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Federica De StefanoView profile

Associate Professor

• Strategic Human Capital
• Employee Mobility
• Career Development
• +3 more

Federica De Stefano is an Associate Professor of Organisation Studies at Saïd Business School, University of Oxford, and a Research Fellow of Green Templeton College. She serves on editorial boards for Organization Science , Human Resource Management , and Human Resource Management Review , while holding roles in the Strategic Management Society (SMS). Previously, she was an Assistant Professor at HEC Paris and a Post-Doctoral Fellow at Wharton People Analytics. She earned a PhD from Bocconi University, with additional degrees from Fudan University and Bocconi. Her research focuses on people management's impact on organizational and individual outcomes, including employee mobility, workplace safety, and social sustainability. Using quantitative methods and large datasets, her work has been published in top journals like Academy of Management Journal and Strategic Management Journal . She has received the Marie Curie Individual Fellowship and recognition as a top 40-under-40 MBA professor. Teaching focuses on people analytics and management, with a 2023 completion of the International Teachers Program (ITP). Her research grants and collaborative work at Wharton People Analytics underscore her commitment to advancing strategic human capital practices. Federica's work bridges academic rigor with real-world organizational challenges, emphasizing ethical and sustainable workforce strategies.

H. Jerry QiView profile

Professor

• Soft Active Materials
• 4D Printing
• 3D Printing Technologies
• +5 more

H. Jerry Qi is a Professor in the Department of Mechanical Engineering at the Georgia Institute of Technology. He specializes in finite deformation multiphysics modeling of soft active materials, with a focus on shape memory polymers, 4D printing, and material recycling. His research integrates experimental and computational approaches to advance additive manufacturing technologies. Education: Sc.D., Massachusetts Institute of Technology, 2003 Ph.D., Tsinghua University, China, 1999 B.S., Tsinghua University, China, 1994 Research Interests: Dr. Qi's work spans 4D printing of active materials, mechanics in 3D printing, and sustainable polymer processing. His group develops hybrid printing methods and recyclable thermosetting polymers, collaborating with institutions like SUTD and AFRL. Key areas include smart material design, photomechanical experiments, and finite element modeling. Scientific Awards: ASME Fellow (2015) Woodruff Faculty Fellow (2015) J. T. Oden Faculty Fellowship (2012) NSF Career Award (2007) Advising & Grants: Dr. Qi actively seeks undergraduate, PhD, and postdoc researchers. His projects are funded by NSF, AFOSR, and industry partnerships. He leads a research group focused on advancing active materials and sustainable manufacturing. Labs & Teams: His lab integrates computational modeling, experimental mechanics, and additive manufacturing to create innovative materials and structures for applications in aerospace, biomedical, and environmental engineering.

Oliver SchmitzView profile

Professor

• Plasma Edge Physics
• Plasma Wall Interaction
• Three-Dimensional Plasma Edge Transport
• +6 more

Oliver Schmitz is a Professor in the Department of Nuclear Engineering & Engineering Physics at the University of Wisconsin-Madison, where he leads research in plasma edge physics for magnetic confinement fusion and next-generation particle accelerators. His work bridges experimental plasma science, computational modeling, and diagnostic development with applications in both tokamaks and stellarators. Education: PhD (2006), Heinrich-Heine-Universität Diploma (2003), Rheinische Friedrich-Wilhelms-Universität Professor Schmitz's research focuses on 3D plasma edge transport phenomena, plasma-wall interactions, and helicon plasma generation for wakefield accelerators. His group employs advanced computational tools like EMC3-EIRENE for 3D plasma edge modeling and develops active spectroscopic diagnostics to measure plasma parameters through atomic emission analysis. Key themes include resonant magnetic perturbation effects in tokamaks, inherent 3D physics in stellarators, and high-density plasma sustainment for accelerator applications. He actively develops atomic models to interpret spectroscopic data and operates helicon plasma test stands for fundamental process studies. Recent publications reveal strong emphasis on experimental-computational integration for fusion boundary physics, with significant contributions to ITER divertor solutions, stellarator exhaust optimization, and plasma-facing materials. The work shows growing focus on wakefield accelerator diagnostics through helicon plasma sources and advanced spectroscopy, alongside persistent innovation in 3D modeling of plasma-material interfaces. Scientific Awards: 2020 Thomas and Suzanne Werner Chair Professorship 2018 UW Madison Teaching Academy Fellow 2017 ITER Science Fellowship & Vilas Mid-Career Award 2015 DOE Early Career Award & NSF CAREER Award 2011 Torkil Jensen Award (General Atomics) 2007 Günther-Leibfried-Preis (Jülich) Professor Schmitz directs multiple DOE/NSF-funded research programs including his UW Madison laboratory and AWAKE project contributions at CERN. He mentors graduate students through NE 890/990 thesis research courses and has developed nationally recognized K-12 outreach including the "Plasma Show" for elementary schools and "Plasma Academy" for high-school educators developing AP Physics curriculum modules. His leadership extends to university governance through the Kaufman seminar on academic leadership. His research group operates helicon plasma test stands and computational facilities for EMC3-EIRENE simulations, with current efforts focused on high-density plasma sources for accelerators and resilient divertor solutions for stellarators. The group maintains strong international collaborations with ITER, CERN, and major fusion facilities worldwide.

