جست‌وجوی استاد و پژوهشگر

John Maمشاهده پروفایل

استاد

• Structural Engineering
• Bridge Engineering
• Prestressed Concrete
• +۷ مورد دیگر

John Ma is a Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, where he has been a faculty member since August 2005. His research focuses on structural engineering, particularly in bridge systems, prestressed concrete, and accelerated construction methods. Research Interests: Dr. Ma's work centers on improving the durability and performance of concrete structures. Key areas include bond behavior between rebar and concrete, alkali-silica reaction (ASR) evaluation, 3D printing of concrete, and the behavior of prestressed concrete bridges. His research supports innovation in accelerated bridge construction (ABC), aiming to enhance safety, longevity, and efficiency in infrastructure. Recent Research Trends: Analysis of his recent publications reveals a consistent focus on advanced concrete technologies, structural health monitoring, and composite materials like FRP. His work combines experimental testing with computational modeling to study shear behavior, joint performance, and long-term degradation mechanisms in concrete structures. Scientific Awards: Moses E. and Mayme Brooks Distinguished Professor Award, 2019 UT TCE Research Achievement Award, 2018 ASCE Tennessee Section’s Daniel B. Barge, Jr Award, 2018 UT TCE Outstanding Advisor Award, 2016 ASCE’s Raymond C. Reese Research Prize, 2013 UT CEE Scholar Recognition, 2012 Fellow of ASCE, 2011 ASCE Tennessee Section’s Peter G. Hoadley Award, 2009 NSF CAREER Award, 2004 ASCE’s T.Y. Lin Award, 2002 PCI’s Martin P. Korn Award, 2001 Advising and Grants: Dr. Ma has actively advised numerous graduate students, many of whom are co-authors on his publications, indicating strong mentorship in research. He has received competitive funding, including the NSF CAREER Award, supporting his work in structural innovation and education. His role as Associate Editor for the ASCE Journal of Bridge Engineering and ASCE Journal of Structural Engineering highlights his leadership in the academic community. Labs and Teams: While specific lab names are not mentioned, Dr. Ma leads a research group focused on structural testing and modeling, involving full-scale experiments, finite element analysis, and material characterization, often in collaboration with industry and transportation agencies.

Ralf Hagemannمشاهده پروفایل

مدرس

• Embedded Systems
• Software Engineering
• Programming Education
• +۵ مورد دیگر

Ralf Hagemann is a Lecturer/Research Associate at Osnabrück University of Applied Sciences, specifically within the Faculty of Engineering and Computer Science . His academic work combines Embedded Systems , Software Engineering , and innovative teaching methods like Problem-Based Learning . He actively develops educational hardware and tools for engineering education. Embedded Systems Board design (STMNucleo32-Baseboard) Problem-oriented curriculum development for computer science students Qt-based visualization frameworks for algorithm training His research spans geometric algorithms (2013 dissertation), digital signal processing (1991 thesis), and domain-specific programming languages (1997 PIPL invention). Recent publications focus on multicultural engineering education and cost-effective product development . As a part-time faculty member , he leads technical workshops and contributes to European Project Semester initiatives. His 1991 Diplomarbeit at Fachhochschule Bielefeld laid foundations for his work in hardware-software integration . He regularly demonstrates his MpC-Bildschirmstellwerk software at international model railway exhibitions (2008-2016) and has published in journals like MIBA digital Extra and Eisenbahn Kurier .

