جست‌وجوی استاد و پژوهشگر

Harry Millwaterمشاهده پروفایل

استاد

• Fracture Mechanics
• Probabilistic Structural Analysis
• Sensitivity Analysis
• +۴ مورد دیگر

Harry Millwater is the Samuel G. Dawson Endowed Professor and Associate Chair for Research in the Mechanical Engineering Department at the University of Texas at San Antonio's Margie and Bill Klesse College of Engineering and Integrated Design. With over three decades of academic and research experience, he has established himself as a leading expert in structural mechanics and computational methods. Dr. Millwater's primary research focuses on fracture mechanics, probabilistic structural analysis, sensitivity analysis, and computational mechanics. His work bridges theoretical developments with practical applications in structural reliability, fatigue analysis, and digital twin technologies. He has pioneered methods using hypercomplex variables for sensitivity analysis, which have significantly advanced the field of computational mechanics and structural engineering. His extensive publication record shows a clear evolution from foundational work in probabilistic structural analysis to cutting-edge research in hypercomplex automatic differentiation applied to structural mechanics. Recent publications demonstrate a strong focus on developing arbitrary-order sensitivity analysis methods using hypercomplex mathematics, with applications spanning structural dynamics, fracture mechanics, additive manufacturing, and uncertainty quantification. His scientific recognition includes multiple U.S. Air Force Research Lab Summer Faculty Fellowships awarded in consecutive years (2005-2007). These prestigious awards reflect the practical impact of his research on aerospace engineering applications. Dr. Millwater's research has been supported by significant funding from defense and aerospace sectors, particularly the Air Force Office of Scientific Research. His work on probabilistic methods for risk assessment of airframe digital twin structures represents a major contribution to modern structural integrity assessment. He has also contributed to educational initiatives focused on improving STEM education at Hispanic-serving institutions. His laboratory work centers on computational mechanics, with emphasis on developing and implementing advanced numerical methods for structural analysis. The ZFEM (Complex Variable Finite Element Method) framework appears to be a cornerstone of his research program, enabling high-precision sensitivity calculations that have broad applications across engineering disciplines.

• Machine Learning
• Deep Learning
• Medical Informatics
• +۳ مورد دیگر

Nasmin Jiwani is a Research Scholar with 56 publications, an h-index of 20, and 921 total citations. Her academic work spans interdisciplinary applications of machine learning and deep learning techniques across medical diagnostics, cybersecurity, and IoT systems. Her research focuses on Medical Informatics where she develops AI-driven diagnostic tools for liver disease prediction, diabetic retinopathy classification, and acute lymphoblastic leukemia detection. In Cybersecurity , she pioneers image-based malware classification using deep learning architectures. Her IoT Systems research includes supply chain optimization and smart security applications. Recent work shows increasing emphasis on healthcare technology integration, particularly in cancer diagnostics and autism spectrum disorder analysis. Collaboration patterns indicate strong partnerships with Ketan Gupta (30 co-authored papers), J. Logeshwaran, and Neda Afreen across IEEE conferences and journals. Her publication trajectory demonstrates consistent output with 10+ papers annually since 2022, showing particular strength in translating theoretical machine learning models to practical healthcare and security applications.

Sándor Kisfaludi-Bakمشاهده پروفایل

استادیار

• Algorithms
• Computational Geometry
• Geometric Optimization
• +۴ مورد دیگر

Sándor Kisfaludi-Bak is an Assistant Professor in the Department of Computer Science at Aalto University, specializing in theoretical computer science with a focus on computational geometry. He develops algorithms for geometric problems involving points, curves, shapes, and spatial networks. His research interests include Algorithm design for geometric optimization Computational geometry fundamentals Spatial network analysis Hyperbolic and planar graph algorithms Parameterized complexity in geometric contexts Recent publications demonstrate expertise in Traveling Salesman Problem optimization, Steiner network construction, and hyperbolic graph analysis. Key research trends span computational geometry, graph theory, and algorithmic complexity in spatial domains. He has no listed scientific awards in the provided materials. No information about student advising or organizational affiliations beyond Aalto University was found.

