Chro Haider Ahmed is an Honorary Research Fellow at the Department of Civil and Environmental Engineering , Faculty of Engineering , Imperial College London. As a Ph.D. student at the Centre for Transport Studies, her research focuses on optimizing transit rail line alignment and station positioning in urban environments. Education: MSc in Transportation Engineering (with Distinction) Ph.D. candidate at Imperial College London Research Interests: Her work bridges urban planning , geographical information systems (GIS) , and transport infrastructure development in low-income regions .
Yunan Yang is the Goenka Family Assistant Professor in Mathematics at Cornell University, within the Department of Mathematics, College of Arts and Sciences. He holds a Ph.D. from the University of Texas at Austin (2018), supervised by Prof. Björn Engquist. Previously, he was a Courant Instructor at NYU (2018–2021), Simons-Berkeley Research Fellow (2021), and Advanced Fellow at ETH Zürich (2022–2023). His research focuses on computational mathematics, including inverse problems, optimal transport, machine learning, and nonconvex optimization. Notable contributions include applications of optimal transport to seismic inversion and PDE-constrained optimization. He has advised numerous students, including undergraduates and Ph.D. candidates at Cornell and other institutions. Yang teaches courses such as MATH 6220 (Applied Functional Analysis) and has published extensively in journals like SIAM Journal on Scientific Computing and Communications on Pure and Applied Mathematics. His work bridges theoretical foundations with practical applications in geophysics and computational science.
Associate Professor Andre Kyme is an academic staff member in the School of Biomedical Engineering at The University of Sydney. His research focuses on developing enabling technologies for biomedical imaging, including motion compensation in MRI/PET, robotic platforms for image-guided therapy, and cross-disciplinary applications like plant salt uptake analysis using PET. He collaborates with institutions globally and advises students on projects like lameness detection in horses and AI-based motion correction. Research Interests: Kyme's work spans motion correction in medical imaging modalities, medical robotics integration with imaging systems, and innovative applications of imaging technologies in non-traditional fields. His team emphasizes leveraging advancements in computer vision, machine learning, and instrumentation to improve imaging performance and accessibility. Recent Projects: Current research includes MRI-compatible robotic platforms for therapy applications, AI-driven lameness detection in horses, and pediatric neuroimaging improvements. He leads the BREEZE initiative to enhance MRI accessibility for children with cerebral palsy through eye-gaze communication technology. Publications: His work spans 20+ years with over 50 peer-reviewed publications in journals like Physics in Medicine and Biology and IEEE Transactions. Key areas include PET/SPECT/CT motion correction algorithms, robotic systems for medical imaging, and novel imaging applications in plant science. Teaching: Kyme instructs core biomedical engineering courses including thesis supervision and capstone projects at both undergraduate and postgraduate levels. Labs/Teams: Active in the Brain and Mind Centre and Biomedical Imaging, Visualisation and Information Technologies groups at Sydney. Collaborates with industry partners like TeleMedVet and academic institutions including University of California Davis and Chinese University of Hong Kong.