LU Wen FengView profile

Adjunct Associate Professor

• Additive Manufacturing
• Robotics
• Smart Manufacturing
• +4 more

LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.

• Friction stir welding
• Steel metallurgy
• Materials engineering
• +4 more

Dr. Athanasios Toumpis is a Senior Lecturer in Mechanical and Aerospace Engineering at the University of Strathclyde, UK. He holds a Master of Science from the University of Glasgow (2012) and a Master of Engineering from the National Technical University of Athens (2003). His research focuses on friction stir welding (FSW), steel metallurgy, and fatigue analysis of structural materials. Key areas include defect analysis in FSW joints, thermal-mechanical behavior of materials, and gigacycle fatigue testing of welded steels. He has led multiple research projects funded by organizations like the Royal Society and Weir Group, including the development of novel FSW technologies for nuclear applications and investigations into steel joint performance under extreme conditions. Dr. Toumpis has authored over 50 publications, with recent work emphasizing very high-cycle fatigue behavior and additive manufacturing processes. He actively participates in international conferences and serves as a principal investigator on various collaborative projects. His teaching includes courses on applied metallurgy, biomaterials, and materials selection. Research Interests: Friction stir welding of low-alloy and stainless steels Fatigue analysis of welded joints, including gigacycle testing Thermal-mechanical analysis of additive manufactured materials Metallurgical characterization of dissimilar material joints Environmental impact assessment of manufacturing processes Professional Activities & Awards: Recipient of the Global Engagement Fund (2024) Organized the First Joint International Conference on Advances in Mechanical and Aerospace Engineering (2023) Participant in the International Institute of Welding Assembly (2024) and Very High Cycle Fatigue Conference (2024) Hosted visiting researchers and collaborated with institutions like Graz University of Technology Grants & Projects (Recent): Development of a novel friction stir additive manufacturing technology (Royal Society, 2025–2026) Investigation of friction stir welded steel joints for giga-cycle applications (Weir Group, 2025–2027) ESCO buckets weld performance investigation (University of Strathclyde, 2024–2027)

• Quality and Reliability Engineering
• Design of Experiments
• Time Series Analysis
• +6 more

Rong Pan is a Professor at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He holds a Ph.D. in Industrial Engineering from Pennsylvania State University (2002), an M.S. from Florida A&M University (1999), and a B.S. in Materials Science from Shanghai Jiao Tong University (1995). His research focuses on quality and reliability engineering, design of experiments, time series analysis, and statistical learning theory. Key projects involve NSF-funded research on reliability prediction, accelerated life testing, and degradation modeling. He serves as an Associate Editor for the Journal of Quality Technology and has authored over 80 publications. Courses taught include Reliability Engineering, Design of Experiments, and Statistics for Data Analysts. His academic service includes roles as a referee for IEEE Transactions and IIE journals. Research interests emphasize statistical methods for reliability improvement, with recent work on Bayesian inference models, optimal experimental design, and machine learning applications in industrial systems. Grants include collaborations with the NSF, Arizona Department of Transportation, and Science Foundation Arizona. His work bridges theoretical advancements and practical applications in manufacturing, energy systems, and semiconductor reliability. Education: Ph.D. (2002), M.S. (1999), B.S. (1995) Key Research Areas: Reliability Engineering, Bayesian Methods, Time Series, DOE Active Grants: NSF CMMI, SUNY IT Visiting Scholar Program Teaching: IEE 573 Reliability Engineering, DSE 501 Statistics Service: Journal of Quality Technology (Associate Editor), IEEE Transactions (Referee)

• Fluid Dynamics
• Renewable Energy Technologies
• Mechanical Engineering Education
• +3 more

Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.