• Sensor Systems and Electronic Nose Technology
• Food Quality Assessment and Authentication
• Artificial Neural Networks Applications
• +۳ مورد دیگر

Todor Nedev Todorov is a Senior Assistant at the Faculty of Electrical Engineering and Electronics at Technical University - Gabrovo, Bulgaria, holding a Doctor (scientific and educational) degree in Technical Sciences. He works in the Department of Automation, Information and Control Technology, with office location in cabinet 3411. Dr. Todorov's research focuses on sensor systems and electronic nose technology for food quality assessment and authentication. His work integrates artificial neural networks with gas sensor arrays to develop innovative solutions for monitoring food products during processing and aging. He has made significant contributions to applications in cheese classification, sunflower oil quality assessment, and bean origin identification. Analysis of Dr. Todorov's publication record from 2012-2023 reveals a consistent research trajectory centered on electronic nose systems and their applications in food science. His work shows progression from basic sensor development to sophisticated neural network implementations for food quality assessment. The research demonstrates strong interdisciplinary connections between electrical engineering, food science, and artificial intelligence. Dr. Todorov has been actively involved in numerous research projects, primarily focusing on sensor systems for environmental monitoring and food quality control. His project portfolio includes both internal university research initiatives and international collaborations aimed at incorporating technology into educational curricula. His laboratory work appears centered around sensor development and integration, particularly gas sensor arrays for food quality monitoring applications. The research infrastructure likely includes electronic nose systems, neural network training environments, and food product testing facilities.

Dina G. Mahmoudمشاهده پروفایل

استادیار

• Heterogeneous Computing
• Hardware Security
• Fault Injection Attacks
• +۳ مورد دیگر

Dina G. Mahmoud is an Assistant Professor at the Department of Computer Science and Engineering at The American University in Cairo (AUC). She earned her Ph.D. in Computer and Communication Sciences from EPFL, Lausanne, Switzerland (2019-2024), where she was a CYD Fellow and collaborated with Dr. Mirjana Stojilović and Dr. Vincent Lenders. Her academic activities include teaching Digital Design, Computer Organization, and Applied Data Structures at AUC. Ph.D. (2019-2024): School of Computer and Communication Sciences, EPFL B.Sc. (2014-2019): Electronics and Communications Engineering with minor in Mathematics, AUC Her research focuses on heterogeneous computing systems , emphasizing security and reliability at the hardware and electrical levels . She investigates fault injection attacks in FPGA systems, particularly in multitenant cloud environments, and has demonstrated the first FPGA-to-CPU fault-injection exploit. Recent publications highlight trends in FPGA security , including power-wasting attacks, hardware Trojans, undervolting exploits, and fault tolerance mechanisms. Her work bridges hardware-software co-design , cloud security , and reconfigurable computing . CYD Fellow (first doctoral recipient) Google Generation Scholarship (2022, EMEA) IC Doctoral Fellowship at EPFL She has served as Head/Teaching Assistant at EPFL for courses like Computer Architecture and Information, Calcul, Communication, and as Head Undergraduate Teaching Assistant at AUC for Digital Logic Design. She contributes to the technical program committee of IEEE Industrial Electronics Society’s ETFA conference.

• Cybersecurity
• Artificial Intelligence
• Blockchain Technology
• +۴ مورد دیگر

Dr. Shun-Wen Hsiao is an Associate Professor in the Department of Management Information Systems at National Chengchi University (NCCU), Taiwan. He earned his PhD in Information Management from National Taiwan University and has been with NCCU since 2017, first as an Assistant Professor before his promotion to Associate Professor in 2023. His research spans: Cybersecurity : Malware analysis, threat detection, IoT security, and blockchain applications Artificial Intelligence : Neural networks for security, NLP, and recommendation systems FinTech : Blockchain frameworks, secure voting systems, and P2P lending risk models E-commerce : Livestreaming recommendation algorithms and consumer behavior analysis He has received multiple awards including: National Science Council Research Award (2023) Three consecutive Outstanding Team awards for Information Security R&D (2016-2018) Research grants from Taiwan's Ministry of Science and Technology Dr. Hsiao leads several major research projects funded by Taiwan's National Science and Technology Council, focusing on explainable AI for cybersecurity, financial technology security, and big data analytics platforms. His work frequently appears in top IEEE transactions and cybersecurity conferences.