Dieter Uckelmann serves as Professor of Information Logistics and Scientific Director of the Institute for Applied Research at Stuttgart University of Applied Sciences (HFT Stuttgart). He holds multiple leadership positions including Spokesperson for the research focus 'Smart Technologies, Processes and Methods' at HFT Stuttgart since March 2023 and Scientific Director of the Institute for Applied Research since September 2023. His academic journey began with mechanical engineering studies in Braunschweig, followed by doctoral research at the University of Bremen focusing on 'Quantifying the Value of RFID and the EPCglobal Architecture Framework in Logistics.' Uckelmann's research spans Internet of Things applications across Industry 4.0, logistics, smart buildings, and smart cities, with significant contributions to educational technology including learning analytics and AI in teaching. His work bridges technical innovation with practical implementation, particularly in digital transformation of laboratories and smart city infrastructure. He has led numerous research projects including KNIGHT (AI for teaching), InDeckLe (earth composite ceiling systems), iCity initiatives, and DigiLab4U (online laboratories). His publication record shows a clear progression from foundational RFID and IoT research toward emerging technologies like the Industrial Metaverse, 5G applications, and AI-driven educational systems. Recent work demonstrates strong integration of physical and digital systems, particularly in urban environments and educational contexts, with increasing emphasis on sustainability and energy efficiency applications. Co-editor of International Journal of RF-Technologies: Research and Applications Member of PhD Association BW, Research Unit III Computer Science and Electrical Engineering Mentor in the HAWCareer mentoring program Program Committee Member for IEEE RFID, IEEE/ITMC, AIET, and other major conferences Associate Editor for Journal of Online and Biomedical Engineering Professor Uckelmann actively mentors students and researchers, with his team contributing to projects across smart city infrastructure, digital learning platforms, and industrial IoT applications. He leads the Industrie 4.0 Laboratory which focuses on industrial IoT applications, digital twins, and the industrial metaverse, with research spanning RFID, RTLS, wireless sensor networks, AR/VR, and IoT architectures. His work extends to international collaborations including visiting professorships at Auburn University and the University of Parma.
Matthew J. Cracknell is a Senior Lecturer in Geodata Analytics at the University of Tasmania's School of Natural Sciences, specializing in Earth Sciences. He holds a PhD in Computational Geophysics (2014) and BSc (Hons) in Geophysics (2009), both from the University of Tasmania. His research integrates geoscience with machine learning to address challenges in mineral exploration, environmental remediation, and sustainable resource management. Key focuses include automated detection of geological features in drillcore imagery, decarbonization of energy systems via ore deposit discovery, and legacy mine waste characterization. Cracknell leads the CODES Research Program 6 (Geophysics and Computational Geosciences) and Module 2 of the AMIRA P1249 project. He has secured significant industry and government funding, including projects with Boliden AB, Anglo American, and the Tasmanian Government. His work emphasizes collaboration with mining partners and agencies like Geoscience Australia and Mineral Resources Tasmania. Teaching roles include developing courses on the mining value chain, climate resilience, and geodata analytics. As Graduate Research Coordinator, he promotes HDR student well-being and supervises over 20 doctoral and masters students. Awards include the 2019 Oz Minerals Explorer Challenge Prize. Key affiliations include the International Association for Mathematical Geosciences, Australian Society of Exploration Geophysicists (Tasmanian Branch Secretary), and Geological Society of Australia.
Georges Zaccour is a full Professor at HEC Montréal's Department of Decision Sciences and holds the Chair in Game Theory and Management. He is a member of the Group for Research in Decision Analysis (GERAD). His research focuses on game theory, operations research, environmental management, and quantitative marketing. He has published over 200 papers and co-authored influential books like *Differential Games in Marketing* and *Games and Dynamic Games*. He earned his M.Sc. and Ph.D. in Administration from HEC Montréal, and a Licence in Mathematics and Economics from Université Paris-Dauphine. Previously, he served as GERAD director and head of HEC's Marketing Department and PhD program. His work spans strategic interactions in supply chains, environmental policy, and dynamic games. He has advised 7 PhD students and 1 MSc student since 2020. He won the 2021 Grand Prix de recherche Pierre-Laurin from HEC Montréal and is a Royal Society of Canada Fellow. Teaching includes courses on pricing models and game theory applications. His grants come from NSERC and SSHRC. He is editor-in-chief of *Dynamic Games and Applications* and serves on editorial boards of several journals.
Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.
