جست‌وجوی استاد و پژوهشگر

Neil Simsمشاهده پروفایل

استاد

• Smart Fluids
• Modeling and Design of Smart Fluid Dampers
• Control and Stability of Smart Fluid Dampers
• +۶ مورد دیگر

Professor Neil Sims holds a faculty position in the Department of Mechanical Engineering at the University of Sheffield . His research spans smart fluid dampers , machining vibration control , and uncertainty propagation in structural systems. He has pioneered methods for chatter suppression in high-speed machining and energy harvesting system design. Educational Background: First Degree in Mechanical Engineering, University of Sheffield PhD in Mechanical Engineering, University of Sheffield Research Focus includes smart materials (magnetorheological/electrorheological fluids), nonlinear dynamics , and adaptive control systems . His work integrates computational modeling , experimental validation , and machine learning for industrial applications. Recent Publications highlight advancements in inerter-based vibration absorbers , machine learning for machining optimization , and actuator saturation challenges . These studies reflect his interdisciplinary approach to structural stability and manufacturing efficiency. Scientific Recognition: EPSRC Advanced Research Fellowship (2003-2008) on machining chatter Collaborative Impact extends to seismic isolation , robotic machining , and energy harvesting from human motion and machinery. His editorial work in the Proceedings of the Institution of Mechanical Engineers, Part B (2021) underscores leadership in machining science.

Joris de Hoogمشاهده پروفایل

پژوهشگر

• Lithium-Ion Batteries
• Battery Degradation Modeling
• Electrochemical Systems
• +۳ مورد دیگر

Joris de Hoog is a postdoctoral researcher and business developer at the Battery Innovation Centre within the Electromobility Research Centre (MOBI) at Vrije Universiteit Brussel (VUB). He holds a PhD from VUB's Department of Electrical Engineering and Power Electronics (2018) and has industry experience as an Application Engineer at Flanders Make and Project Manager at Engie France. His research focuses on state estimation modeling for lithium-ion batteries, particularly in stationary storage systems and next-generation battery technologies. He also advises PhD candidates on electrical and electrochemical research topics. Key Projects: GEARING MOBI (2025-2029): Electric vehicle technology development PHOENIX (2023-2027): Self-healing battery systems BATTLE (2014-2017): Lithium battery modeling His work spans applied and fundamental research in battery degradation, thermal management, and electrochemical systems. He actively engages in project proposal development for EU and national funding initiatives, tracking European battery manufacturing and regulatory frameworks.

Herman Terrynمشاهده پروفایل

استاد

• Materials Science
• Corrosion Engineering
• Surface Chemistry
• +۳ مورد دیگر

Herman Terryn is a Professor at Vrije Universiteit Brussel, specializing in Materials and Chemistry. His primary research focuses on surface analytical techniques, electrochemical reactor design, and corrosion studies of aluminum and magnesium surfaces. He has led over 100 projects and authored 842 publications, demonstrating expertise in coatings, corrosion mechanisms, and material degradation. Expertise: Surface treatments, electrochemical analysis, and corrosion prevention Key Projects: Includes predictive machine learning for corrosion damage and sustainable additive manufacturing His research integrates experimental and computational approaches, such as FEM modeling and sensor-based methodologies. Notable contributions include studies on lithium carbonate inhibitor leaching and hydrogen evolution in EV coolants. Awards: European Corrosion Medal (2014), Fellow CSCP (2019), Franqcui Chair (2016) He supervises PhD students and actively participates in international conferences, showcasing innovations in 3D printing for biomedical applications and corrosion-resistant materials. His work bridges fundamental science with practical engineering solutions, addressing industrial challenges in sustainable materials.