• Terahertz Imaging
• Submillimeter-wave Technology
• Quasioptical Systems
• +۵ مورد دیگر

Aleksi Tamminen serves as a Lecturer in the Department of Electronics and Nanoengineering at Aalto University, Finland, specializing in terahertz and submillimeter-wave technologies with significant biomedical applications. His academic role bridges electrical engineering, optics, and medical diagnostics, focusing on instrumentation development for non-invasive corneal water-content sensing. His research expertise spans: Terahertz imaging system design Quasioptical measurement techniques Submillimeter-wave holography Biomedical sensor development Corneal diagnostic instrumentation Analysis of his 15 most recent publications (2023-2025) reveals a concentrated evolution toward automated optimization frameworks and telecentric imaging systems. His work increasingly integrates computational methods (automatic differentiation, boundary integral techniques) with optical engineering to solve calibration challenges in cryogenic and biomedical contexts. A dominant theme across 70% of these publications is corneal sensing, demonstrating sustained focus on ophthalmic applications of terahertz technology. While specific awards remain undocumented in source materials, his extensive publication record in SPIE journals and IEEE transactions indicates recognition within the terahertz research community. His technical contributions to quasioptical calibration standards and frequency-diverse holography represent significant methodological advances. Dr. Tamminen's academic activities include teaching within Aalto's microelectronics curriculum and collaborative research with medical institutions for terahertz corneal diagnostics. His laboratory work centers on developing vacuum-compatible measurement systems and compact imaging apparatus for submillimeter-wave applications, with ongoing projects targeting real-time video-rate imaging for medical diagnostics.

• Computer Vision
• Image Processing
• Machine Learning
• +۵ مورد دیگر

Prof. Ing. Adam Herout, Ph.D., is a faculty member at the Faculty of Information Technology (FIT) of Brno University of Technology (BUT). He serves as Deputy Head of the Department of Computer Graphics and Multimedia (DCGM), focusing on computer vision, image processing, and 3D reconstruction. His research spans traffic surveillance, augmented reality, and real-time processing, with applications in medical imaging and autonomous systems. Academic Rank: Professor Department: Computer Graphics and Multimedia Email: herout@fit.vut.cz Herout's research interests lie in computer vision, machine learning, and their interdisciplinary applications. He has pioneered techniques for camera calibration using vehicle landmarks, density-based traffic analysis, and medical imaging solutions like cranial implant design. His work combines theoretical advancements with practical implementations in real-time systems. Key trends in his 15 most recent articles (2019–2023) include deep learning for traffic analysis, medical image segmentation, and optimization of computer vision algorithms. Sub-fields span from automated checkout systems to CNN-based AFM data correction, reflecting his interdisciplinary expertise. Scientific recognitions include the Commemorative Medal of FIT BUT (Bronze 2012, Silver 2019) and the Imagine Cup 2013. He leads the Computer Graphics Research Group at FIT and chairs disciplinary committees.

Mihai Teodor Lazarescuمشاهده پروفایل

دانشیار

• Artificial intelligence
• Capacitive sensors
• Embedded software
• +۱۰ مورد دیگر

Dr. Mihai Teodor Lazarescu is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino , where he contributes to research and teaching activities. He is also a member of the PolitoBIOMed Lab (Biomedical Engineering Lab) and the Ambient Sensing and Processing research group. Scientific Affiliation: IEEE Member (2019-present) Editorial Roles: Guest Editor for SENSORS, ELECTRONICS, and ACM Transactions on Embedded Computing Systems His research interests focus on hardware acceleration for machine learning algorithms, particularly using FPGAs for data center and embedded applications. He works on high-level synthesis optimization flows, capacitive sensor design for indoor monitoring, and low-power embedded systems . His work intersects Internet of Things , Wireless Sensor Networks , and Machine Learning with applications in human localization, environmental monitoring, and industrial automation. Recent publications demonstrate expertise in neural network optimization , DSP resource sharing , and multi-FPGA allocation . His teaching spans Applied Electronics , Digital Electronic Design , and Embedded Systems Optimization across bachelor's and master's programs in Electronic Engineering and Computer Engineering . Patents: Noise cancellation for single-plate capacitive sensors Capacitive sensor for space change detection Projects: Scientific Manager for Horizon 2020-S2RJU project (2018)