Ming CaoView profile

Professor

• Multi-agent systems
• Autonomous Robots
• Complex Systems and Networks
• +4 more

Ming Cao is a Full Professor at the University of Groningen (Netherlands), holding positions in the Department of Discrete Technology and Production Automation, the Engineering and Technology Institute Groningen, and serving as Chair of the Jantina Tammes School of Digital Society, Technology and AI. His academic roles include Director of the Jantina Tammes School and membership in prestigious organizations such as the International Federation of Automatic Control (IFAC) and the European Commission’s DG CNECT. Cao’s research focuses on multi-agent systems, autonomous robotics, complex networks, and cooperative control, with applications in robotics, epidemic modeling, and biomimetic sensors. Education: PostDoc in Mechanical Engineering from Princeton University (2008), PhD in Electrical Engineering from Yale University (2007). Research Interests: Multi-agent systems, distributed decision-making, cooperative control, robotic teams, seal whisker-inspired flow sensing, and privacy-preserving control systems. Recent Trends in Articles: Recent work emphasizes co-evolutionary dynamics in social-technical systems, privacy in control systems, and biomimetic robotics. Key topics include feedback mechanisms in cooperation, hypergraph-based epidemic models, and seal whisker mechanics for underwater sensing. Awards: European Control Award (2016), Manfred Thoma Medal (2017), ERC Grant (2012). Grants: Vidi Grant from NWO (2015) for agent coordination research. Labs/Teams: Jan C. Willems Center for Systems and Control, Research Center for Data Science and Systems Complexity (DSSC). Active in editorial roles for journals like Artificial Life and Robotics and the SIAM Journal on Control and Optimization .

Wenzel JakobView profile

Associate Professor

• Inverse Graphics
• Differentiable Rendering
• Physically Based Rendering
• +7 more

Wenzel Jakob is an Associate Professor and leader of the Realistic Graphics Lab at EPFL's School of Computer and Communication Sciences , currently on sabbatical at the University of Tokyo until Fall 2025. His work bridges inverse graphics , physically based rendering , and compiler/systems research , with a focus on developing robust differentiable rendering frameworks. Key research themes include: Backpropagation through rendering algorithms for inverse problems Material appearance modeling and optical measurement systems Compiler design for differentiable rendering pipelines Manifold sampling techniques and light transport derivatives His group created Mitsuba renderer , Dr.Jit , and Instant Meshes (recipient of the SGP Software Award). Recent publications (2021–2024) explore volumetric rendering, SDF-based differentiable systems, and efficient Monte Carlo estimators. Awards include the ACM SIGGRAPH Significant Researcher Award , Eurographics Young Researcher Award , and ERC Starting Grant . Teaching roles (2016–2024) span Advanced Computer Graphics and Numerical Methods for Visual Computing courses at EPFL.

• Multidisciplinary design optimization
• Topology optimization
• Aeroelasticity
• +3 more

Kai A. James is an Associate Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in Computational Science and Engineering. He holds a Ph.D. (2012) and M.A.Sc. (2006) from University of Toronto, and B.A.Sc. (2004) in Engineering Science. His research focuses on multidisciplinary design optimization, topology optimization, aeroelasticity, and nonlinear mechanics, with applications to aerospace structures, additive manufacturing, and smart materials. He teaches courses such as Structural Design Optimization (AE 498), Nonlinear Solid Mechanics (AE 598), and Finite Element Analysis (ME 471). His honors include the NSF CAREER Award (2018), Scott White Aerospace Engineering Fellow (2020), and UIUC Teacher of the Year (2017). His work spans academic publications (over 50 journal/conference articles listed) and innovations in topology optimization frameworks for complex systems. Recent research emphasizes bi-stable structures (e.g., cardiovascular stents, morphing airfoils), thermomechanical design of shape-memory alloys, and spatial packing optimization for engineering systems. His lab, located in Talbot Laboratory, develops computational tools for multiphysics and multiscale design optimization.

