جست‌وجوی استاد و پژوهشگر

Gianluca Piazzaمشاهده پروفایل

استاد

• MEMS/NEMS
• Nanotechnology
• Piezoelectric Devices
• +۷ مورد دیگر

Gianluca Piazza is the STMicroelectronics Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Mechanical Engineering. He directs the John and Claire Bertucci Nanotechnology Laboratory (CMU Nanofab). Previously, he was the Wilf Family Term Assistant Professor at the University of Pennsylvania. His research focuses on piezoelectric micro/nano electromechanical systems (M/NEMS) for RF communication, optomechanics, chemical/biological sensing, and mechanical computing. Key projects include nanorelays for low-power computing, ultrasound-based wireless powering, and piezoelectric MEMS for energy harvesting. Education: PhD (2005) in Electrical Engineering from UC Berkeley; MS (2001) from University of Texas at Austin and Politecnico di Milano (Italy). Research Interests: M/NEMS design, micro/nano fabrication, piezoelectric materials, mechanical switches, and energy-efficient electronics. His work bridges fundamental science and applied engineering, with patents in micromechanical resonators and awards including the IBM Young Faculty Award (2006) and multiple IEEE Best Paper Awards. Grants & Collaborations: NSF LEAP-HI grant ($2M) for nanorelay development (2020); CMU Kavčić-Moura Endowment funding. Collaborates with Maarten de Boer (Mechanical Engineering) and institutions like the University of Pennsylvania and City University of Hong Kong. Labs & Teams: Leads the Piazza Micro and Nano Systems Laboratory, focusing on NEMS/MEMS innovation. Active in CMU’s Center for Silicon System Implementation and Engineering Research Accelerator.

Cara M. Nunezمشاهده پروفایل

استادیار

• Haptics
• Human-Computer Interaction
• Sensory Devices
• +۲ مورد دیگر

Cara M. Nunez is an Assistant Professor in Mechanical and Aerospace Engineering at Cornell Engineering. Her research focuses on haptic interfaces, sensory perception, and human-robot interaction. Research Areas: Development of wearable haptic devices for sensory feedback Human perception of tactile stimuli under cognitive load Multimodal interaction combining haptic, audio, and visual cues Medical applications of haptic guidance systems Key publications explore smartphone-based sensory assessment, affective mediated touch, and haptic guidance for medical procedures. Her work appears in robotics and human-computer interaction venues.

Yves Leterrierمشاهده پروفایل

پژوهشگر

• Sustainable materials and processes
• Polymer composites and hybrid materials
• Photopolymerization and sol-gel processes
• +۷ مورد دیگر

Yves Leterrier is a Senior Scientist and lecturer at École Polytechnique Fédérale de Lausanne (EPFL), where he has been a faculty member since 1993. He works in the Laboratory for Processing of Advanced Composites (LPAC) within the Institute of Materials at the School of Engineering. His academic career spans over three decades with significant contributions to sustainable materials science and polymer composite technologies. Senior Scientist, Laboratory for Processing of Advanced Composites (LPAC) Teaching roles in SMX and EDMX programs PhD program committee member for Materials Science and Engineering Author of over 300 technical articles including 145 peer-reviewed journal papers Leterrier's research focuses on sustainable materials and processes, particularly in polymer composites, multilayer and hybrid materials, photopolymerization and sol-gel processes, mechanics of thin films on polymers, and roll-to-roll process methods. His work bridges fundamental materials science with practical applications in flexible electronics, renewable energy, and sustainable packaging. He has pioneered techniques for creating bioinspired surfaces, diffusion-barrier coatings, and cost-effective manufacturing processes for advanced materials. His recent publications reveal a strong emphasis on water permeation monitoring in bioelectronic implants, fluorine-free superhydrophobic surfaces, and biobased composites using nanocellulose. His research shows a clear trajectory toward sustainable materials solutions with applications in medical devices, flexible electronics, and environmentally friendly packaging. The consistent theme across his work is the development of reliable, high-performance materials through innovative processing techniques and composite design. Leterrier actively contributes to the academic community through editorial roles, including serving on the editorial board of Applied Surface Science since 2012 and as Associate Editor for Frontiers in Materials since 2014. He coordinates EPFL's Minor on 'Engineering for Sustainability' and has been President of the EPFL Materials Science Library commission since 2000. His leadership extends to industry collaboration through multiple funded research projects. His current research portfolio includes significant projects such as BioPack (biobased packaging materials), FLEXCAN (flexible encapsulation of active implants), 3DP4PEACE (sustainable 3D printing), and DuPrintProtect (advanced manufacturing). Previously, he led projects including XinoCaps, UltraCeal, SUNLITE, and REFLEX, demonstrating consistent funding success across diverse materials science applications. He also serves on the board of the French Adhesion Society and has organized international symposia on materials and micro-technologies. Leterrier leads the Laboratory for Processing of Advanced Composites, where his team develops cutting-edge materials processing techniques. His work on photo-hyphenated methods, UV nanoimprint lithography, and electro-fragmentation analysis represents the laboratory's focus on innovative characterization and manufacturing approaches for advanced materials.