Stefano Querمشاهده پروفایل

دانشیار

• Computer Science
• Electrical Engineering
• Formal Methods
• +۷ مورد دیگر

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues

Ján Drgonaمشاهده پروفایل

دانشیار

• Differentiable programming
• Scientific machine learning
• Dynamical systems
• +۳ مورد دیگر

Ján Drgona is an Associate Professor in the Department of Civil and Systems Engineering at Johns Hopkins University's Whiting School of Engineering and a member of the Ralph S. O'Connor Sustainable Energy Institute (ROSEI). Previously, he served as a Principal Investigator and Research Data Scientist at Pacific Northwest National Laboratory (PNNL) and held a postdoctoral position at KU Leuven in Belgium. Dr. Drgona earned his BSc, MSc, and PhD in control engineering from the Slovak University of Technology. His research centers on differentiable programming and scientific machine learning (SciML) for dynamical systems, optimization, and control, with particular applications to building energy systems and industrial process control. He is the lead developer of the Neuromancer SciML library in PyTorch for solving constrained optimization, physics-informed machine learning, and optimal control problems, which became PNNL's most popular open-source repository within two years of its release. Dr. Drgona's publication record demonstrates a strong focus on bridging machine learning with physical systems and control theory. His recent work spans differentiable predictive control, physics-informed neural networks, optimization algorithms, and applications to energy systems. A recurring theme across his publications is the integration of domain knowledge with data-driven approaches to create more efficient, reliable, and interpretable systems for real-world applications, particularly in sustainable energy and building systems. As an active member of the scientific community, Dr. Drgona regularly serves as a reviewer for prestigious journals including Applied Energy, Automatica, IEEE Control Systems Letters, IEEE Transactions on Control Systems Technology, IEEE Transactions on Industrial Informatics, Control Engineering Practice, Journal of Process Control, Energy and Buildings, Journal of Control Automation and Electrical Systems, and Electric Power Systems Research. Dr. Drgona has been involved in several high-impact projects, including developing AI models that slash HVAC energy costs while predicting them with precision. He has participated in Johns Hopkins' International Energy Summit to accelerate clean technology innovation and has presented at major conferences including ACC 2025 where he co-organized workshops on Physics-Informed Machine Learning in Control and Safe Physics-Informed Machine Learning for Dynamics and Control.

• Biomedical Engineering
• Laser Spectroscopy
• Diffuse Reflectance Spectroscopy
• +۷ مورد دیگر

Wesam Bachir, PhD, is an Assistant Professor at the Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology (Politechnika Warszawska). His expertise lies at the intersection of biomedical engineering, laser spectroscopy, and optical diagnostics for medical applications. Research Interests Dr Bachir’s core research areas include: Biomedical optics & spectroscopy: developing diffuse reflectance and transmittance methods for non-invasive monitoring of tissue oxygenation, hemodynamics, and vital signs. Laser-tissue interaction & photodynamic therapy: optimizing light dosimetry, photosensitizer selection, and treatment planning for breast and skin cancers. Optical phantoms & Monte Carlo modeling: creating tissue-mimicking phantoms from everyday materials (milk, intralipid, India ink) and validating optical properties through advanced simulations. Smartphone-based sensing: leveraging mobile devices and their built-in light sources for point-of-care photoplethysmography and respiratory monitoring. Publication Trends Across 36 peer-reviewed publications (h-index 6 Scopus, 5 WoS), Dr Bachir demonstrates a consistent upward trajectory in both clinical translation and fundamental optical modeling. His 2024–2025 papers emphasize AI-enhanced spectroscopy and ultra-short-term physiological monitoring, while earlier work (2019–2022) concentrated on Monte Carlo algorithms for PDT planning and phantom characterization. The portfolio spans experimental validation, computational modeling, and proof-of-concept clinical studies. Supervision & Grants He has successfully supervised four doctoral theses to completion and currently leads or co-leads three active research projects funded by national and international agencies, focusing on non-contact respiratory monitoring, AI-driven spectral diagnostics, and optimized fiber-coupled light delivery for photodynamic therapy. Laboratory & Collaboration Dr Bachir’s laboratory is embedded within the Institute of Metrology and Biomedical Engineering, providing access to state-of-the-art laser sources, integrating sphere systems, and high-resolution spectrometers. He collaborates extensively with clinicians at local medical centers and maintains active partnerships with research groups in Europe and the Middle East to accelerate technology transfer from bench to bedside.

