جست‌وجوی استاد و پژوهشگر

David J. Fleetمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Image Processing
• +۷ مورد دیگر

David J. Fleet is a Professor in the Department of Computer Science and the Department of Computer and Mathematical Sciences at the University of Toronto. He serves as a CIFAR AI Chair and Faculty Member at the Vector Institute, with additional affiliations at the UofT Robotics Institute. PhD in Computer Science (1990), University of Toronto Research focuses on computer vision, deep learning, visual neuroscience, and computational biology Key contributions in motion analysis, stereopsis, 3D reconstruction, and diffusion models Research Interests: His work explores mathematical foundations for visual motion analysis, human pose estimation, and 3D structure determination in electron cryo-microscopy. Recent projects involve deep learning and diffusion models for video and image synthesis. Scientific Recognition: Recipient of the Koenderink Prize, CIFAR AI Chair, and multiple best paper awards at NeurIPS, CVPR, and BMVC. Former Chair of UTSC's Computer and Mathematical Sciences Department (2012–2017). Students and Collaborations: Mentored numerous PhD and MSc students, including Ali Punjani (co-founder of Structura Biotech) and Sara Sabour (Google Brain). Collaborates with institutions like Google DeepMind (2020–present) and PARC (1999–2003).

Arman Oshnoeiمشاهده پروفایل

استادیار

• Power Engineering
• Renewable Energy Integration
• Battery Management Systems
• +۳ مورد دیگر

Arman Oshnoei is an Assistant Professor at Aalborg University, affiliated with the Faculty of Engineering and Science's Department of Power Electronics System Integration and Materials. His research focuses on renewable energy integration, battery management systems, and AI-driven solutions for smart grids. He leads and participates in high-impact projects like CROSBAT (2023-2026) and BMS-DC (2024), addressing challenges in battery safety, energy efficiency, and data center optimization. Education: Advanced degree in Power Engineering (details not specified). His research interests span power electronics, cybersecurity in energy systems, and predictive control models. Recent work includes optimizing green hydrogen production using AI and enhancing battery lifespan through advanced state-of-charge estimation. He has authored over 78 publications, including a 2025 best paper award for battery balancing techniques. Key Projects: - CROSBAT: AI-based battery lifetime optimization (2023-2026) - BMS-DC: Next-gen battery management for data centers (2024) - REPEPS: Reliable power electronic systems (2021-2023) Dr. Oshnoei also serves as a reviewer for IEEE Transactions on Sustainable Energy and holds grants totaling over €2M in research funding.

Hanseup Kimمشاهده پروفایل

استاد

• MEMS Actuators and Sensors
• Polymer-Based Bioapplications
• Micro Energy Harvesting
• +۶ مورد دیگر

Hanseup Kim is a Professor in the Department of Electrical and Computer Engineering at the University of Utah, with adjunct roles in Biomedical and Mechanical Engineering. He holds the H. Kent Bowen Endowed Professorship and serves as Department Chair. His research focuses on MEMS, biomedical microsystems, energy harvesting, and smart wearable devices. Education: B.S. from Seoul National University (1997), M.S. and Ph.D. from University of Michigan (2002, 2006). Postdoctoral training at the University of Michigan's WIMS Center (2006–2009). Joined University of Utah as USTAR Assistant Professor in 2009, advancing to Professor in 2022. Research interests include MEMS actuators/sensors, polymer-based bioapplications, micro energy harvesters, and integrated circuits. Key projects involve smart contact lenses, adaptive optics for vision correction, and low-power sensor networks. Notable awards: 2012 NSF CAREER Award, 2011 DARPA Young Faculty Award, and multiple best paper awards. Active in grants from NSF, DARPA, and industry, focusing on energy systems, environmental monitoring, and biomedical applications. Labs: Hanseup Kim Research Lab (specializing in Microsystems in Moving Fluids). Teaches courses on microsensors, microactuators, and electric circuits. Supervises interdisciplinary teams in cleanroom fabrication and biological testing facilities.

