Professor David Wagg is a Professor of Nonlinear Dynamics and Departmental Director of Research and Innovation at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. His research focuses on nonlinear structural dynamics, digital twins, vibration suppression, and real-time hybrid testing. He holds a BEng and PhD from University College London and previously served as a Professor at the University of Bristol (2008–2013). Notable awards include the EPSRC Advanced Research Fellowship (2004–2009). Education: BEng and PhD in Nonlinear Dynamics from University College London. Research Interests: Digital twins for dynamics applications, nonlinear structural dynamics, vibration control, real-time hybrid testing, and identification methods for nonlinear dynamics. His work emphasizes applying nonlinear models and control strategies to engineering challenges like wind turbines and large civil infrastructure. Grants & Leadership: Co-Investigator for EPSRC grants on CITCoM and Digitwin, coordinator of the Marie Curie ETN DyVirt, and PI for the EPSRC programme on Engineering Nonlinearity (2012–2017). He co-authored Nonlinear Vibration with Control (2015) and edited books on structural dynamics. Lab/Teams: Involved in the Laboratory for Verification and Validation (LVV) and leads research groups focused on digital twin applications, inerter-based systems, and structural health monitoring.
John Whitney is an Associate Professor in the Department of Mechanical and Industrial Engineering at Northeastern University's College of Engineering. He joined the university in January 2016. His research focuses on human-safe robotics, medical robotics, soft robotics, MEMS, microrobotics, and bio-inspired design, with a particular emphasis on flapping aerodynamics and insect flight mechanisms. He has led major research initiatives including the National Science Foundation-funded 'Controllable Compliance' robotic arm project and Office of Naval Research projects on haptic manipulators for explosive ordnance disposal. Whitney holds a PhD in Engineering Sciences from Harvard University (2012) and an SM in Aeronautics and Astronautics from MIT (2006). He is affiliated with Northeastern's Institute for Experiential Robotics and has contributed to advanced systems like the ANA Avatar XPRIZE robotic avatar. His work integrates interdisciplinary approaches combining mechanical engineering, control systems, and biomedical applications. Education: PhD in Engineering Sciences, Harvard University, 2012 SM in Aeronautics and Astronautics, MIT, 2006 Awards: 2023 Impact Award Finalist, International Conference on Robotics and Automation 2022-2023 College of Engineering Faculty Award Recipient His research spans teleoperation systems, haptic feedback mechanisms, and soft material manufacturing. Notable projects include a MR-safe haptic system for prostate biopsies and a novel robotic arm for contact-rich environments. His lab's work on flapping-wing microrobots draws inspiration from insect flight dynamics to improve micro air vehicle (MAV) performance. Whitney advises teams like the Northeastern Mars Rover Team and ANA Avatar XPRIZE finalists, demonstrating his commitment to hands-on student engagement. His publications emphasize practical robotics solutions for medical, industrial, and exploratory applications.
Professor John D. Kubiatowicz is a faculty member at the University of California at Berkeley in the Department of Electrical Engineering and Computer Sciences since 1998. He holds a PhD in Electrical Engineering and Computer Science (minor in Physics) from MIT (1998), an M.S. in EECS (1993), and a double B.S. in Electrical Engineering and Physics (1987) from MIT. His research interests span Quantum Computing Architectures Distributed Systems and Storage Network Security and Peer-to-Peer Protocols Introspective and Manycore Operating Systems Edge and Fog Computing Hardware-Assisted Security He has pioneered systems like OceanStore , a global-scale distributed file system, and Tessellation , a manycore OS with continuous adaptation. The scientific awards he has received include Presidential Early Career Award (PECASE, 2000) Scientific American 50 (2002) Diane S. McEntyre Teaching Award (2003) IEEE ICRA Best Paper (2025) George M. Sprowls Award for MIT PhD thesis (1998) Okawa Research Grant (1998) Best Paper at International Conference on Supercomputing (1993) His recent publications focus on Quantum Circuit Design and Optimization Edge/Fog Computing Architectures Secure Runtime Systems Distributed Garbage Collection Manycore OS Innovations Hardware-Assisted Security Mechanisms He leads the Quantum Architecture Research Center and co-founded the SWARM Lab at Berkeley, advancing a vision of self-adapting, secure systems from the chip level to internet scale.