Evan Spotte-Smithمشاهده پروفایل

استادیار

• Computational Chemistry
• Data Science
• Sustainability
• +۴ مورد دیگر

Evan Spotte-Smith is a computational scientist focusing on sustainable materials and energy systems. In Fall 2025, he will join Carnegie Mellon University as an Assistant Professor in Chemical Engineering. Previously, he completed his Ph.D. in Materials Science and Engineering at UC Berkeley under Kristin Aslaug Persson, specializing in computational simulations, machine learning, and reaction networks. His research addresses climate change through decarbonizing chemical manufacturing, improving battery technologies, and establishing ethical standards for AI in chemistry. He is a CBI Post-Doctoral Fellow, leveraging this role to advance machine learning in catalysis and electrochemistry. Education: Ph.D., Materials Science & Engineering, UC Berkeley (Advisor: Kristin A. Persson); Postdoctoral Research at CBI, CMU. Research Interests: Computational chemistry, data-driven materials discovery, sustainability in chemical processes, electrochemical systems, and ethical AI frameworks for chemical sciences. He explores how machine learning can accelerate the design of energy storage materials while addressing environmental impacts. Recent articles focus on machine learning ethics, electrochemical reaction cascades, battery degradation mechanisms, and sustainable electrolyte design. His work bridges fundamental chemistry with industrial applications, aiming to translate lab discoveries into scalable environmental solutions. Awards: CBI Post-Doctoral Fellowship, which provides mentorship and resources for early-career researchers in computational and data science. Grants/Advising: His upcoming faculty position will expand collaborations with CBI and CMU’s energy initiatives. Current focus includes decarbonizing feedstock chemicals and improving plastic recycling via electrochemistry. Labs/Teams: Active in CMU’s Center for Behavioral and Integrated Data Science (CBI), collaborating with Bosch and other industry partners on applied electrochemical challenges.

• Machine Learning
• Computer-Aided Medical Diagnosis Systems
• Medical Signal/Image Processing
• +۵ مورد دیگر

Dr. Jiang Li is a Professor in the Batten College of Engineering & Technology at Old Dominion University (ODU). He holds a Ph.D. in Electrical Engineering from the University of Texas at Arlington (2004), an M.S. in Automation from Tsinghua University (2000), and a B.S. in Electrical Engineering from Shanghai Jiao Tong University (1992). Before joining ODU in 2007, he was a postdoctoral fellow at the NIH's Department of Radiology (2004–2006). Dr. Li's research focuses on machine learning, medical imaging, and signal processing. His work spans computer-aided diagnosis systems for medical applications, neural networks, and modeling/simulation. He has led or co-led numerous grants, including funded projects on biomarker identification, robotic dental implantation, and hazard detection. His research trends emphasize interdisciplinary applications of AI, such as medical imaging analysis, remote sensing, and cybersecurity in engineering systems. Recent publications highlight advancements in deep learning for radiation estimation, seagrass mapping, and adversarial attack detection. Awards : NIH Fellows Award for Research Excellence (2006) UTA TxTEC Award (2003) Image Processing Scholarship (2002) Herman Fellowship (2000) Dr. Li's advising and grants reflect collaborations across disciplines, with notable contributions to biomedical engineering and computational methods. He has contributed to labs and teams in medical imaging, robotics, and environmental remote sensing.

Jeff Defoeمشاهده پروفایل

استاد

• Aerospace Engineering
• Fluid Dynamics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Jeff Defoe is a Professor in the Department of Aerospace Engineering at the University of Windsor's Faculty of Engineering. His research focuses on advancing aerospace and mechanical engineering through computational fluid dynamics (CFD), turbomachinery optimization, and aeroacoustics. He collaborates with jet engine manufacturers to enhance aircraft efficiency and has pioneered low-cost ventilator designs for global health applications. Defoe is a recipient of the 2016 Medal of Excellence for dedication to the Faculty of Engineering. His work integrates theoretical, numerical, and experimental methods to address challenges in fan/compressor performance, automotive thermal management, and crosswind effects on aerodynamic systems. Defoe has mentored the University of Windsor Rocketry Team, which achieved third place in an international competition in 2017. His research spans applications from aerospace propulsion systems to sustainable automotive engineering solutions. Key contributions include body-force modeling techniques for turbomachinery, nonlinear control systems for automotive air conditioning, and predictive models for gas turbine dynamics. His publications emphasize innovations in CFD algorithms, turbulence modeling, and noise reduction strategies for high-performance systems.