Mahmoud Shafieeمشاهده پروفایل

استاد

• Energy Systems Resilience
• Sustainable Energy
• Structural Health Monitoring
• +۱۳ مورد دیگر

Professor Mahmoud Shafiee is a globally recognized academic and researcher at the University of Surrey , holding the Chair in Resilient Energy at the School of Mechanical Engineering Sciences. He directs the Energy Resilience Centre and leads the REF 2029 Engineering Unit of Assessment . His career spans leadership roles at Cranfield University, University of Kent, and University of Sheffield, alongside research fellowships in Sweden and Canada. He is a Fellow of the Institute for Sustainability and serves on committees for Institution of Mechanical Engineers (IMechE) , European Safety & Reliability Association (ESRA) , and Engineering Integrity Society (EIS) . Education : PhD, Chartered Engineer (CEng), Postgraduate Certificate in Higher Education (PGCHE), Senior Fellow of the Higher Education Academy (SFHEA) Professional Memberships : Fellow of IMechE, Member of IET, BINDT, Energy Institute, and advisory roles at RenewableUK, WindEurope, and GWEC His research focuses on Energy Systems Resilience , Structural Health Monitoring , Digital Twins , Machine Learning , and Circular Economy applications in renewable energy. Recent work integrates Industry 4.0/5.0 technologies into offshore wind and hydrogen systems. His 15 most recent articles emphasize machine learning for energy consumption prediction, digital twins for structural monitoring, and circular economy strategies in wind turbine recycling. Scientific Awards : Best Paper Award 2025 (Energies), Fellow of Institute for Sustainability (IfS) Grants & Collaborations : Principal Investigator for UK-Brazil Smart Wind Monitoring Project; Co-Investigator in €5.3M Horizon Europe Digital Twins for Wind Power; lead in £20M UK Clean Maritime Programme and £1.3M Hydrogen Transportation Project Supervision : Supervised 22 PhD, 80 MSc/MRes, and 200 BEng/MEng students. Highlights include advising on offshore wind life performance, structural monitoring, and PEM Fuel Cell modeling. Editorial Roles : Associated Editor and Editorial Board member for journals in Resilience Engineering, Renewable Energy, and Prognostics & Health Management (PHM). Conferences : Plenary speaker at international events on topics like hydrogen refueling resilience and remanufacturing strategies for renewable assets.

Ravi Karkarمشاهده پروفایل

استادیار

• Health Informatics
• Human-Computer Interaction
• Medical Technology
• +۴ مورد دیگر

Ravi Karkar is an Assistant Professor at the University of Massachusetts Amherst in the Manning College of Information and Computer Sciences (CICS). He co-directs the Health Tech for the People (HT4P) initiative and contributes to the stakeholder engagement core of MassAITC. His research focuses on designing human-centered tools to empower individuals in managing their health through data-driven insights. Karkar holds a PhD in Computer Science & Engineering from the University of Washington, alongside multiple fellowships and awards, including the STRIDE and PIT Faculty Fellowships (2024). Education: PhD, Computer Science & Engineering, University of Washington (2020) MS, Computer Science & Engineering, University of Washington (2016) MS, Computer Science, Georgia Institute of Technology (2012) BE, Computer Engineering, Gujarat University (2011) Research Interests: Karkar’s work emphasizes tools for chronic disease management (e.g., IBS, cirrhosis, depression), self-tracking technologies, and ethical design of health applications. He explores collaborative care models, personalized interventions, and the intersection of HCI with clinical practices. Recent projects include tools for Alzheimer’s disease support, ethics in healthcare technology, and novel diagnostics like the Beacon device for hepatic encephalopathy. Publications: His research spans health informatics, wearable devices, and chronic condition management, with notable contributions in CHI , DIS , and IEEE-BSN . Key themes include self-experimentation frameworks, patient self-monitoring, and interdisciplinary healthcare innovation. Awards & Recognition: Best Paper Award (Top 1%, CHI 2025) Three-Sixty Fellowship for CSE mHealth Training Institute Fellow (2023) Advising & Grants: Karkar mentors PhD students (e.g., Abhay Sheel Anand, Itir Sayar) and has secured grants through initiatives like STRIDE and PIT. His work bridges academic research with clinical practice, emphasizing real-world impact. Labs & Teams: Co-leads HT4P, fostering equitable health tech design, and collaborates with MassAITC to engage stakeholders in healthcare innovation.