Prof. Gabriele Schrag holds the Professorship of Microsensors and Actuators at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. Her research focuses on MEMS (Micro-Electro-Mechanical Systems), including microsensors, actuators, and their applications in acoustics, microfluidics, and bioengineering. She has pioneered work in virtual prototyping for system-level modeling to enhance device robustness and performance. Education: PhD (summa cum laude) from TUM on 'Modeling coupled effects in microsystems' Habilitation in sensor systems technology (2018) Acting head of the Chair of Technical Electrophysics (2018-2023) Research emphasizes acoustic MEMS transducers , electrohydrodynamic printing , and physics-based modeling . Notable projects include developing piezoelectric MEMS microphones with corrugated membranes and integrated micropump systems. Awards include the Bavarian Prize for Good Teaching (2021) and Eurosensors Fellow Award (2019). Her work bridges virtual prototyping with real-world applications , addressing challenges in miniaturization, energy efficiency, and sensor integration for medical and industrial systems.
Günter J. Hitsch is the Kilts Family Professor of Marketing at the University of Chicago Booth School of Business, where he has been a faculty member since 2001. His academic leadership extends to editorial roles as Co-Editor of the Journal of Quantitative Marketing and Economics and Associate Editor at Marketing Science and Management Science. Hitsch's educational journey includes an undergraduate degree from the University of Vienna (1995), followed by master's degrees in economics (1997, 1998), and a PhD in economics from Yale University (2001). This strong foundation in economics informs his approach to marketing research. His research program focuses on quantitative marketing and industrial organization, with particular emphasis on dynamic models of firm and consumer decision-making. Key areas include advertising effectiveness, pricing strategies, sequential learning and experimentation, and intertemporal consumer choice. Hitsch is pioneering in applying causal inference and machine learning to solve practical marketing problems such as optimal customer targeting. His work on dating and marriage markets demonstrates innovative application of economic theory to social phenomena. Hitsch's publication trajectory shows evolution from foundational work on consumer choice and switching costs to more recent applications of machine learning in marketing contexts. His research spans theoretical development and practical application, examining everything from private label demand during economic recessions to television advertising effectiveness across hundreds of brands. Co-Editor, Journal of Quantitative Marketing and Economics Associate Editor, Marketing Science Associate Editor, Management Science Hitsch's editorial leadership has significantly shaped the direction of quantitative marketing research. His commitment to methodological rigor and generalizable results ensures his work provides reliable inputs for both marketing practitioners and academic researchers. As an educator, Hitsch teaches advanced courses in quantitative marketing and business analytics, with scheduled courses for 2024-2026. He emphasizes that 'good marketing isn't fluffy,' challenging students to develop analytical approaches to marketing problems. His research philosophy prioritizes providing generalizable results that apply beyond specific case studies, serving as inputs for both practitioner decision-making and academic advancement.
Tracy Becker is an Adjunct Assistant Professor in the Department of Civil Engineering at McMaster University, where she has been since 2014. Her expertise lies in the design, modeling, and experimental testing of high-performance structural systems with a focus on seismic isolation. Education: BS in Structural Engineering, University of California, San Diego MS and PhD in Structural Engineering, Mechanics and Materials, University of California, Berkeley Post-doctoral research at Kyoto University's Disaster Prevention Research Institute Research Interests: Becker specializes in seismic isolation systems, hybrid simulation methods, and structural performance under extreme events. Her work spans bridge engineering, nuclear infrastructure protection, and innovative materials for earthquake resilience. She integrates computational modeling with experimental validation to address challenges in: Nonlinear system behavior in isolated structures Multi-hazard optimization for seismic and wind loads Bridge management using data-driven and fuzzy logic frameworks Advanced gusset plate design for seismic retrofit Adaptive isolation systems for nuclear facilities Probabilistic lifetime demand predictions for infrastructure Teaching: She has instructed courses in Seismic Design (CIVENG 4ED4), Structural Mechanics (CIVENG 2C04), and Earthquake Engineering (CIVENG 730) at McMaster University.