Farhad AslaniView profile

Associate Professor

• Structural Engineering
• Concrete Engineering
• Sustainable Construction Materials
• +5 more

Dr. Farhad Aslani is an Associate Professor in the Department of Civil, Environmental and Mining Engineering at the University of Western Australia (UWA), serving as Director of the Materials and Structures Innovation Group. He leads the $250M Australian Composites Manufacturing CRC and co-leads UWA's Engineering Materials Research Cluster. His research focuses on innovative construction materials, including self-sensing concrete, 3D-printed composites, and fire-resistant materials. He has secured over $20M in CRC funding and holds leadership roles in national/international conferences. Key awards include the 2024 Concrete Institute WA Rising Star Award and multiple citation milestones. His work aligns with sustainable development goals, emphasizing eco-friendly materials and infrastructure resilience. Education: PhD in Structural Engineering, University of Technology Sydney (2014) Certificates in Leadership, Research Commercialization, Public Policy, and Project Management from Curtin University, Queensland University of Technology, RMIT, and UTS. Research Interests: Smart materials, sustainable concrete technologies, additive manufacturing, blast/fire resistance, and composites for infrastructure. His lab develops self-sensing concretes, lightweight engineered composites, and electromagnetic shielding materials. Grants & Projects: $4.3M ACM CRC project on composite repairs ARC grants for nanocomposite coatings and fire facilities Main Roads WA funding for timber bridge strengthening Expertise: Structural design, composite materials, and industrial collaborations (e.g., Woodside, Holcim). He advises on major projects like the Morley Ellenbrook Rail Line and Forrestfield Airport Link. Awards: 2024 Concrete Institute WA Rising Star Highly Cited Scholar (ScholarGPS, 2024) Most Cited Paper Awards (2018–2020)

Dominic Liao-McPhersonView profile

Assistant Professor

• Control Theory
• Optimization
• Algorithmic Control
• +7 more

Dominic Liao-McPherson serves as an Assistant Professor in the Department of Mechanical Engineering within the Faculty of Applied Science at the University of British Columbia. His research bridges algorithmic control, optimization theory, and computational engineering with practical applications across robotics, energy systems, and aerospace domains. His academic background includes a BASc from the University of Toronto, PhD from the University of Michigan, and postdoctoral training at ETH Zürich: BASc (University of Toronto) PhD (University of Michigan) Postdoc (ETH Zürich) Dr. Liao-McPherson's research centers on developing real-time computational decision-making algorithms for physical systems. His work spans predictive and constrained control (including model predictive control and reference governors), real-time embedded optimization, and game-theoretic coordination mechanisms for multi-agent systems. Key application areas include energy grids, autonomous vehicles, additive manufacturing, and aerospace systems, with past projects covering spacecraft landing, engine emissions control, and aircraft upset recovery. His methodology emphasizes rigorous stability analysis, constraint satisfaction, and practical implementation on resource-constrained hardware. Analysis of his 2020-2022 publications reveals a strong focus on advancing optimization-based control frameworks. His work consistently addresses stability guarantees and constraint handling in real-time systems, with increasing emphasis on distributed algorithms for multi-agent coordination. The research demonstrates a clear trajectory from theoretical algorithm development (e.g., FBstab solver) toward experimental validation in complex engineering systems like diesel engines and autonomous networks. No scientific awards are documented in the provided materials. Regarding academic advising and research funding, the source text contains no information about current students, grant awards, or sponsored research projects. He directs the Algorithmic Optimization and Control Lab (AOCL) at UBC, as evidenced by his research website (aocl.mech.ubc.ca). The lab specializes in developing computationally efficient control algorithms for embedded systems, with particular expertise in handling physical constraints and coordination challenges in multi-agent environments across energy, manufacturing, and robotics applications.