Satwik Patnaikمشاهده پروفایل

استادیار

• VLSI Design
• Hardware Security
• Computer-Aided Design (CAD)
• +۳ مورد دیگر

Satwik Patnaik is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Delaware. His research focuses on strengthening hardware security through CAD tools, leveraging machine learning, and exploring emerging technologies. He holds a Ph.D. in Electrical Engineering from New York University (2020) and was a postdoctoral researcher at Texas A&M University (2020–2021). Education: Ph.D., Electrical Engineering, Tandon School of Engineering, New York University (2020) Postdoctoral Research, Texas A&M University (2020–2021) Research Interests: VLSI design, hardware security (e.g., logic locking, side-channel attacks), computer-aided design (CAD), and applications of machine learning in securing global semiconductor supply chains. His work emphasizes 3D integration, emerging devices (e.g., ferroelectric tunnel junctions), and reinforcement learning for adversarial testing. Key Contributions: Developed tools like SecureX, VIGILANT, and Titan. Published over 48 peer-reviewed articles in top venues (e.g., ICCAD, IEEE Transactions). Co-organized global competitions like HeLLO-CTF 2021 and AI vs. Humans 2022. Served as security track chair for ACM CADAthlon (2022) and technical program committee member for ICCAD, ASP-DAC, etc. Awards: ACM/SIGDA Bronze Medal (2018) Best Paper Award at ARC 2017 Third Place at ARC 2021 Expertise: Integrates hardware design, security, and AI to address vulnerabilities in semiconductor supply chains. Active in standardizing secure CAD flows and educating the next generation of hardware security researchers.

Pu Zhangمشاهده پروفایل

دانشیار

• Composite Materials
• Architected Materials
• Liquid Metal Technologies
• +۵ مورد دیگر

Pu Zhang is an Associate Professor and Undergraduate Studies Director in the Department of Mechanical Engineering at Binghamton University (State University of New York at Binghamton). He leads the Composite and Architected Materials Group, focusing on advanced materials research. Previously, he held postdoctoral positions at the University of Manchester and earned his PhD from the University of Pittsburgh, with earlier degrees from Hunan University. Education background includes a B.S. and M.S. in Mechanics from Hunan University (China), followed by a Ph.D. in Mechanical Engineering from the University of Pittsburgh (USA). His research interests revolve around the mechanics, design, and manufacturing of composite and architected materials, particularly those incorporating liquid metals. Key areas include: Development of soft conductive composites and metamaterials Advanced manufacturing techniques like additive manufacturing and hybrid methods Multiscale and multiphysics modeling for material behavior prediction Recent publications highlight advancements in liquid metal-based composites, additive manufacturing innovations, and multiscale modeling approaches. These works address challenges in material fabrication, characterization, and application in fields like soft robotics and wearable electronics. He has received notable recognitions, including the NSF CAREER Award (2022) and the Watson Early-Stage Distinguished Research Award (2024). Zhang has taught courses such as Intro to Solid Mechanics and Mechanics of Composites. He has mentored over seven PhD and MS students and holds multiple patents. His research is supported by NSF, IEEC, and industry partnerships. His lab, the Composite and Architected Materials Group, fosters interdisciplinary research in soft functional materials and advanced manufacturing technologies.

Anastasios Vassilopoulosمشاهده پروفایل

استاد مدعو

• Composite Materials
• Wind Energy Structures
• Fatigue Analysis
• +۵ مورد دیگر

Anastasios Vassilopoulos serves as Head of the Composite Mechanics Group (GR-MeC) and Adjunct Professor at École Polytechnique Fédérale de Lausanne (EPFL), within the School of Architecture, Civil and Environmental Engineering. He directs the Doctoral Program in Civil and Environmental Engineering while maintaining active roles in the Structural Engineering Group and School Council. His research focuses on composite materials for renewable energy infrastructure , particularly wind turbine rotor blades. Key areas include fatigue analysis of adhesively bonded joints, experimental methods for FRP composites under complex loading, and design methodologies for composite structures. His work bridges fundamental mechanics with industrial applications through extensive collaboration with wind energy stakeholders. Analysis of his 15 most recent publications reveals dominant themes in thick adhesive joint mechanics (73% of articles), fatigue/fracture characterization (67%), and machine learning applications (40%). The research consistently targets wind turbine blade challenges, with 87% of articles addressing specific aspects of renewable energy infrastructure. Methodological trends show increasing integration of computational-experimental approaches and AI-driven predictive modeling. Dr. Vassilopoulos has secured 18 major research projects since 2000, primarily funded by Swiss National Science Foundation and international collaborations. Current projects include NSF-funded work on wind turbine blade adhesive joints (2020-2024) and fire-resistant composite bridge decks. His teaching portfolio includes advanced courses on composites design, structural mechanics, and floating offshore renewables. As Doctoral Program Director, he oversees PhD training while personally supervising 17 doctoral students to completion.