Prof. Dr.-Ing. Udo Fiedler is a faculty member at the Technical University of Central Hesse (THM), Department of Business Administration and Economics, where he serves as Head of the Production Engineering Laboratory and Member of the Senate. His academic work focuses on manufacturing engineering with specialization in high-speed machining, production processes, and machine tools. His research interests include: High-Speed Machining (HSC) and precision manufacturing Green machining of sintered parts in the green state Process optimization using statistical experimental design Machine tool technology and NC programming Industry 4.0 applications in manufacturing education Process monitoring and control for increased manufacturing safety Prof. Fiedler's publication record demonstrates an evolution from fundamental machining processes toward integrating AI with traditional manufacturing. His recent work shows strong emphasis on applying artificial intelligence to quality prediction, optimizing green machining processes, and implementing Industry 4.0 concepts through learning factory approaches, bridging traditional manufacturing engineering with modern digital technologies. His significant scientific contributions include: Development of methods for NC programming of complex workpieces Research on stability lobe diagrams for milling processes Studies comparing different production methods including HSC, EDM, and generative processes Work on mechatronic tool holders for process monitoring Applications in the ophthalmic industry for precision machining of spectacle lenses Prof. Fiedler teaches multiple courses at THM including Factory Planning/Ergonomics, Handling and Assembly Technology, Innovative Manufacturing Processes, and Machine Tools at the bachelor's level, and Learning Factory 1 and 2 at the master's level. He leads current research projects including Klag-Robotics (2023-2025), Loewe Project OST (2018-2021), and GrünSpan (2014-2015), demonstrating sustained research activity across multiple manufacturing domains.
Professor Michael Ramage is a Senior Lecturer in the Department of Architecture at Cambridge University , where he directs the Centre for Natural Material Innovation . He is also a fellow of Sidney Sussex College and co-founder of Light Earth Designs . His academic background includes architecture studies at MIT and professional experience at Conzett Bronzini Gartmann in Switzerland. His research focuses on low-energy structural materials , natural material innovation , and sustainable housing in developing regions, with particular emphasis on engineered timber and bamboo . The 15 most recent publications highlight trends in modular timber construction , 3D printed earthen materials , and climate action in the building sector . Key subfields include circular economy , resource optimization , structural testing , and behavioral impacts on decarbonization . He has secured research funding from the Leverhulme Trust , Engineering and Physical Sciences Research Council (EPSRC) , Royal Society , and British Academy .
Cihan Tepedelenlioglu is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work bridges wireless communications, statistical signal processing, and renewable energy systems, with a focus on photovoltaic array monitoring, fault detection, and optimization. PhD, MS, and BS in Electrical Engineering from University of Minnesota, University of Virginia, and Florida Institute of Technology 2001 NSF CAREER Award recipient Research interests span wireless communications , graph signal processing , stochastic optimization , and machine learning applications to solar energy systems . Key projects include quantum machine learning for PV topology optimization, consensus algorithms for distributed networks, and real-time fault detection using neural networks. Recent articles emphasize machine learning in energy systems (2023-2025), with 12 publications on photovoltaic monitoring and 3 on consensus algorithms. Earlier work focused on channel estimation in OFDM systems and fading models in wireless communications. Scientific awards : NSF CAREER Award (2001) Major grants include NSF funding for networked solar array management (2013-2016), nonlinear distributed consensus (2013-2016), and statistical processing of solar data (2009-2012). Teaching roles include EEE 350 Random Signal Analysis and graduate research supervision in signal processing and wireless communications. Collaborates extensively with Andreas Spanias, Mahesh Banavar, and other researchers on cyber-physical systems for energy applications.
Christian Helland serves as an Assistant Professor in the Department of Sport and Social Sciences at the Norwegian School of Sport Sciences (NIH). Additionally, he works as a consultant in the strength department at Olympiatoppen (the Norwegian Olympic Training Center), where he is responsible for physical training programs for beach volleyball, para table tennis, and rowing athletes. Christian holds a master's degree from the Institute of Physical Performance and has been engaged in both practical and theoretical lecturing since 2012. His professional background includes competing as a beach volleyball player at the World Tour level since 2014, which provides him with valuable practical experience to complement his academic work. Dr. Helland's research focuses on optimizing athletic performance through scientific approaches to physical training. His work examines strength development, jump and sprint performance metrics, tendon mechanics, and recovery processes in elite athletes. His research has significant practical applications for coaches and athletes seeking to improve performance while minimizing injury risk. His publication record demonstrates a strong focus on force-velocity profiling, strength and power testing methodologies, and the physiological responses to different training modalities. A recurring theme in his work is the comparison of different training approaches and assessment methods, particularly examining how strength-oriented versus power-oriented training affects recovery needs and performance outcomes. His research often involves collaborations with other leading sports scientists across Norway and internationally. Christian teaches courses in volleyball, coaching methodologies, sports psychology, and sports practice for children and youth. His practical experience as an elite athlete informs his teaching approach, bridging theoretical knowledge with real-world application.