David Parkerمشاهده پروفایل

استاد

• Formal Verification
• Probabilistic Model Checking
• Quantitative Analysis
• +۲ مورد دیگر

David Parker is Professor of Computer Science at the University of Oxford and a Tutorial Fellow at Trinity College. His research focuses on formal verification methods for checking system correctness, particularly quantitative verification techniques for probabilistic systems. As leader of the PRISM and PRISM-games projects, he develops tools for analyzing safety, reliability, and performance properties in complex systems. Current research explores verification of AI systems, robust decision-making under uncertainty, and multi-agent systems using stochastic games. His work bridges theoretical foundations with applications in autonomous systems, robotics, and healthcare technology. Recent publications demonstrate advancements in probabilistic temporal logic, robust policy learning, and bisimulation techniques for Markov models. These works consistently emphasize formal guarantees for safety-critical applications and novel approaches to model checking. ETAPS Test-of-Time Tool Award (2024) HVC Award (2016) Professor Parker mentors PhD students in verification, control synthesis, and AI safety, with research funded by ERC, EPSRC, and industrial partners. He serves on editorial boards for Formal Aspects of Computing and ACM Transactions on Autonomous Systems.

David Mowbrayمشاهده پروفایل

استاد

• Semiconductor Physics
• Quantum Dots
• Nanowire Growth
• +۵ مورد دیگر

Professor David Mowbray is a Professor of Physics at the University of Sheffield, affiliated with the School of Mathematical and Physical Sciences and the Department of Physics. His research focuses on III-V semiconductors, quantum dots, and nanostructures, emphasizing applications in high-efficiency lasers and light emitters. He has pioneered studies on AlGaInP band structures and quantum dot-based devices, including lasers on Si substrates for silicon integration. Qualifications: B.A. in Physics (Hertford College, Oxford, 1984) and D.Phil. in Physics (Hertford College, Oxford, 1989). Research interests include optical spectroscopy of wide band gap materials (AlGaInP, AlInGaN) for visible/UV emitters, quantum dot lasers with low threshold currents, and nanowire quantum dots for single-photon sources. Current projects involve quantum dots in quantum wires with UCL and Warwick, aiming for nanoscale lasers and efficient photon sources. Teaching includes courses on Fourier Techniques, Electromagnetism, and nanotechnology. He has held leadership roles, such as Head of Department and Senior Tutor, and serves on professional committees like the Institute of Physics Degree Accreditation Committee. Grants include EPSRC funding for quantum dot lasers on Si (2012–2016) and nanowire quantum dots for silicon-based emitters (2016–2020). His work bridges semiconductor physics, nanostructure engineering, and optoelectronic device applications.

Donya Hajializadehمشاهده پروفایل

دانشیار

• Structural Health Monitoring
• Machine Learning
• Asset Management Systems
• +۴ مورد دیگر

Dr Donya Hajializadeh is an Associate Professor of Structural Engineering at the University of Surrey's School of Sustainability, Civil and Environmental Engineering. She holds multiple professional qualifications including Chartered Engineer (CEng) and European Engineer (EUR ING), and is a Fellow of the Higher Education Academy (FHEA). Her roles include Director of Employability (since 2020), Deputy Coordinator of the Surrey/ICE Scholarship (since 2019), and IStructE Liaison Officer (since 2021). She is also affiliated with the Surrey Institute for People-Centred Artificial Intelligence (PAI). Her education includes a BEng (Hons), MEng, and PhD in relevant fields. Research focuses on structural health monitoring (SHM), machine learning applications in asset management, and deep learning for damage identification. Key areas include railway bridge dynamics, vibration analysis, and resilience assessment under seismic and environmental hazards. Current PhD students include Chia Sadik (Transport Infrastructure Failure Assessment) and Michael Millgate (Dynamic Characterisation of Tall RC Buildings). Teaching responsibilities include ENG1073 Fluid Mechanics and ENGM054 Earthquake Engineering. Research aligns with sustainable development goals, emphasizing infrastructure sustainability and carbon reduction strategies. Notable projects include rail bridge innovation recognized by the Chief Scientific Adviser Award and presentations on damage identification techniques to government officials. She contributes actively to interdisciplinary initiatives, integrating AI with civil engineering for smarter infrastructure solutions.