Nian-Ze Leeمشاهده پروفایل

استادیار

• Formal Methods
• Hardware Verification
• Software Verification
• +۳ مورد دیگر

Nian-Ze Lee is an Assistant Professor at the Department of Electrical Engineering of National Taiwan University, leading the Formal Methods and Analysis for Computing and Engineering Laboratory (ForMACE Lab). He is also a Guest Professor affiliated with the Software and Computational Systems Lab (SoSy-Lab) at Ludwig-Maximilians-Universität München (LMU Munich), Germany. He holds a Ph.D. in Electronics Engineering from National Taiwan University (2021). His research focuses on formal methods, hardware and software verification, and circuit-based analysis. Education: Ph.D. in Electronics Engineering, National Taiwan University (2021) Research Interests: Formal methods for hardware and software systems Model checking and verification frameworks Circuit-based program verification (e.g., Btor2C translator) Algorithm selection for verification tools Awards: ACM SIGSOFT Distinguished Paper Award (2025) Best Artifact Award (2024) DFG Grant for Bridging Hardware and Software Analysis (2024) Advising & Grants: Supervises Ph.D./Master’s students on topics like algorithm selection and verification frameworks Recipient of DFG grant enabling collaboration between NTU and LMU Munich Labs/Teams: ForMACE Lab (NTU) – Focuses on formal methods and system analysis SoSy-Lab (LMU) – Collaborations on verification tools and frameworks

Elona Shatriمشاهده پروفایل

مدرس

• Optical Music Recognition
• Deep Learning
• Artificial Intelligence
• +۳ مورد دیگر

Elona Shatri is a PhD candidate at the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM) and a visiting lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. She specializes in Optical Music Recognition (OMR) using Deep Learning and is a leading advocate for ethical AI practices. Her research focuses on advancing OMR techniques, including GAN-based music synthesis and dataset development (e.g., DoReMi), while addressing challenges in low-data scenarios and historical manuscripts. She teaches postgraduate courses on Machine Learning and Visual Data Analysis, blending technical rigor with creative applications. Research Interests : OMR with deep learning, ethics in AI, generative AI models, music informatics, and interdisciplinary collaborations between AI and the arts. Awards : Recipient of the Best Student Paper Award at the 2024 Knowledge Discovery in OMR conference for her work on instance segmentation. Projects : Co-lead on the UK-Qatar AI Collaboration (2024–) and the CREAATIF project examining AI in creative industries. Founded the QMUL AI and Ethics Research Group, fostering interdisciplinary dialogues on fairness, transparency, and societal impacts of AI. Labs/Teams : Centre for Digital Music (C4DM), part of Queen Mary's School of Electronic Engineering and Computer Science.

Thomas Clarkمشاهده پروفایل

استاد

• Photonics
• Microwave Photonics
• Integrated Photonic Circuits
• +۴ مورد دیگر

Thomas Clark is a Professor in the Department of Electrical and Computer Engineering (ECE) at Michigan State University (MSU), part of the College of Engineering. He specializes in low-noise and ultrafast lasers, photonic systems, and millimeter-wave photonics, with applications in communications, sensing, and signal processing. Dr. Clark holds a Ph.D. from the University of Maryland (1998), an M.S. from Lehigh University (1993), and a B.S. from Loyola College of Maryland (1991). His research focuses on microwave photonics, photonic integrated circuits, and emerging technologies like quantum computing and AI-driven autonomy. He has authored over 100 publications and holds 11 patents. Key professional roles include Program Area Manager for Advanced Concepts at Johns Hopkins University Applied Physics Laboratory (2012–2024), leadership in IEEE Photonics Society, and organizing major conferences like the IEEE Photonics Conference (2016). Clark’s work emphasizes agile, reconfigurable systems and has been recognized with awards such as the 2017 Outstanding Mission Accomplishment Award and multiple Outstanding Development Paper Awards. His contributions span government, industry, and academia, including roles at the Naval Research Laboratory and a telecommunications startup. Research trends in his articles highlight advancements in integrated optical beamforming, millimeter-wave systems, and photonic analog-to-digital converters. His publications frequently address challenges in signal processing, noise reduction, and high-speed data transmission. Professional memberships include Optica and IEEE senior membership, with active participation in technical committees for microwave photonics and fiber optics. Clark’s advising and grants focus on fostering innovation in photonics and microwave systems. He has led teams in developing cutting-edge technologies for defense, telecommunications, and emerging fields like quantum computing. His lab work emphasizes cross-disciplinary collaboration to address real-world technical challenges.