Jung Yun Bae serves as Assistant Professor in Mechanical and Aerospace Engineering at Michigan Technological University with a secondary appointment in Applied Computing within the College of Computing, joining MTU in 2019 after five years as Research Professor at Korea University's Intelligent Systems and Robotics Laboratory. Her academic credentials include: PhD in Mechanical Engineering from Texas A&M University MS in Mechanical Engineering from Hongik University BS in Mechanical Engineering from Hongik University Dr. Bae's research program centers on Robotics with emphasis on Multi-robot systems, particularly Coordination of Heterogeneous Robot Teams and Vehicle Routing Problems. Her work develops operational strategies for multi-agent autonomous vehicle systems through Multi-robot System Control and Optimization techniques, extending to Autonomous Navigation and Operational Research applications. Current investigations focus on underwater robotics coordination and neuroevolution approaches for connected vehicle systems. Analysis of her recent publications reveals consistent focus on workload-balanced task allocation for heterogeneous robot teams across challenging environments. Her underwater robotics research addresses tether management and entanglement avoidance, while neuroevolution applications target autonomous vehicle control at uncontrolled intersections and hybrid powertrain optimization, bridging robotics with operations research and artificial intelligence. Prior to MTU, Dr. Bae maintained affiliation with Korea University's Intelligent Systems and Robotics Laboratory. Her current work at MTU connects with the Great Lakes Research Center context, though specific laboratory details aren't provided in available materials.
Jonathan Boualavong is an Assistant Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo, State University of New York. His research focuses on electrochemical separations for climate change mitigation, public health, and environmental justice, integrating engineering and critical science and technology studies perspectives. PhD, Environmental Engineering, Pennsylvania State University (2023) MPhil, Chemical Engineering, University of Strathclyde, Scotland (2019) BS, Biomedical Engineering, University of Rochester (2017) His work examines: Electrochemical CO2 capture and its energy implications Mechanistic understanding of metal separations Ethical dimensions of scientific measurement Integration of renewable energy systems with chemical processes Current projects analyze: Air-water interface manipulation for CO2 absorption Electrochemical controls on lead/copper corrosion Coordination chemistry in transition metal redox processes Ethical citation networks in separation science Contact: jboualav@buffalo.edu
Dr. Yiting Xia is a tenure-track faculty member at the Max Planck Institute for Informatics (MPI-INF), leading the Network and Cloud Systems research group. She previously worked as a research scientist at Facebook and holds a PhD in Computer Science from Rice University (2018) and a B.S. in Telecommunications Engineering from Beijing University of Posts and Telecommunications and Queen Mary University of London (2011). Her research focuses on high-performance and energy-efficient networking for cloud computing, including reconfigurable data center networks, optical communications, and network protocols. Notable contributions include innovations in transport protocols, time synchronization for optical networks, and failure-resilient network design. Education: PhD in Computer Science, Rice University, 2018 M.S. in Computer Science, Rice University, 2014 B.S. in Telecommunications Engineering, BUPT & QMUL, 2011 Research Interests: Data center networking, optical communications, cloud systems, network protocols, distributed systems, and network security. Her work bridges theoretical contributions with practical implementations, addressing challenges in latency-sensitive flows, traffic engineering, and system reliability. Awards include the Ken Kennedy-Cray Fellowship and the N2Women Rising Star Award (2021). She has co-lectured courses on distributed systems and data networks at Saarland University and previously contributed to teaching at Rice University. Key projects include Aurora (for MoE inference optimization), Lighthouse (an open research framework for optical networks), and Occam (a reliable network management system). Grants & Projects: Focus on deployable optical network architectures and resilient backbone management during pandemic-driven traffic shifts. Labs/Teams: Leads the Network and Cloud Systems group at MPI-INF, collaborating with academia and industry on cutting-edge networking solutions.
