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.
Babak Moaveni is a Professor in the Department of Civil and Environmental Engineering at Tufts University, serving as the Associate Chair since September 2024. He also holds a joint appointment as a Professor in Electrical and Computer Engineering. His research focuses on structural health monitoring, Bayesian inference, earthquake engineering, and offshore wind energy systems. Moaveni earned his Ph.D. in Structural Engineering from the University of California San Diego (2007), following an M.S. (2001) and B.S. (1999) from Sharif University of Technology in Tehran, Iran. His research interests span probabilistic system identification, signal processing, uncertainty quantification, and verification/validation of computational models. Notable grants include leadership in the PIRE project on offshore wind energy digital twins and the Coastal Virginia Offshore Wind Pilot Project. He has supervised multiple Ph.D. and M.S. students, with current advisees including Mehdi Akhlaghi and Nasim Partovi-Mehr. Moaveni has received the Best Presentation Award at the 2022 EDGE Symposium and serves on editorial boards for journals like Structural Health Monitoring and Frontiers in Built Environment . His lab, the Structural Health Monitoring Lab, specializes in infrastructure management and offshore wind energy systems. Key professional activities include membership in the American Society of Civil Engineers (ASCE) and roles on Tufts' Tenure and Promotion Committee. His teaching includes courses on structural health monitoring, numerical methods, and structural reliability.
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.
Nicole Megow is a Professor holding the chair for Combinatorial Optimization in the Faculty of Mathematics and Computer Science at the University of Bremen since 2016. She is affiliated with several research clusters including Humans on Mars Initiative, Minds, Media, Machines, and Dynamics in Logistics. Her academic journey includes positions at TU Berlin, Max Planck Institute for Informatics, TU Darmstadt, and TU Munich. Professor Megow's research focuses on mathematical optimization, algorithm design and analysis, and operations research. Her specific interests span combinatorial and discrete optimization, efficient algorithms, scheduling theory, resource allocation, packing problems, network design, routing, and uncertainty models including online, stochastic, robust, and explorable approaches. Her work bridges theoretical foundations with practical applications in logistics and decision-making systems. Her recent publications demonstrate a strong trend toward integrating prediction models with traditional optimization frameworks, particularly in scheduling and matching problems. She has made significant contributions to understanding the role of uncertainty in optimization problems, developing algorithms that work effectively with incomplete or uncertain information. Her work spans multiple prestigious venues including Mathematical Programming, Algorithmica, SODA, STACS, and NeurIPS. Dissertation Award by the German Operations Research Society (2007) Berlin Science Award for Young Researchers (2013) Heinz Maier-Leibnitz Prize (2013) Listed among Germany's top 40 researchers below 40 (Capital, 2014, 2015) Professor Megow actively supervises PhD students and postdocs, including Max Stahlberg, Joes Biburger, Sarah Morell, Bart Zondervan, Zhenwei Liu, and Alexander Lindermayr. She serves on numerous program committees for major conferences including SODA, IPCO, and STOC, and holds editorial positions for several prestigious journals. Her current research projects include Optimization under Explorable Uncertainty (DFG funded), How robots learn how to use structure (seed grant from MMM research cluster), and Scheduling Invasive Multicore Programs Under Uncertainty (within TCRC 89).
Auezhan Amanov is an Associate Professor at the Faculty of Engineering and Natural Sciences, Tampere University, specializing in the Engineering Materials Science (EMS) department. His research focuses on tribology, surface engineering, and advanced materials processing. He leads the 'Tribology and Surface Modification' research group, aiming to enhance machine element performance through surface treatments and manufacturing innovations. Dr. Amanov is an active member of international tribology societies (STLE, JAST, KTS), chairing the 'Surface Engineering' committee at STLE. His work emphasizes improving wear resistance, fatigue life, and tribological performance of materials like titanium alloys, high-entropy alloys, and thermal spray coatings. His research integrates additive manufacturing, laser-based processes, and severe plastic deformation techniques to optimize material properties. Key contributions include studies on ultrasonic nanocrystal surface modification (UNSM) for enhancing mechanical and tribological characteristics. Collaborations with industries and academic institutions globally drive his mission to translate research into practical solutions for manufacturing efficiency and sustainable development. Dr. Amanov holds an h-index of 34 (Google Scholar) and has authored numerous peer-reviewed articles on materials science and tribology advancements. Teaching responsibilities include tribology and fatigue-related courses, reflecting his expertise in both academic and applied engineering domains. His vision includes advancing circular economy practices through bearing restoration technologies and improving 'Made in Finland' manufacturing competitiveness through material science innovations.