Negin Alemazkoorمشاهده پروفایل

استادیار

• Infrastructure Systems
• Artificial Intelligence
• Renewable Energy
• +۷ مورد دیگر

Negin Alemazkoor is an Assistant Professor at the University of Virginia's School of Engineering and Applied Science, specializing in interdisciplinary research on infrastructure resilience. Her work focuses on developing AI-driven methodologies for analyzing interconnected systems like power grids, urban flood models, and transportation networks under uncertainty. Key areas include enhancing grid reliability through multi-fidelity modeling, hurricane evacuation equity analysis, and precision-compression techniques for large-scale data. She co-leads a NSF-funded initiative to democratize AI education in high schools. Her research integrates graph neural networks, physics-informed models, and machine learning to address challenges in energy systems, environmental monitoring, and disaster response. Notable projects include hurricane-induced power outage risk analysis under climate change and precision guarantees for smart-meter data analytics. She emphasizes computational efficiency and multi-fidelity approaches to balance accuracy with resource constraints. Recent contributions span AI applications in flood forecasting, renewable energy integration, and infrastructure cybersecurity. Her NSF grant aims to create inclusive AI curricula, reflecting her commitment to education and societal impact. She is affiliated with UVA Engineering’s research initiatives on resilient systems and data-driven decision-making.

Sijia Gengمشاهده پروفایل

استادیار

• Power Systems
• Control Theory
• Nonlinear Dynamical Systems
• +۴ مورد دیگر

Sijia Geng is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University (JHU) and a core researcher at the Ralph O’Connor Sustainable Energy Institute (ROSEI). She directs the Power and Energy Network Systems Analysis (PENSA) Laboratory and co-leads the NSF-funded Electric Power Innovation for a Carbon-free Society (EPICS) Center as co-PI. Her research focuses on integrating control theory, mathematical analysis, and optimization to enhance renewable energy utilization and grid resiliency. Education: Ph.D. and M.S. (ECE & Mathematics) from the University of Michigan-Ann Arbor (2016–2022), B.S. in Automation from Harbin Institute of Technology (2016). Postdoctoral work at MIT (2022) and visiting scholar roles at Purdue University (2015) and Pacific Northwest National Lab (2018). Research Interests: Dynamic analysis of inverter-based power systems, nonlinear control theory, data-driven decision-making, and multi-energy systems. Her work emphasizes achieving autonomous, resilient energy systems through advanced computational tools and theoretical frameworks. Awards: Best Paper Award at MIT/Harvard Applied Energy Symposium (2022), MIT Rising Stars in EECS (2021), Barbour Scholarship (2021), Towner Prize (2018), and Gerald and Esther Forrest Fellowship (2016). She is active in IEEE and INFORMS, organizing sessions at PES General Meeting and CISS conferences. Grants & Collaborations: Funded by NSF, DOE, MIT Energy Initiative, and industry. Leads global initiatives through EPICS, collaborating with UK, Australian, and international stakeholders. Co-leads ROSEI’s Grid pillar to advance fossil-free energy systems. Labs & Teams: Directs PENSA Lab, affiliated with JHU’s Data Science and AI Institute, Applied Mathematics & Statistics, and Computer Science departments.

Hatem Abou-Zeidمشاهده پروفایل

استادیار

• AI for 6G
• Wireless Sensing
• Extended Reality Networking
• +۵ مورد دیگر

Dr. Hatem Abou-Zeid is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary, directing the WAVES Research Group. He holds adjunct positions at Queen’s University, Carleton University, and Ontario Tech University. His research focuses on AI-driven 6G networks, wireless sensing, extended reality (XR), and brain-computer interfaces (BCI). Prior to academia, he spent 7 years in industry at Ericsson and Cisco, leading projects in 5G radio access and network intelligence, resulting in 20+ patents and $3.5M+ collaborative research projects. Education: PhD in Electrical and Computer Engineering (Queen’s University), M.Sc. and B.Sc. in Electronics and Communications Engineering (Arab Academy, Egypt). Research interests span trustworthy AI for 6G, joint sensing & communication systems, and AI for immersive networking. Notable work includes foundational models for 6G radios, self-supervised learning for spectrograms, and safe reinforcement learning for network slicing. His lab explores pediatric BCI, IoT edge computing, and low-power wireless prototyping. Publications highlight contributions to AI-driven resource allocation, 5G/6G slicing, and federated learning in tactical networks. Awards include the 2023 Early Research Excellence Award and 2023 Software Engineering Professor of the Year. Advising involves 15+ students and postdocs, with collaborations spanning academia (e.g., Hotchkiss Brain Institute) and industry (Ericsson, Telus). Current openings exist for PDF/PhD researchers in AI/6G wireless systems and pediatric BCI. Labs/Teams: Director of WAVES Lab; collaborates with Ericsson Canada, Alberta Innovates, and Canadian Space Agency on applied research projects. Teaching includes advanced networking, machine learning systems, and IoT courses.