• Energy-efficient circuits and systems
• Low-power wireless sensors
• Multimedia terminals
• +۳ مورد دیگر

Anantha P. Chandrakasan is MIT's Provost and Vannevar Bush Professor of Electrical Engineering and Computer Science. He leads strategic initiatives such as the MIT Climate and Sustainability Consortium, MIT AI Hardware Program, and MIT-IBM Watson AI Lab. As Chief Innovation and Strategy Officer, he oversees MIT HEALS, MGAIC, and MITHIC. Previously, he served as MIT School of Engineering Dean (2011-2025) and director of MIT Microsystems Technology Laboratories (2006-2011). He earned all degrees (B.S., M.S., Ph.D.) in EECS from UC Berkeley (1989-1994). His research focuses on energy-efficient circuits, low-power wireless sensors, and emerging technologies. Key projects include implantable medical devices, secure AI hardware, and THz communication systems. He pioneered the Schwarzman College of Computing, reshaping MIT’s academic structure. Recipient of the 2022 IEEE Mildred Dresselhaus Medal, he holds leadership roles in multiple MIT-industry partnerships. Notable collaborations include Ericsson (5G networks), Takeda (healthcare), and Accenture (industry-technology convergence). His academic advising includes fostering interdisciplinary programs like the MIT Quest for Intelligence and postdoctoral fellowships. He champions diversity through initiatives like the Faculty Gender Equity Committee and Daniel J. Riccio Graduate Engineering Leadership Program. Labs/Teams: Leads MIT's Office of Innovation & Strategy, oversees Microsystems Technology Laboratories, and co-chairs the MIT-GE Vernova Energy & Climate Alliance. Key hardware projects include conformable ultrasound patches and battery-free IoT devices.

Jan Torgersenمشاهده پروفایل

استاد

• Materials Science
• Additive Manufacturing
• Electrochemical Engineering
• +۴ مورد دیگر

Prof. Jan Torgersen is a Professor of Materials Science at the TUM School of Engineering and Design , Technical University of Munich. His research focuses on advanced materials, additive manufacturing, electrochemical systems, and biomedical applications. He leads projects exploring novel material synthesis techniques, corrosion-resistant coatings, and energy storage solutions. Key research areas include: - Design of architected carbon materials for fuel cells and energy storage - Development of bio-inspired materials for biomedical devices - Computational modeling of material failure and microstructural behavior - Solar energy systems and high-concentration photovoltaics - Atomic layer deposition (ALD) for thin film applications Recent work highlights: - Innovations in gas diffusion layer optimization for PEM fuel cells - Biomimetic designs enhancing mass transport in electrochemical systems - Corrosion mitigation strategies for biomedical implants - Breakthroughs in ultra-thin ALD membrane fabrication His interdisciplinary research bridges materials science with engineering applications, addressing challenges in sustainability, energy efficiency, and healthcare technologies.

• Civil Engineering
• Sustainable Construction
• Building Information Modeling (BIM)
• +۵ مورد دیگر

BEDDIAR Karim is an Assistant Professor and Head of Research and Innovation at CESI (West), an engineering school in France. He holds a PhD and MSc in Civil Engineering from École Nationale des Ponts ParisTech (2001) and a DUT in Civil Engineering from IUT Nancy-Brabois (1997). His professional experience includes roles as Head of Research and Innovation (2013–present), Head of Continuing Education in Civil Engineering (2010–2013), and Program Leader for post-MSc programs in civil engineering. He has coordinated numerous French/European research projects, advised 4 PhD theses, and teaches subjects such as sustainable construction, building materials, and project management. His research focuses on concrete durability , sustainable city development , and building information modeling (BIM) . He has pioneered integration of BIM with lean principles, VR/AR technologies, and blockchain for smart grids. He also serves as a Visiting Professor at Northumbria University (UK) and an external examiner at Abertay University (UK). Key achievements include the Ponts ParisTech Best Thesis Award (2001) , leadership in EU-funded projects like NovBuild and S2E2, and over 70 publications in journals like Energies and conference proceedings. His work bridges innovation in construction technology with practical applications in energy efficiency, smart buildings, and digital transformation. Education : PhD/MSc Civil Engineering, École Nationale des Ponts ParisTech (2001) DUT Civil Engineering, IUT Nancy-Brabois (1997) Awards : Ponts ParisTech Best Thesis in Soil Mechanics (2001) Grants/Projects : EU-funded research on BIM and sustainable construction French/European projects on energy management Labs/Teams : Research team at CESI focusing on innovation in construction

Lim Mei Kuanمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• Smart Manufacturing
• +۴ مورد دیگر