Dr. Wei David Dai is an Assistant Professor of Computer Science at Purdue University Northwest and Director of the Advanced Intelligence Software (AIS) Lab. His research focuses on robust deep learning, data quality, and public safety technologies like gunshot detection systems. He previously worked at IBM China as a senior engineer and served in Arkansas state government as a data scientist. Education: Ph.D. in Computer and Information Sciences (University of Arkansas at Little Rock, USA, 2020) M.S. in Information Science (University of Arkansas at Little Rock, USA, 2016) M.S. in Software Engineering (South China University of Technology, China, 2013) B.S. in Computer Science (Central South University, China, 2007) Research Interests: His work spans robust deep learning models, distributed computing systems, and privacy-preserving technologies. Notable projects include public safety innovations such as acoustic gunshot detection and AI-driven campus security systems. Articles Trends: Recent publications emphasize public safety applications (e.g., mass school shooting simulations) and deep learning robustness evaluation (e.g., the Accuracy-Stability Index metric). Earlier works address cloud computing optimization and data quality frameworks. Awards: Recipient of the 2024 Excellence in Research Award and multiple IBM honors for technical excellence and instruction. Grants & Advising: Leads the Indiana Space Grant Consortium-funded satellite imaging project and Purdue Provost Grant for gunshot detection. Advises doctoral and master’s students on AI ethics, distributed systems, and public safety. Labs: The AIS Lab develops AI tools for public safety, equipped with GPU resources for audio and image analysis.
Professor Hing-Ho Tsang is the Chair in Civil and Structural Engineering at the University of Dundee, with over a decade of academic experience in Australia and Hong Kong. His research focuses on advancing sustainable infrastructure solutions, earthquake resilience, and green technologies to enhance building and infrastructure safety against natural disasters. He holds a Chartered Professional Engineer (CPEng) certification and advises governments and industries on building codes and seismic design guidelines. Tsang chairs the Global Network for Geotechnical Seismic Isolation (GSI) and serves as the Australian National Delegate to the International Association for Earthquake Engineering (IAEE). His expertise spans geotechnical seismic isolation, recycled materials in construction, and structural dynamics, contributing to UN Sustainable Development Goals (SDGs) like resilient infrastructure, circular economy, and climate action. With over 200 publications and a career-long impact ranking in Civil Engineering, Tsang has received prestigious awards including the R W Chapman Medal and Research Impact Award. Research Focus: Seismic design, sustainable construction, bio-inspired materials, and geotechnical isolation systems. Awards: Top Cited Article (2021–2022), Teaching Excellence Award (2022), and multiple international recognitions. Leadership Roles: Editorial board member for Geosynthetics International , organizer of the 18th World Conference on Earthquake Engineering technical session. His work emphasizes equity-driven engineering solutions, fostering inclusive and disaster-resilient communities. Current projects include innovative modular building systems and AI-driven seismic response models.
Miklós Koren is a Professor of Economics at the Central European University (CEU), Vienna. He serves as Head of the MS in Business Analytics Program and a Core member of the Economics Doctoral School. His research focuses on international trade, economic development, and the role of management in economic growth. He holds a Ph.D. from Harvard University (2005), an M.A. from CEU (2000), and a B.A. from Corvinus University Budapest (1999). Education: Ph.D. in Economics, Harvard University, 2005 M.A. in Economics, Central European University, 2000 B.A. in Economics, Corvinus University Budapest, 1999 Research Interests: Dr. Koren’s work examines the impact of managerial practices on economic development, trade policies, and firm performance. He has explored topics such as the effects of international experience on managerial talent, the role of expatriate CEOs in enhancing productivity, and the long-term implications of social distancing on industries reliant on face-to-face interactions. His research integrates empirical analysis with theoretical frameworks, often using large datasets to address questions of economic volatility and diversification. Key Contributions: He leads the CEU MicroData research group and has received an ERC Starting Grant for his work on trade and development. His publications span journals like the Quarterly Journal of Economics and PLoS ONE, addressing issues ranging from managerial skills in post-communist economies to the predictive power of machine learning in geospatial flows. Awards: Recipient of the Peter Kenen Fellowship and the Nicholas Káldor Prize, recognizing his contributions to economic theory and applied research. Grants & Labs: His research has been supported by grants from the European Research Council. He contributes to the development of research tools like the Stata package 'eventbaseline' for event study analysis.
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.