Lauri Rautkari is an Associate Professor in the Department of Bioproducts and Biosystems at Aalto University, Finland. His research focuses on water interactions in biomaterials, particularly wood, with an emphasis on developing advanced analytical methods for water vapor sorption, creating novel low-sorption materials, and investigating hygroscopicity and fungal decay resistance in modified wood systems. Research Highlights: Gas-phase ozone treatment for improved wettability, thermal and chemical wood modification, hyperspectral imaging for moisture prediction, bioinspired coatings for fungal protection, and interlaboratory studies on sorption data quality. Recent Publications: Key contributions to understanding lignin's role in moisture interactions, acetylation reversibility, and the impact of fungal degradation on heat-treated wood. The trend in his publications reflects a strong focus on hygroscopicity, chemical modification techniques (acetylation, melamine-formaldehyde impregnation), advanced imaging methods (hyperspectral, neutron scattering), and the development of sustainable wood-based materials for construction and acoustic applications. Collaborative interlaboratory efforts dominate his work, ensuring standardized methodologies for moisture analysis.
Dr. Adrian Fazekas is a Lecturer at the Institute of Highway Engineering, RWTH Aachen University, and collaborates with the Federal Highway Research Institute (BASt). He holds a Dr.-Ing. in Computer Science from RWTH Aachen (2005–2011), specializing in Media Engineering. His professional trajectory includes roles as a Research Assistant at RWTH Aachen and industry experience as a Software Developer at Continental AG. Research interests focus on traffic data acquisition , microscopic traffic flow simulation , and intelligent transportation systems . Key projects include: DROVA: Drone-based traffic analysis for infrastructure optimization ESIMAS: Real-time tunnel safety management Digital Twin Road: Physical-informational mapping of future highways AUTUKAR: Automated tunnel monitoring systems His publications emphasize real-time traffic detection , safety analytics , and data-driven modeling , with recent work exploring thermal-camera nudging systems and weigh-in-motion accuracy. He actively contributes to the Research Association for Roads, Earth and Tunneling (SETAC). No awards or student advising roles are documented.
Fei He is an Associate Professor at Tsinghua University's School of Software, where he leads the THUFV research lab focused on formal verification and program analysis. His research spans formal methods, automated reasoning, and program verification, with applications in concurrent systems, networking (P4 programs), and probabilistic systems. Education & Employment: PhD from Tsinghua University (2008) Visiting Scholar at Carnegie Mellon University (2010-2011) and Politecnico di Milano (2006-2007) Faculty positions at Tsinghua since 2008 (Assistant Professor 2008-2011, Associate Professor 2011-present) Research: He's developed innovative techniques in SMT solving for concurrency verification, termination analysis, and regression verification. His tools like Deagle have won gold medals at SV-COMP. Current work focuses on probabilistic program verification and network program analysis. Publications: His 80+ publications demonstrate consistent contributions across formal methods (PLDI, OOPSLA, ICSE), networking (NSDI, INFOCOM), and software engineering (TSE, TOSEM), with recent emphasis on data-driven verification and automated invariant inference. Awards: Gold Medals in SV-COMP ConcurrencySafety (2022, 2023, 2025) Best Paper Awards at PPoPP 2022 and SETTA 2022 Advising: Mentors 13 PhD/Master's students in THUFV lab, with graduates joining Huawei, MPI-SP, and research institutions. Secured multiple NSF China grants for trustworthy software research. Service: Associate Editor for Theory of Computing Systems, program committees for PLDI/ICSE/OOPSLA, and former Local Chair for ISSTA 2019.