• Medical Image Processing
• Bioengineering
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Kristen Mariko Meiburger is an Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. She is a member of the PolitoBIOMed Lab , focusing on biomedical engineering research. Research Interests: Medical image processing, photoacoustic imaging, ultrasound technologies, and AI-driven diagnostic systems. Her work bridges industrial and information engineering with clinical applications. Recent Publications highlight advancements in photoacoustic uncertainty quantification, high-frequency vascular imaging, machine learning for muscular dystrophy analysis, and optoacoustic/ultrasound reconstruction techniques. Scientific Awards: Premio di Laurea GNB (2011) Premio di Qualità (2014) Key Projects: ImPACT-AI (2023-2025) AI-VASCUES (2023-2025) REAP (2021-2024) H2020-ICT (EU-funded) PhD Students: Bruna Cotrufo, Alen Shahini, Federico Sinnona, Matteo Salvi, Giulia Rotunno, Francesco Branciforti, Francesco Marzola.

• Electronics
• Nanocomputing
• Quantum Technologies
• +۱۲ مورد دیگر

Fabrizio Riente is a Fixed-term Researcher at the Department of Electronics and Telecommunications (DET) , Politecnico di Torino. He holds academic responsibilities in multiple programs and contributes to editorial and conference committees. Member of College of Electronic, Telecommunications and Physics Engineering Invited Member of College of Computer, Film, and Mechatronics Engineering His research spans Nanocomputing , Quantum Technologies , and Machine Learning for environmental and healthcare applications, with a focus on: Qubit Control & Readout Systems IoT for Bee Health Monitoring 3D Audio-Visual Reproduction for Hearing Research Hybrid Simulation and Emerging Nanotechnologies Low-Power Electronic Systems His recent publications demonstrate interdisciplinary work bridging Quantum Electronics and Acoustic Ecology , particularly in developing VLSI architectures for novel applications. Notable scientific awards include Associate Editorship at Frontiers in Electronics and program committee roles at international conferences. He supervises PhD students in Quantum Engineering and Electronic Engineering , directing research projects funded by commercial contracts on quantum architectures and automotive technologies. His teaching portfolio includes courses on Microelectronic Systems and Low-Power Electronics .

• Artificial intelligence
• Energy efficiency
• Smart cities
• +۷ مورد دیگر

Massimo Ruo Roch serves as an Associate Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, Italy. His academic appointment falls under the scientific disciplinary sector IINF-01/A - Electronics within Area 0009 - Industrial and Information Engineering. His research spans multiple cutting-edge domains including Artificial Intelligence, Internet of Things, Energy Efficiency, Smart Cities, Logic in Memory, and Nanomagnetics . His work aligns with several European Research Council sectors including Micro- and nano-systems engineering, Artificial intelligence, Computer architecture, and Distributed systems. Ruo Roch leads the VLSILAB research group and has developed significant expertise in smart embedded systems for lighting and IoT applications, as well as agritech with autonomous robot systems for grape harvesting. His publication record demonstrates consistent contributions to low-power computing, magnetic logic circuits, and error correction techniques dating back to the late 1990s. Among his notable recognitions are the National Innovation Award (2013) and the prestigious Prize of Prizes (2014) conferred by the President of the Italian Republic through the National Foundation for Technological Innovation COTEC. He actively supervises doctoral candidates including Fabrizio Mo (working on Molecular Sensors at the Nanoscale) and Andrea Mongardi (researching Bio-inspired sEMG-based embedded systems). His research portfolio includes multiple commercial contracts and patents related to test systems, data-driven architectures, and intelligent lighting devices.