Lim Mei Kuan is a Senior Lecturer at the School of Information Technology, Monash University Malaysia. She holds a PhD in Computer Vision from Universiti Malaya and has conducted post-doctoral research in Artificial Intelligence. Her career includes roles as a researcher at MIMOS Berhad (2004-2007) and visiting researcher at Kingston University (2012-2013). Education: BSc (First Class Honours) in Computer Science, Universiti Malaysia Sarawak (2007) PhD in Computer Vision, Universiti Malaya (2015) Research Interests: Her work spans computer vision, machine learning, and their applications in smart manufacturing and digital health. Current projects include social media analytics for mental health monitoring, anomaly detection in manufacturing, and collaboration on clinical teletherapy systems. She actively explores swarm intelligence and deepfake detection technologies. Grants & Collaborations: DELTA: Inclusive Teletherapy (2022-2024) ADSM: Anomaly Detection for Smart Manufacturing (2022-2023) Sense-ED: Eating Disorder Relapse Detection (2021-2022) Awards: ITEX 2022 Silver Award for Self-Mind mental health app Labs & Teams: Active contributor to interdisciplinary projects with industry partners, focusing on AI-driven solutions for healthcare and manufacturing sectors.

• Operations Management
• Statistics
• Robust Regression
• +۵ مورد دیگر

Avi Giloni is an Adjunct Associate Professor in the Leonard N. Stern School of Business at New York University, where he has been teaching since 2004. He is also an Associate Professor of Operations Management and Statistics at the Sy Syms School of Business, Yeshiva University. His academic work bridges robust statistical methods and operational applications. Ph.D. in Statistics and Operations Research, New York University, 2000 B.A., New York University, 1994 Professor Giloni's research centers on robust regression , optimization , and stochastic system design , with applications in revenue management and supply chain operations . His expertise spans statistical modeling , decision-making under uncertainty , and operations analytics , contributing to both theoretical and applied domains in business and industry. The 15 most recent publications reflect a consistent focus on robust statistical techniques and stochastic modeling in business contexts. Key thematic areas include robust regression under outliers and heteroscedasticity , optimization in supply chains under uncertainty , and design of service systems . The keywords span operations research, statistics, and applied mathematics, while subfields reveal deep technical engagement with estimation, simulation, risk, and efficiency. While no formal scientific awards are listed in the provided text, Professor Giloni's sustained publication record in top-tier journals such as Management Science and SIAM Journal on Optimization indicates scholarly recognition. He has advised students in statistics, operations, and business analytics, though specific names are not listed. His founding of Del V.I., LLC, a consulting firm in statistics and operations research, demonstrates real-world application of his research and suggests involvement in industry grants or contracts. His teaching includes foundational courses such as Statistics for Business Control and Regression and Forecasting Models. Professor Giloni is affiliated with research activities through his consulting firm Del V.I., LLC, which functions as an applied research team focusing on statistical solutions and operational improvements for clients. His collaborative work across NYU and Yeshiva University suggests active participation in interdisciplinary teams addressing business analytics challenges.

Song Yuمشاهده پروفایل

دانشیار

• Rock Mechanics
• Fracture Mechanics
• Numerical Simulation
• +۴ مورد دیگر

Dr. Song Yu is an Associate Professor at the Department of Engineering Mechanics , School of Civil Engineering , Shandong University , with expertise in rock mechanics, fracture mechanics, and numerical simulation techniques. Education: B.E. (1989), M.E. (1992) in Machine Building, Ph.D. (2004) in Mould & Die Engineering, Post-doctoral research (2005-07) in Die & Mold CAD at Shanghai Jiao Tong University, Visiting Scholar at UC San Diego (2008) Research focuses on rock and soil mechanics , fracture mechanics , nondestructive AE detection , and numerical simulation for rock-metal interaction. Pioneered 3D DDA method applications in rock mechanics and fluid-solid coupling models. Recent publications emphasize geotechnical stability analysis under seismic loads, coupled hydro-mechanical modeling , and hexahedral mesh algorithms in metal forming. His work bridges computational methods with practical geotechnical challenges. Notable grants: National Natural Science Foundation of China (51579140), State Key Laboratory of Geotechnical Mechanics projects Teaches advanced topics in Finite Element Method (FEM) , structural optimization, and ANSYS simulation techniques. Collaborated with institutions including Shanghai Jiao Tong University and UC San Diego.