Sophia Tsokaمشاهده پروفایل

دانشیار

• Computational genome analysis
• Genome data mining
• Network analysis and reconstruction
• +۷ مورد دیگر

Sophia Tsoka is a Reader in Bioinformatics at King's College London specializing in computational genome analysis, network reconstruction, and machine learning applications in cancer immunology and microbiome research. She leads the 'Algorithms for Antibodies' project funded by the Royal Society and serves as Co-Investigator on multiple research projects including 'Understanding the significance of patient B cells and expressed antibodies in melanoma' supported by the British Skin Foundation. Dr. Tsoka's research focuses on computational genome analysis, genome data mining, network analysis and reconstruction, metabolic networks, protein interaction networks, and the evolution of genome properties and dynamics. Her work bridges bioinformatics, machine learning, and immunology, with particular emphasis on applying computational approaches to understand antibody mechanisms, tumor microenvironments, and microbiome dynamics. She has developed innovative algorithms for network analysis, classification, and multi-omics data integration that have advanced our understanding of complex biological systems. Her recent publications demonstrate a strong trajectory in applying computational methods to cancer immunology, with multiple high-impact papers in 2025 spanning IgE antibody therapeutics, tumor microenvironment analysis, and machine learning approaches for biomedical data. These works reveal a consistent focus on developing interpretable computational models that can translate complex biological data into clinically relevant insights. Best paper award (2022) Best Paper Award (2020) Dr. Tsoka supervises numerous research projects and has secured significant grant funding from prestigious organizations including the Royal Society and British Skin Foundation. Her collaborative work spans multiple disciplines, connecting computational scientists with immunologists and clinicians to advance cancer therapeutics. She has established herself as a key contributor to the field of computational immunology with over 4,800 citations to her work. Her laboratory focuses on developing and applying advanced computational methods for analyzing complex biological networks, with particular emphasis on cancer immunology applications. The team combines expertise in algorithm development, machine learning, and biological data analysis to address challenging problems in antibody engineering and tumor microenvironment characterization.

• Software Development
• Internet of Things (IoT)
• Blockchain
• +۷ مورد دیگر

Joanna F. Defranco is an Associate Professor of Engineering at the Engineering Division (Great Valley) of Pennsylvania State University. Her research focuses on software development, internet of things (IoT), blockchain, and artificial intelligence, with a particular emphasis on quality assurance, security, and practical implementations in engineering and healthcare. Research Interests Defranco's work addresses critical challenges in IoT security, digital twins for manufacturing, and AI-driven software quality analysis. She explores secure data sharing frameworks, blockchain applications in healthcare, and the evolution of low-code/no-code platforms. Her recent publications highlight interdisciplinary approaches to telemedicine, smart agriculture, and urban infrastructure. Publication Trends Her 2023-2025 publications show increasing focus on IoT integration with AI, secure healthcare data systems, and the societal implications of emerging technologies. Key themes include digital twin adoption in SMEs, generative AI's impact on software development, and cybersecurity resilience. Collaborations She collaborates with institutions like IEEE and researchers such as Paul Laplante, Joseph Voas, and Thrasyvoulos Speicher. Her work bridges engineering education with real-world applications in manufacturing, agriculture, and healthcare.