Torsten Wolfgang KuhlenView profile

Professor

• Virtual Reality
• Immersive Visualization
• Scientific Visualization
• +5 more

Prof. Torsten Wolfgang Kuhlen serves as a Universitätsprofessor at RWTH Aachen University, leading the Teaching and Research Area for Virtual Reality and Immersive Visualization within the Department of Computer Science. He is affiliated with Chair of Computer Science 12 (High Performance Computing), the Visual Computing Institute, and remains an integral part of the RWTH IT Center where his research group operates one of the world's largest Virtual Reality laboratories including the 30 sqm aixCAVE visualization chamber. The group maintains strong connections with Computational Science & Engineering Division, National High Performance Computing Center for Computational Engineering Science (NHR4CES), and VR in Science and Industry Network NRW e.V. Prof. Kuhlen's research spans virtual reality, immersive visualization, and multimodal 3D user interfaces with applications across simulation science, production technology, neuroscience, and medicine. His work combines basic research on advanced methods and algorithms with interdisciplinary collaborations involving RWTH Aachen institutes, Forschungszentrum Jülich, and industry partners. Recent publications demonstrate strong focus on audiovisual perception, immersive analytics, collaborative virtual environments, and practical VR applications in education and manufacturing. His research group has produced significant work on listening effort in virtual environments, immersive authoring techniques, and VR applications for scientific visualization. Notable projects include VRScenarioBuilder for automated vehicle testing and applications in monitoring additive manufacturing processes. The group actively participates in major conferences including IEEE VIS and EuroVis, with several award-winning contributions. Prof. Kuhlen has advised PhD students including Martin Bellgardt who recently completed his doctoral degree on "Increasing Immersion in Machine Learning Pipelines for Mechanical Engineering". The research group maintains state-of-the-art VR infrastructure including the aixCAVE facility which is open to all RWTH research groups.

• Differential Privacy
• Machine Learning
• Privacy-Preserving Data Analysis
• +3 more

Daniel Kifer is a Professor in the Computer Science and Engineering department at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His work bridges computer science, privacy-preserving machine learning, and geoscience applications. With over 10,000 citations and a high h-index, he focuses on methods to unify theoretical and applied research. Research Interests: Differential Privacy, Privacy-Preserving Machine Learning, Physics-Informed Neural Networks, Landslide Prediction, and Formal Verification of Privacy Systems. Recent projects include grants from the National Science Foundation: SaTC: CORE: Small (2024): privacy-preserving user data embedding in machine learning pipelines. SaTC: CORE: Medium (2017-2023): formal methods for differential privacy and accuracy optimization. His research outputs span domains like geoscience, database systems, and policy analysis, emphasizing precision and scalability of privacy-preserving algorithms.

• Fatigue strength of aluminum structures
• Fracture mechanics
• Railway bridge assessment
• +4 more

Dorina Siebert is a Researcher at the Chair of Metal Construction within the School of Engineering at the Technical University of Munich. She has been working as a research assistant at the Chair since 2019, contributing to various research projects related to steel and aluminum construction, fracture mechanics, and additive manufacturing in construction. Education: M.Sc. in Civil Engineering from Technical University of Munich (2012-2019) Affiliation: Chair of Metal Construction, School of Engineering, Technical University of Munich Contact: dorina.siebert@tum.de, Room 0101.Z1.038, +49 (89) 289-22527 Dorina's research primarily focuses on the fatigue strength of aluminum structures, fracture mechanics in railway bridges, and the application of additive manufacturing techniques in construction. Her work on powder bed-based laser beam melting of metal has significant implications for modern construction methods. She also investigates safe operating time intervals for historic steel bridges and has contributed to the development of a mobile vehicle barrier, demonstrating the practical applications of her theoretical work. Her publication record shows a strong trend toward computational and experimental analysis of material behavior under stress, particularly in aluminum alloys and steel structures. She has published extensively on fatigue properties, fracture mechanics calculations, and additive manufacturing applications, with a clear progression toward more complex modeling techniques and practical engineering solutions. Her work bridges theoretical computational models with real-world infrastructure challenges. Dorina teaches courses including 'Constructing with aluminum' for the Summer semester 2025 and 'Fracture mechanics and fatigue' for the Winter semester 2024/25. She also leads a seminar on plate buckling and steel bridge construction, sharing her specialized knowledge with engineering students. Her teaching directly reflects her research expertise, creating a strong connection between theoretical knowledge and practical application for her students.