Andreas Grothey is a Senior Lecturer in the School of Mathematics at The University of Edinburgh, a position he has held since 2011. He completed his MSc in Numerical Algebra and Mathematical Computing at the University of Dundee (1995) and his PhD in Optimization at the University of Edinburgh (2001), supervised by Ken McKinnon. His research focuses on stochastic programming, interior point methods, decomposition approaches, high-performance computing, and energy systems optimization. He has contributed to energy planning, power grid reliability, and emergency response strategies for power networks. Grothey has advised seven PhD students, including work on unit commitment, top-percentile traffic routing, and power flow optimization. His projects include the OOPS solver, CESI energy integration center, and the Structured Modelling Language (SML). Recent work addresses pandemic policy optimization and exascale computational challenges. Education: MSc in Numerical Algebra and Mathematical Computing (University of Dundee, 1995) PhD in Optimization (University of Edinburgh, 2001) Research Interests: Stochastic Programming Interior Point Methods Decomposition Methods High-Performance Computing Energy Systems Optimization Advising & Projects: PhD Supervision (7 students, 2007–2022) OOPS Parallel Solver Development CESI Energy Systems Integration SML Structured Modelling Language Labs/Teams: Member of the Edinburgh Research Group on Optimization, leading projects in power grid stability and energy planning.
Chris Freeman is a Professor of Robotics and Control at the University of Southampton's Electronics and Computer Science (ECS) school. His research focuses on iterative learning control theory, biomedical engineering, and robotics with applications in industrial automation and healthcare. As Deputy Head of School (Equity, Diversity and Inclusion) and Chair of the ECS Belonging, Inclusion, Diversity and Equity (BIDE) Committee, he drives initiatives promoting inclusive academic environments. Freeman leads multidisciplinary research projects such as "Towards intelligent, pervasive, high performance control system architectures" "Elder Athletes: building incidental interaction at home" "Low-cost personalised instrumented clothing with integrated FES electrodes" . His work combines robotics, functional electrical stimulation (FES), and wearable technologies to develop rehabilitation systems for stroke patients and industrial automation solutions. His recent publications demonstrate expertise in iterative learning control (ILC), model predictive control, and biomedical applications. Research groups include: Digital Health and Biomedical Engineering Institute for Life Sciences Centre for Health Technologies Centre for Robotics
George Nacouzi is a Senior Engineer at RAND Corporation and a Professor of Policy Analysis at the RAND School of Public Policy. He specializes in strategic defense research, focusing on space systems resilience, missile defense, hypersonic technologies, and nuclear command systems. His work bridges technical analysis with policy implications, particularly in integrating commercial space services into U.S. military operations. Education: Ph.D. in Mechanical and Aerospace Engineering from the University of California, Irvine. Prior to RAND, he held senior engineering roles at TRW and Northrop Grumman, analyzing space and missile defense systems. He also taught space-related courses at UC San Diego and Northrop Grumman. Research Interests: Space domain awareness, commercial space contributions to national security, orbital operations, small satellite applications, and the impact of emerging technologies on strategic stability. His work emphasizes non-materiel resilience strategies and policy frameworks for space systems. Key Article Trends: Recent publications focus on AI/ML applications for space domain awareness, commercial space integration challenges, and hypersonic missile nonproliferation. He explores how evolving technologies disrupt traditional military domains and influence global stability. Scientific Awards: None explicitly mentioned in provided texts. Advising & Grants: No formal advisees listed, but leads research projects at RAND’s Project AIR FORCE and National Security Research Division. His work is funded by U.S. Department of Defense and Congressional mandates. Labs/Teams: Affiliated with RAND’s Project AIR FORCE and National Security Research Division, collaborating with U.S. Space Force and Department of the Air Force on strategic initiatives.
