13 (Climate Action). He is actively involved in IEEE committees, including the PSDP Task Force on Microgrid Stability. Teaching roles include Programme Manager for the Bachelor of Electrical Engineering (HK) and Subject Coordinator for Power System Analysis and Control courses. Collaborations span industry and international research institutions, emphasizing real-world applications of his research in power systems and renewable energy integration.
Florian Shkurti is an Assistant Professor in the Department of Computer Science at the University of Toronto Mississauga (UTM), affiliated with the UofT Robotics Institute, Vector Institute, and Acceleration Consortium. His research focuses on robotics, machine learning, and computer vision, emphasizing safe and effective autonomous systems in dynamic environments. He directs the Robot Vision and Learning (RVL) lab, exploring areas like environmental monitoring, autonomous navigation, and mobile manipulation. Research Interests: His work spans robotics, machine learning, and computer vision. Key areas include robot perception, planning under uncertainty, safe exploration, imitation learning, and applications in field robotics, autonomous vehicles, and chemistry lab automation. He develops methods enabling robots to perceive, reason, and act safely in collaboration with humans. Publications: Recent work includes advancements in safe multitask learning, interactive crowd navigation, and diffusion models for trajectory planning. His research bridges theoretical foundations with real-world applications in environmental science and autonomous systems. Affiliations: Faculty Member, UofT Robotics Institute; Faculty Affiliate, Vector Institute; Faculty Member, Acceleration Consortium. He also holds positions at UTM's Mathematical & Computational Sciences department. Teaching: Courses include Imitation Learning for Robotics, Neural Networks, and Mobile Robotics. He emphasizes hands-on experience with autonomous systems through projects involving RC cars and simulation tools. Labs & Teams: Leads the RVL lab, collaborating on projects like RoboCulture (automated biological experimentation) and SICNav (safe crowd navigation systems). The lab focuses on cross-disciplinary robotics solutions for real-world challenges.