Todd Millstein is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA). He served as the Computer Science Department Chair from 2022-2025 and is also an Amazon Scholar. His research focuses on making software systems more reliable through programming languages techniques, with significant contributions to network verification and probabilistic programming. Millstein received his Ph.D. from the University of Washington Department of Computer Science, where he was a member of the Cecil group led by Craig Chambers. Prior to that, he completed his undergraduate studies at Brown University under the guidance of Paris Kanellakis and Pascal Van Hentenryck. Millstein's research spans several areas of programming languages and systems with a focus on reliability. He has made significant contributions to network verification, developing the Batfish network configuration analyzer which is now managed by Amazon Web Services and forms the basis of Oracle Cloud's Network Path Analyzer. His work has been recognized with the ACM SIGCOMM Networking Systems Award in 2025. He also works on interactive program verification through lemma synthesis and scalable reasoning methods for probabilistic programming languages. His research bridges programming languages theory with practical systems challenges, as highlighted in his SPLASH/OOPSLA 2024 keynote "Everything is a Program (even if it's not)". Millstein's recent publications demonstrate a consistent focus on verification and reliability across multiple domains. His work shows a progression from foundational programming language techniques to practical applications in networking and probabilistic systems. Key themes include data-driven approaches to program analysis, synthesis of verification artifacts, and applying programming languages techniques to non-traditional domains like network configuration. Millstein's scientific achievements have been recognized with numerous prestigious awards including an NSF CAREER Award, an ACM SIGPLAN Most Influential PLDI Paper Award, an ACM SIGCOMM Networking Systems Award, IEEE Micro Top Picks selection, best-paper awards from PLDI, OOPSLA, and SIGCOMM, a Microsoft Research Outstanding Collaborator Award, an Okawa Foundation Research Grant, an IBM Faculty Award, and a Facebook Research Award. He has also received both the Northrop Grumman Excellence in Teaching Award (for junior faculty) and the Eon Instrumentation Inc. Excellence in Teaching Award (for senior faculty) from UCLA Engineering. Millstein advises several Ph.D. students including Ana Brendel, Poorva Garg (co-advised with Guy Van den Broeck), Rajdeep Mondal (co-advised with George Varghese), and Rathin Singha (co-advised with George Varghese). His research has been supported by various grants including an NSF CAREER Award, Okawa Foundation Research Grant, IBM Faculty Award, and Facebook Research Award. He has also been a Co-Founder and Chief Scientist of Intentionet, which was later acquired by Amazon Web Services. Millstein is actively involved in the Batfish project, an open-source network configuration analyzer that has had significant practical impact. Batfish is now managed by AWS, powers Oracle Cloud's Network Path Analyzer, and is used by dozens of companies. His research group continues to work on network reliability, developing techniques for scalable BGP policy verification and behavioral testing of protocol implementations.
Zhibin Chen is an Assistant Professor of Engineering at NYU Shanghai and concurrently a Global Network Assistant Professor within the broader New York University system. Since January 2019 he has led research and teaching activities at the Division of Engineering and Computer Science in Shanghai, while maintaining university-wide collaborations through his Global Network appointment. Education Ph.D. in Transportation Engineering, University of Florida (2017) Research Interests Dr. Chen’s scholarship centres on Transportation Network Modeling and Optimization , Intelligent Transportation Systems , and Discrete Optimization . He integrates operations research, data science, and engineering to address emerging challenges in electric mobility, autonomous vehicles, and large-scale urban networks. Recent thrusts include: Data-driven analytics of electric-vehicle charging behaviour under usage heterogeneity. Optimization of charging and swapping infrastructure for electric buses and trucks. Network-level deployment and control strategies for connected and automated vehicles. Day-to-day traffic dynamics and equilibrium models with elastic demand. Pricing, policy, and incentive design for sustainable transportation systems. Scientific Awards Stella Dafermos Best Paper Award – awarded at the 95th Transportation Research Board Annual Meeting. Ryuichi Kitamura Paper Award – also conferred at the 95th TRB Annual Meeting. Editorial & Professional Service Dr. Chen currently serves on the Editorial Advisory Board of Transportation Research Part C: Emerging Technologies , shaping the editorial direction of the leading journal in his field. Grants & Collaborations While specific grant identifiers are not disclosed in the provided text, Dr. Chen’s extensive publication record in top-tier journals ( Transportation Science , Transportation Research Parts B, C, D , IEEE ITS , Applied Energy ) and his editorial role indicate sustained research funding and active collaboration with international partners across North America and China. Laboratories & Teams Operating within the Division of Engineering and Computer Science at NYU Shanghai , Dr. Chen leads a research group focused on next-generation mobility analytics, leveraging the university’s interdisciplinary ecosystem and NYU’s Global Network resources to advance smart and sustainable transportation.