Stefan Duma is the Harry C. Wyatt Professor of Engineering and a University Distinguished Professor at Virginia Tech. He is currently serving as Interim Department Head in the Department of Biomedical Engineering and Mechanics within the College of Engineering. He also directs the Institute for Critical Technology and Applied Sciences and leads the Virginia Tech Helmet Lab. His educational background includes: Ph.D. in Mechanical Engineering from the University of Virginia (2000) M.S. in Industrial Engineering from the University of Cincinnati (1996) B.S. in Mechanical Engineering from the University of Tennessee (1995) Dr. Duma's research focuses on injury and impact biomechanics, with applications in automobile safety design , sports biomechanics (especially football and hockey), and military restraint systems . His work investigates head and neck injury mechanisms, concussion thresholds, and protective equipment performance. He has pioneered methodologies for evaluating helmet safety and individualized injury tolerance. The recent publications reflect a strong focus on head impact biomechanics , concussion prediction , and wearable sensor validation . The research spans youth and collegiate sports, drone impact risks, and automotive safety. Key themes include individual variability in injury response, helmet performance assessment, and translational safety applications. Scientific recognition includes his appointment as a University Distinguished Professor and leadership roles, though specific awards are not listed in the provided text. Dr. Duma advises a team of researchers and students, including Steven Rowson, Abigail Tyson, and Eamon Campolettano. His lab has secured significant research funding (implied by patent and publication volume), particularly in developing safety standards and injury prevention technologies. The Virginia Tech Helmet Lab is central to his research, conducting experiments with human volunteers, PMHS, and advanced instrumentation. His lab, the Virginia Tech Helmet Lab, is a leading center for impact biomechanics research, focusing on real-world safety challenges in sports, transportation, and emerging technologies like drones.
Rajeev Balasubramonian is a Professor and Associate Director at the School of Computing, University of Utah. He specializes in computer architecture, with a focus on memory systems, emerging technologies, and energy-efficient computing. His research addresses challenges in DRAM/NVM architectures, security, and acceleration for big data and machine learning workloads. Education: PhD in Computer Science (University of Rochester, 2003), M.S. (University of Rochester, 2000), B.Tech in Computer Science (IIT Bombay, 1998). Research Interests: Memory reliability, near-data processing, cache hierarchies, transactional memory, and hardware-software co-design for emerging technologies. He has led projects on crossbar accelerators, secure memory systems, and resistive memory architectures. Recent Trends in Publications: Focus on encrypted inference (Hyena), data prefetching (PATHFINDER), and neuromorphic computing (SpinalFlow). His work bridges hardware and software, emphasizing practical acceleration and security solutions. Awards: IEEE Fellow (2021), Google Faculty Awards (2019/2020), Intel Research Award (2017), and multiple best paper awards (ISCA, ISPASS, PACT). Grants & Students: Over $4M in NSF/industry funding. Advised 15+ PhD students (e.g., Ali Shafiee, Karl Taht) and currently mentors researchers in resistive memory and security accelerators. His lab includes teams like Utah Arch Research Group. Labs & Teams: Leads the Utah Arch Research Group , organizing workshops on near-data processing and memory systems (e.g., ISCA, HPCA).
Jens Krause is a Professor and Head of Department at the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin, leading the Research Group on Mechanisms and Functions of Group-Living. He holds a full professorship in Fish Ecology at Humboldt-Universität zu Berlin, Faculty of Life Sciences, Thaer-Institute, and since 2018 has been an Adjunct Professor at Technical University Berlin within the Excellence Cluster 'Science of Intelligence'. His research is centered on collective intelligence, social networks, decision-making, and behavioural ecology in fish and other animals. Full Professor in Fish Ecology, Humboldt-Universität zu Berlin Adjunct Professor at Technical University Berlin (since 2018) Head of Department, IGB Berlin PhD, University of Cambridge Diploma, Free University Berlin His work integrates experimental biology, network analysis, and biomimetic robotics to understand how animals make collective decisions. His expertise spans animal behaviour, evolution, and ecological physiology, with a strong focus on group-living dynamics. Recent research explores group hunting, predator evasion, social foraging, and the impact of environmental stressors on collective behaviour. The analysis of his recent publications reveals a strong trend in understanding collective behaviour in fish, including escape waves, social foraging, group hunting in marlins and sailfish, and the use of robotic agents to study social integration. His interdisciplinary approach combines marine biology, physics, robotics, and data science to uncover the mechanisms behind collective intelligence in both animal and human systems. Editorial Board, Behavioral Ecology Editorial Board, Fish and Fisheries Executive Board, Excellence Cluster 'Science of Intelligence' Advisory Board, Bimini Biological Field Station Foundation He advises numerous PhD students and postdoctoral researchers, and leads major research projects, including 'Developing exploration behaviour' funded by the Excellence Cluster. His work has been supported by extensive collaborations across Europe and North America, and he frequently publishes in top-tier journals such as Nature , Science Advances , Proceedings of the Royal Society , and Current Biology . His lab employs cutting-edge methods including automated tracking, social network analysis, and interactive robotics to study animal groups. His research group, 'Mechanisms and Functions of Group-Living', is embedded within the Excellence Cluster 'Science of Intelligence', where they investigate collective cognition, social information use, and the role of individual differences in group performance. The team combines field studies with laboratory experiments and computational modelling to understand the evolution and function of collective behaviour across species.