Wen Liمشاهده پروفایل

استاد

• MEMS/NEMS technologies
• Micro sensors and actuators
• Biomimetic devices
• +۶ مورد دیگر

Dr. Wen Li is a Professor in the Department of Electrical and Computer Engineering at Michigan State University's College of Engineering. She leads the MicroTechn Laboratory and is affiliated with the Institute for Quantitative Health Science & Engineering. Her research focuses on micro/nano systems for biomedical applications. Ph.D., California Institute of Technology (2009) M.S., California Institute of Technology (2004) M.E., Tsinghua University (2003) B.E., Tsinghua University (2001) Her work spans MEMS/NEMS technologies , biomimetic devices , and neural interfaces , with applications in intraocular pressure monitoring and implantable neuroprosthetics . Current projects include diamond-based microelectrodes and graphene nanosensors for biomedical applications. Recent publications highlight advancements in transparent neural arrays, wireless ocular sensors, and optogenetic interfaces. Her lab employs cutting-edge fabrication techniques for biomedical microsystems. Innovator of the Year Award (2024) NSF CAREER Award (2011) Best Paper Awards at IEEE EMBC, BioCAS, and 3M-NANO Dr. Li's team has secured funding from NIH, NSF, Wellcome Trust, and the State of Michigan. The lab trains 4 PhD students, 3 undergraduates, and collaborates across disciplines.

Hans M. Wyssمشاهده پروفایل

دانشیار

• Microfluidics
• Soft Matter
• Colloidal Suspensions
• +۴ مورد دیگر

Hans M. Wyss is an Associate Professor in Microfluidics and Soft Matter at TU/e's Department of Mechanical Engineering. He leads a research group studying meso-scale materials such as colloids, emulsions, and hydrogels using microfluidics-based tools. His work explores mechanical properties, microgel dynamics, and phoretic forces, including groundbreaking insights into the 'exclusion-zone' effect. Wyss holds a PhD from ETH Zurich and a postdoc at Harvard. He collaborates with ICMS and international groups, and partners with FrieslandCampina and Wetsus. Current projects include indoor air quality monitoring (2023–2027). Courses taught include Experimental Soft Matter and Engineering Design. His research impacts UN SDGs related to health and innovation. Education: PhD (Materials Science, ETH Zurich), Experimental Physics (ETH Zurich) Research Themes: Hydrogel mechanics, soft material rheology, microfluidic tools Key collaborations include Zhejiang University and industry partners. Notable achievements include over 3,950 citations and 90+ publications. His lab focuses on translating fundamental insights into biomedical applications like glaucoma implants.

Andrew Boutrosمشاهده پروفایل

استادیار

• Reconfigurable Computing
• Field-Programmable Gate Array (FPGA) Architecture
• Computer-Aided Design (CAD) Tools
• +۴ مورد دیگر

Andrew Boutros is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on reconfigurable computing architectures, FPGA design, and domain-specific acceleration for deep learning and datacenter workloads. He holds a PhD from the University of Toronto (2024) and has worked at Intel Labs and MangoBoost. Education: PhD, Electrical and Computer Engineering, University of Toronto, Canada (2024) MASc, Electrical and Computer Engineering, University of Toronto, Canada (2018) BSc, Electronics Engineering, German University in Cairo, Egypt (2016) Research Interests: Developing efficient FPGA architectures and CAD tools for reconfigurable hardware, domain-specific acceleration, and application/hardware co-design. Specific areas include 3D-stacked acceleration devices, graph neural network acceleration, and FPGA-based smart NICs for AI training. Publications: Over 30 papers in top venues like IEEE FPL, FCCM, and FPGA conferences, with 4 best paper awards. Recent work includes 3D-stacked architectures, graph neural network inference, and FPGA optimization for deep learning. Awards: Best Paper Award (FPT 2023) Best Paper Award (ICM 2021) Stamatis Vassiliadis Best Paper Award (FPL 2018) Advising/Grants: Currently accepting graduate students. Collaborations include 84 co-authors and industry partnerships with Intel and MangoBoost.

John W. Jacksonمشاهده پروفایل

دانشیار

• causal inference
• confounding
• decomposition
• +۱۵ مورد دیگر

John W. Jackson, ScD is an Associate Professor in the Department of Epidemiology at Johns Hopkins Bloomberg School of Public Health. His primary academic appointment is in Epidemiology with joint affiliations in Biostatistics. Dr. Jackson develops innovative methods for translational health equity research, focusing on measurement, epidemiology, and policy/intervention effects on health inequities. Dr. Jackson's research centers on developing methods to identify, refine, and evaluate interventions to eliminate health and healthcare disparities, as well as improving transparency and conduct of observational studies and post-hoc analyses of clinical trials. His work spans causal inference, confounding, decomposition methods, intersectionality, mediation analysis, and health disparities research across multiple domains including mental health, pharmacoepidemiology, and observational studies. Analysis of Dr. Jackson's recent publications (2024-2025) reveals a strong focus on health equity methodologies, with particular attention to intersectional approaches that examine how multiple marginalized identities compound health disparities. His work frequently applies causal decomposition frameworks to identify intervention targets for reducing disparities across various health conditions including hypertension, mental health, and cancer screening. 2018 Discovery Award Grant, Johns Hopkins University 2018 Exemplary peer reviewer for Epidemiology 2017 Honorable mention, Thomas Ten Have Award, Atlantic Causal Inference Conference 2016 Kenneth Rothman Prize for best paper published in Epidemiology 2016 Top peer reviewer for Pharmacoepidemiology and Drug Safety 2014 Alonzo Smythe Yerby Fellowship, Harvard T.H. Chan School of Public Health 2013 Best overall poster, Society for Epidemiologic Research Annual Meeting Dr. Jackson maintains active collaborations across Johns Hopkins University and with external institutions, particularly in projects examining the intersection of race, gender identity, disability, and other social determinants of health. His methodological innovations have significant implications for health policy and clinical practice, particularly in identifying actionable intervention points to address persistent health disparities.