Jinhan Kimمشاهده پروفایل

پژوهشگر

• Software Engineering
• Mutation Testing
• Fault Localization
• +۴ مورد دیگر

Jinhan Kim is a Postdoctoral Researcher at the Università della Svizzera italiana (USI) in the Faculty of Informatics, working in the TAU lab under Prof. Paolo Tonella. He earned his Ph.D. from KAIST under Prof. Shin Yoo, focusing on software engineering research in mutation testing, fault localization, and deep learning system testing. His work bridges traditional software engineering techniques with AI-driven methodologies, emphasizing AI4SE and SE4AI paradigms. Education: Ph.D. in Software Engineering, KAIST, 2023 Research Interests: Mutation Testing Deep Learning System Testing Autonomous Systems Testing Adversarial Attack Detection Empirical Software Engineering Service and Leadership: Organized SBFT 2026 and DeepTest 2026 (co-located with ICSE 2026) Program Committee Member for ASE, ISSTA, Mutation, and DeMeSSAI Board of Distinguished Reviewers for TOSEM (2024–2025) Labs and Teams: Active contributor to the TAU Lab at USI, focusing on advanced software testing and AI integration.

• Primatology
• Animal Behavior
• Evolutionary Anthropology
• +۳ مورد دیگر

Ian Gilby is an Associate Professor at the School of Human Evolution and Social Change, Arizona State University. His research focuses on the social behavior, ecology, and cognition of wild chimpanzees, particularly within the context of long-term studies at Gombe National Park, Tanzania. Gilby investigates topics such as cooperative hunting, dominance hierarchies, social bonding, and the influence of ecological factors on primate behavior. His work bridges primatology, evolutionary biology, and conservation science, with a strong emphasis on understanding the adaptive strategies of chimpanzees in complex social environments. Key themes in Gilby’s research include the evolution of cooperation, reproductive strategies, and the ecological drivers of social behavior. He has contributed significantly to studies on chimpanzee aggression, hunting tactics, and the role of vocal communication in group coordination. His findings highlight the intricate relationship between social structure, ecological conditions, and individual success in primate communities. Notably, Gilby is involved in the Gombe Chimpanzee Project, analyzing long-term datasets to address questions about data sharing in conservation science and the impacts of environmental changes on wildlife. While no formal awards or grants are explicitly mentioned in the provided texts, his extensive publication record underscores his expertise in primate behavior and ecology.

• Fatigue Assessment
• Structural Engineering
• Welded Metal Structures
• +۷ مورد دیگر

Scott Walbridge is the Chair of the Department of Civil and Environmental Engineering at the University of Waterloo, where he has been actively teaching and researching since 2006. He holds a Doctorate in Civil Engineering from the Swiss Federal Institute of Technology (EPFL), a Master's from the University of Alberta, and a Bachelor's in Civil Engineering from the same institution. His research focuses on enhancing structural safety and durability through fatigue assessment, retrofitting of welded metal structures, modular construction, and life-cycle cost analysis. He chairs the CSA aluminum structures technical subcommittee for bridge design codes (S6) and actively contributes to code development for structural welding and aluminum design. Walbridge has been Program Director for Waterloo’s Architectural Engineering program (2018–2022) and serves on editorial boards for journals like Structural Engineering International and ASCE Journal of Bridge Engineering . Education: PhD, Civil Engineering (Steel Structures), EPFL, Switzerland (2005) MSc, Structural Engineering, University of Alberta (1998) BSc, Civil Engineering, University of Alberta (1996) Research Interests: Fatigue assessment, welded metal structures, modular construction, structural reliability, fracture mechanics, and life-cycle cost analysis. His work bridges theoretical frameworks with practical applications, such as improving fatigue life prediction for aluminum bridge decks and optimizing material selection for corrosion resistance. Professional Engagement: Chair of CSA S6 Aluminum Structures Subcommittee, active member of welding code committees (W59, W59.2), and contributor to national bridge design standards. His leadership in code development ensures alignment with modern material technologies and sustainability goals. Teaching & Advising: Recently taught courses like CIVE 512 (Rehabilitation of Structures) and CIVE 704 (Bridge Design). He is currently accepting graduate students in structural engineering and bridge design.