Habiba Farrukhمشاهده پروفایل

استادیار

• Security & Privacy
• Mobile Computing
• Internet of Things Security
• +۳ مورد دیگر

Habiba Farrukh is an Assistant Professor in the Department of Computer Science at the University of California, Irvine , where she directs the Security and Privacy of Emerging Computing Technology (SPECT) Lab . Her research focuses on security & privacy and mobile computing , using system design, machine learning, and human-centered approaches to address threats in emerging computing platforms. Ph.D. in Computer Science from Purdue University (advisor: Dr. Z. Berkay Celik) Research Trends : Her recent work spans XR security (UI attacks, eye gaze privacy), mobile/IoT security (magnetometer side-channels, secure group pairing), online abuse (toxic content against refugees), and wearable privacy . Publications appear at top venues like USENIX Security , IEEE S&P , and ACM CCS . Scientific Awards : Best Poster Runner-Up Award at MobiSys 2025 Outstanding Reviewer Award at VehicleSec 2024 Bilsland Dissertation Fellowship 2021-2022 Teaching : CS190: Introduction to Security & Privacy (Spring 2025) CS204: Usable Security and Privacy (Fall 204) CS295: Security and Privacy of Emerging Computing Platforms (Spring 2024)

• Automotive Engineering
• Motion Planning and Control
• Connected and Automated Vehicles
• +۶ مورد دیگر

Abdel Ra'ouf Mayyas is an Associate Professor at The Polytechnic School of Arizona State University (ASU), specializing in Automotive Engineering. He is affiliated with the Human Systems Engineering (HSE) PhD program as a graduate faculty member and served as the lead faculty advisor for the ASU-Advanced Vehicle Technology Competitions (EcoCAR 3) from 2014-2018. Education: Ph.D. in Automotive Engineering (2010), Clemson University M.S. in Computer Engineering (Embedded Systems) (2006), Yarmouk University B.S. in Mechanical Engineering (Automotive) (1996), Mu’ta University His research focuses on autonomous driving, advanced driver assistance systems (ADAS), model predictive control (MPC) for energy management in urban autonomous fleets, V2V/V2I applications for smart cities, human-centric vehicle safety systems, and thermal modeling of connected powertrains. He has contributed to vehicle hardware-in-the-loop (VHiL) testing and energy optimization of automated vehicles. Mayyas has led funded projects by the U.S. Army Automotive Research Center, Toyota Motor Corp, and Salt River Project (SRP) for battery performance evaluation in hot climates. His work appears in journals like Energy Research , Applied Energy , and Journal of Power Sources . Labs: Autonomous Collaborative Research Laboratory Connected Powertrains Laboratory Vehicle Hardware In-the-Loop (VHiL) Laboratory Advanced Vehicle Technology Competitions (AVTCs) Laboratory

• Quality Improvement
• Patient Safety
• Medical Education
• +۳ مورد دیگر

Carly Kuehn, MD, MME serves as Clinical Associate Professor of Internal Medicine-Hospital Medicine at the University of Iowa Carver College of Medicine, holding the leadership role of Educational Director for Safety and Quality within the Department of Internal Medicine. Education: MD, University of Wisconsin School of Medicine and Public Health Residency in Internal Medicine, University of Iowa Hospitals & Clinics Chief Resident, Internal Medicine, University of Iowa Hospitals & Clinics MME, University of Iowa Carver College of Medicine Dr. Kuehn's research focuses on integrating quality improvement methodologies into medical education , particularly through resident engagement in safety initiatives. Her work emphasizes practical application of QI frameworks in ambulatory settings to enhance both educational outcomes and clinical care delivery. As Educational Director for Safety and Quality, she develops curricula that bridge theoretical knowledge with real-world healthcare improvement. Scholarly output demonstrates consistent focus on residency training innovation , with publications examining structured approaches to involve trainees in quality improvement projects. Her 2018 research established foundational methods for embedding QI education within ambulatory rotations, reflecting expertise in medical education design and systems-based practice. Through her leadership position, Dr. Kuehn mentors faculty and residents in quality improvement methodologies while advancing the Department of Internal Medicine's safety initiatives. Her operational role directly impacts educational programming and quality metrics across hospital medicine services.