Huang Yonggangمشاهده پروفایل

استاد

• Stretchable Electronics
• 3D Mesostructures
• Bioresorbable Devices
• +۲ مورد دیگر

Yonggang Huang is the Jan and Marcia Achenbach Professor at Northwestern University with joint appointments in Mechanical Engineering, Civil Engineering, and Materials Science. His research pioneers stretchable electronics, deterministic 3D assembly, and bioresorbable medical devices. Innovations include epidermal electronics for health monitoring, injectable microsystems for neural interfacing, and environmentally degradable sensors. Collaborative work with John Rogers has produced landmark Science papers on silicon-based flexible circuits. Honors include membership in all three US National Academies and top awards in mechanics (von Karman, Drucker medals). Teaching integrates mechanics theory with advanced manufacturing. Recent projects focus on wireless implants for real-time physiological monitoring and biodegradable medical devices.

Mohamed Atiaمشاهده پروفایل

پژوهشگر

• Modular Robotics
• Soft Robotics
• Path Planning Algorithms
• +۳ مورد دیگر

Mohamed Atia is a Researcher in the Department of Electrical and Electronic Engineering at the University of Nottingham. His academic role focuses on robotic systems, with a PhD awarded in 2023 for his work on reconfigurable soft robots. His research aligns with UN Sustainable Development Goals related to innovation and education. Education: Doctor of Philosophy (2017–2022): Reconfigurable Soft Robots by Building Blocks , University of Nottingham Research Interests: Atia specializes in modular robotics, soft robotics, and path planning algorithms. His work integrates advanced materials with control systems, particularly in exoskeleton development. Recent studies explore machine learning applications in material science and 3D-printed composites. Research Trends: His publications emphasize reconfigurable robot design (2022–2024), path optimization for mobile systems (2020–2018), and exoskeleton control systems (2019–2017). The 2024 paper on machine learning for composites marks an interdisciplinary expansion. Impact & Collaborations: Participated in the CRADLE center, focusing on robotic autonomy in demanding environments. His work has been cited over 30+ times and reached 40+ readers on Mendeley. Labs/Teams: Part of the CRADLE research group, collaborating with experts in robotics, materials science, and biomedical engineering.

Marc Estibeiroمشاهده پروفایل

دانشیار

• Computer Music
• Electroacoustic Composition
• Music Technology
• +۳ مورد دیگر

Dr. Marc Estibeiro is an Associate Professor of Music at Staffordshire University, where he serves as Course Leader for the MA Music Production program. His academic work focuses on composing for acoustic instruments and electronics. He holds a PhD in Composition from Durham University (2016), alongside MAs in Music (Bangor), English Language Teaching (Essex), and a BA(Hons) in Music (Middlesex). Research interests include electroacoustic composition, live electronics, and interdisciplinary music technology. His work has been presented globally, including at the Royal College of Music (Stockholm), ICMC conferences (Shanghai, Daegu, and Shenzhen), and Visiones Sonoras (Mexico). He co-organized the NoiseFloor event at Staffordshire University, attracting international practitioners. Grants : 2019 Arts Council-funded audiovisual project exploring Stoke-on-Trent's pottery industry legacy. Teaching : Pro Tools, creative music software design, and postgraduate supervision. Professional Memberships : Performing Rights Society, AVID Certified Pro Tools Instructor. Publications include chapters in Rethinking the Musical Instrument (2022) and Innovation in Music (2019), alongside conference papers on granular synthesis and digital instrument design. His music has been broadcast on BBC and Channel 5, and he collaborates internationally with ensembles like the Ives Ensemble and Acceder8 brass band.