Miroslav Krstic is a Distinguished Professor of Mechanical and Aerospace Engineering at the University of California, San Diego (UCSD), and serves as Senior Associate Vice Chancellor for Research overseeing 17 research institutes, postdoctoral affairs, and shared facilities. He leads the Center for Control Systems and Dynamics and the Naval Innovation, Science, and Engineering Center (NISEC). Education: PhD (1994) and MS (1992) from University of California, Santa Barbara, under advisor Petar Kokotovic. BSc (1989) from University of Belgrade, Yugoslavia. Research Interests: Pioneered methods in control theory including PDE backstepping, extremum seeking, nonlinear adaptive control, and delay compensation. Focuses on applications in chip manufacturing, aircraft carriers, particle accelerators, Mars rovers, and traffic congestion. Integrates machine learning with control design for PDE systems. Awards: Over 30 major honors including the Bellman Award, Reid Prize, Oldenburger Medal, Bode Lecture Prize, and Fellowships from AAAS, SIAM, ASME, IEEE, and IFAC. Recognized as the world's top control theorist by ScholarGPS. Service & Grants: Editor-in-Chief of IEEE Transactions on Automatic Control and Systems & Control Letters . Directed over $100M in research funding annually. Advised 30+ PhD students and postdocs, many in industry leadership roles. Industry Impact: Technologies deployed in EUV lithography (Cymer/ASML), US Navy aircraft carrier arresting gear (General Atomics), and NASA's Mars Curiosity Rover laser system. Contributions to fusion control, battery estimation, and combustion optimization.
Shannon Neibergs is an academic professional at Washington State University (WSU), serving as Director of the Western Center for Risk Management Education and Extension Specialist in the School of Economic Sciences. She holds a Ph.D. in Agricultural Economics from Texas A&M University (1993), an M.A. in Agricultural Economics from WSU (1987), and a B.S. in Animal Science from WSU (1983). Her research focuses on livestock production economics, auction market dynamics, and agribusiness employment strategies, with significant contributions to risk management education and sustainable agriculture. Notable honors include NACAA National and Regional Finalist awards for team newsletters (2010, 2008), a Faculty Member of the Year Award (University of Louisville, 1997), and multiple annual evaluation awards for service and research excellence. Her work bridges academic research with practical extension programs, addressing challenges in beef production systems, genomic selection tools, and rangeland management. Risk Management Education: Leads initiatives to help farmers navigate market uncertainties and policy changes. Livestock Economics: Specializes in production costs, crossbreeding impacts, and disease management economics. Regional Agriculture: Analyzes economic contributions of Washington's beef and dairy sectors through input-output models. Her advisory and collaborative efforts include managing the Western Center for Risk Management and contributing to the Beef Risk Control (BRD CAP) project. She collaborates with ranchers and policymakers to enhance agricultural resilience. Active in interdisciplinary teams such as the IMPACT Center and Transportation Research Group, her work emphasizes translating research into actionable solutions for agricultural stakeholders.
Chung-Hsing Yeh is an Associate Professor at Monash University's Faculty of Information Technology, Department of Data Science & AI. He holds a visiting professorship at National Cheng Kung University, Taiwan, and has extensive experience in academic roles including Chief Examiner and Lecturer for numerous IT and business-related courses. His research focuses on multicriteria decision analysis, applied artificial intelligence, fuzzy logic, neural networks, and sustainable operations management. He has led collaborative projects on e-waste recycling, supply chain optimization, and public health policy, funded by organizations like the Ministry of Science and Technology (Taiwan) and the Australian Research Council. Education: PhD in Operations Research/Information Systems, Monash University (1988) MSc in Management Science, National Cheng Kung University (1982) BSc (Engineering) in Industrial Design, National Cheng Kung University (1977) Research Interests: His work spans decision support systems, optimization modeling, transport research, and recycling operations. Notable contributions include algorithms for production scheduling, AI-driven solutions for healthcare, and sustainable e-waste management strategies. Awards: Listed in Marquis Who's Who in the World Listed in Who's Who in Finance and Industry Listed in Who's Who in Science and Engineering Grants & Projects: Led 6 major projects, including 'Maximizing E-waste Recycling Profitability' (2019–2020) and 'Smoke-Free Policy Effectiveness' (2007–2010). Active in grant review roles for ARC and the Netherlands Organisation for Scientific Research. Teaching: Overseeing courses such as Fundamentals of Artificial Intelligence, Business Intelligence Modelling, and Management Information Systems.
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.