Juan Jesús García Domínguezمشاهده پروفایل

استاد

• Electronics Engineering
• Sensor Technology
• Biomedical Engineering
• +۳ مورد دیگر

Juan Jesús García Domínguez is a Professor in the Department of Electronics at the Universidad de Alcalá. His primary research focuses on sensor systems, wearable technology, and their applications in healthcare and smart environments. He leads the GEINTRA research group, dedicated to Electronic Engineering Applied to Intelligent Spaces and Transport. Dr. García Domínguez holds a PhD from Universidad de Alcalá (2006) with a thesis on infrared obstacle detection in railway environments. His research interests include biomedical sensors, inertial measurement units (IMUs), indoor localization systems (BLE/UWB), and elderly care technology. He has pioneered work on non-invasive behavioral monitoring, gait analysis, and wearable devices for vulnerable populations. Recent projects involve developing systems for activity recognition, fall detection, and telemedicine applications. Key contributions include the FrailWear wearable IoT device, BLE-based behavioral analytics frameworks, and multi-sensory systems for long-term patient monitoring. His work bridges electronic engineering with healthcare, emphasizing practical solutions for aging-in-place and smart transportation safety. Teaching includes digital electronics and active learning methodologies in engineering education. Dr. García Domínguez has published extensively on topics like acoustic positioning systems, IMU calibration algorithms, and NILM techniques for energy management. His lab focuses on translating sensor data into actionable insights for medical and environmental applications.

Gregory T. Byrnesمشاهده پروفایل

استاد

• Biomechanics
• Locomotor Ecology
• Comparative Biomechanics
• +۳ مورد دیگر

Gregory T. Byrnes is a Professor in the Department of Biology at Siena University, where he has been a faculty member since 2012. He teaches upper-level courses including Comparative Biomechanics (integrating biology, physics, and engineering), Writing and Research Skills for Biologists, and General Biology, while actively involving undergraduates in hands-on research. His academic credentials include a Ph.D. in Integrative Biology from the University of California, Berkeley (2009), where he investigated gliding biomechanics in mammals, followed by postdoctoral research at the University of Cincinnati on arboreal snake locomotion. Ph.D., Integrative Biology, University of California, Berkeley, 2009 Postdoctoral Fellow, University of Cincinnati, 2009-2011 Teaching Fellow (NSF GK-12), UC Berkeley, 2008-2009 Dr. Byrnes' research centers on understanding animal locomotion through the physical interaction between organisms and their environments . He integrates laboratory-based physiology and field-based ecology to examine how morphology, physiology, and behavior contribute to performance in ecologically relevant behaviors. His work bridges functional morphology, evolutionary biology, and engineering to address questions at the interface of locomotor physiology and behavioral ecology, with emphasis on whole-organism performance in unpredictable natural settings. Analysis of his 15 most recent publications reveals a dominant focus on comparative biomechanics of arboreal and gliding locomotion across diverse taxa (squirrels, geckos, snakes, colugos). Key themes include tail-assisted aerial maneuvers, substrate interaction mechanics, locomotor trade-offs (safety vs. economy), and ecological implications of movement performance. This body of work demonstrates consistent application of interdisciplinary methods to solve problems ranging from fundamental biomechanics to conservation applications. His scientific recognition includes: Visiting Scientist position at the Max Planck Institute for Intelligent Systems (2018) Dr. Byrnes maintains a strong commitment to undergraduate research mentorship, embedding students directly in his biomechanics investigations. His teaching philosophy emphasizes merging research into classroom instruction to demonstrate scientific processes firsthand, leveraging Siena's small class sizes and laboratory-intensive curriculum. While specific grant details aren't provided, his sustained research output and international collaborations (including Max Planck Institute) indicate successful external funding acquisition. His laboratory work spans both controlled experimental settings and field studies, with recent projects exploring bio-inspired robotics applications (e.g., tail reflexes in soft robotics). Current research directions focus on optimizing habitat connectivity for gliding mammals and translating biomechanical insights into engineering solutions.