Gudrun P. Kiesmüllerمشاهده پروفایل

استاد

• Supply Chain Management
• Inventory Management
• Spare Parts Inventory Management
• +۳ مورد دیگر

Prof. Dr. Gudrun P. Kiesmüller is a full professor of Operations Management at TUM Campus Heilbronn since 2019. Previously, she held full professorships at Kiel University (Supply Chain Management) and Otto von Guericke University Magdeburg (Operations Management). She studied mathematics at Julius-Maximilians-University of Würzburg and later worked as a postdoc and assistant professor at Eindhoven University of Technology. Her research focuses on supply chain management, inventory management (particularly spare parts), maintenance process planning, and manufacturing system design. She develops optimization approaches for decision support, with publications in journals like IISE Transactions and Production and Operations Management . Key awards include an Honorary Doctorate (2023), ISIR Service Award (2022), and multiple teaching and reviewer awards. She has contributed to advancing stochastic inventory models and operational efficiency in complex systems. Her work integrates theoretical rigor with practical applications, addressing challenges in inventory routing, buffer allocation, and component reliability optimization. Current research emphasizes dynamic maintenance planning and capital goods design.

Tijani CHAHEDمشاهده پروفایل

استاد

• Network Optimization
• Edge Computing
• Machine Learning in Networks
• +۴ مورد دیگر

Prof. Tijani CHAHED is a Professor at Telecom SudParis, part of Université Paris-Saclay, affiliated with the SAMOVAR laboratory and the NeSS research group. His work focuses on network optimization, edge computing, machine learning applications in telecommunications, and game-theoretical frameworks for distributed systems. He holds a position in the Department of Computer Science and Telecommunications. His research spans resource allocation in 5G/6G networks, energy efficiency strategies for mobile infrastructure, reinforcement learning for dynamic systems, and coalitional game theory for multi-agent systems. Key contributions include optimization of cache allocation in edge computing, latency-critical traffic management (URLLC), and strategic investment models for distributed computing infrastructures. Selected articles highlight advances in edge computing resource management, metaverse data transport over 5G, and energy-efficient sleep mode control for base stations. His work often intersects with industrial applications in green networks and smart grid integration for mobile infrastructure. Collaborations involve institutions like École Polytechnique, INRIA, and industry partners in telecommunications. Current projects include 6G network architectures, metaverse-enabled edge services, and decentralized resource allocation frameworks. Labs/Teams: SAMOVAR Lab (Signal and Media Access Networks, Optical and Radio Networks), NeSS Group (Networked Systems and Services).

Chen Liuمشاهده پروفایل

استادیار

• Machine Learning
• Adversarial Robustness
• Privacy-Preserving Machine Learning
• +۹ مورد دیگر

Chen Liu is an Assistant Professor in the Department of Computer Science at City University of Hong Kong and the Principal Investigator (PI) of the Machine Learning and Optimization (MLO) group. His research focuses on building reliable machine learning models, particularly studying robustness and privacy properties of deep neural networks from an optimization perspective. University: City University of Hong Kong Academic Rank: Assistant Professor Students: Supervises multiple PhD, MPhil, and postdoctoral researchers. Education: Holds a Ph.D. (2022) and MSc (2017) in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), and a BSc (2015) in Computer Science from Tsinghua University. Research Interests: Adversarial robustness, privacy-preserving machine learning, optimization algorithms, dataset distillation, generative models, and theoretical analysis of loss landscapes. His work addresses challenges like catastrophic overfitting, architecture overfitting in distilled data, and stable adversarial training methods. Article Trends: Recent publications explore adversarial robustness under l0/l1 norms, gradient inversion for data reconstruction, evolutionary factor searching in finance, and meta-tuning for out-of-domain few-shot learning. These works emphasize optimization techniques to enhance model reliability and generalization. Scientific Awards: Microsoft Research Ph.D. Scholarship Programme (2017–2019) Advising and Grants: Supervises a diverse team of current and former students, with collaborations across institutions like George Mason University and Zhejiang University. Research supported by academic and industry grants. Labs and Teams: Leads the MLO group, which investigates fundamental ML theory and algorithms to improve system reliability. The group's work spans adversarial training, dataset distillation, and generative model optimization.