Ali Madooeiمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Software Engineering
• Instructional Design
• +۴ مورد دیگر

Ali Madooei is a Teaching Professor in the Department of Computer Science at Johns Hopkins University, affiliated with the Whiting School of Engineering. He specializes in computer science education, software engineering, instructional design, and learning technology, with a focus on hands-on project-based learning. Department: Computer Science School: Whiting School of Engineering Academic Rank: Teaching Professor Email: madooei@jhu.edu His research interests revolve around enhancing software development education through project-based learning environments. He established the Coding, Learning, and Application-Building Lab (COLLAB) , which provides students with unstructured, self-directed software project experiences. He also leads the AI-Assisted Instruction Lab , exploring how artificial intelligence can improve educational technology. Madooei's work emphasizes modern technology stacks, employability, and flexible remote collaboration, with projects often aligning with industry standards. Additionally, he has contributed to biomedical imaging through prior research in color modeling and hyperspectral analysis for skin lesion diagnostics. Ali Madooei has received the Whiting School of Engineering Excellence in Teaching Award (2024) , highlighting his commitment to pedagogical innovation in computer science education. As an educator, Madooei promotes independent learning, mentorship, and leadership development in his labs. His labs support a dozen students each term with academic credit and practical experience, offering paid, volunteer, and self-directed project opportunities. Projects are structured around sprint cycles and remote collaboration, with students encouraged to propose ideas or join existing initiatives. He has previously taught at the University of British Columbia, Simon Fraser University, and Kwantlen Polytechnic University, bringing diverse institutional experience to his current role.

• System Dynamics
• Control Systems
• Fluid Power Control
• +۴ مورد دیگر

Professor Yücel Ercan is affiliated with the Department of Mechanical Engineering at TOBB University of Economics and Technology (TOBB ETÜ). He previously held academic positions at Middle East Technical University (METU) and Gazi University, including roles as assistant professor, associate professor, and professor of mechanical engineering. His career spans over 40 years, with a focus on system dynamics, control systems, and industrial applications. Education : B.Sc., M.Sc., and Sc.D. in Mechanical Engineering from MIT (1966, 1968, 1971) Leadership Roles : Vice-Chairman at METU (1974-1977), Vice-President of METU (1977-1978), Dean of Gazi University School of Engineering (1982-1992), and held similar roles at TOBB ETÜ. His research interests lie in system dynamics, control systems, fluid power control, and industrial emission control. He has developed advanced methodologies for nonlinear vibration analysis and time-suboptimal control of industrial manipulators, contributing significantly to manufacturing and mechanical systems optimization. The 8 recent publications demonstrate expertise in nonlinear vibrations, control algorithms, and computer-aided manufacturing. Key trends include modeling machine tool vibrations, optimizing robotic task sequencing, and enhancing industrial machinery control systems through innovative theoretical frameworks and software development. Scientific Awards : Alexander von Humboldt Fellowship (research in Germany, 1979-1981) Academic Leadership & Contributions : Supervised 28 master’s and 5 doctoral theses, led approximately 80 research projects, and provided consulting services to 250 industrial companies. He is a member of professional societies including TMMO, TOK, TIBTD, and MATİM.

Thijs Roumenمشاهده پروفایل

استادیار

• Digital Fabrication
• Human-Computer Interaction (HCI)
• Laser Cutting
• +۳ مورد دیگر

Thijs Roumen is an Assistant Professor at Cornell Tech within the Department of Information Science . He leads the Matter of Tech Lab , focusing on Digital Fabrication and Human-Computer Interaction (HCI) . His work aims to democratize fabrication technology for non-industrial users. PhD from Hasso Plattner Institute MSc in IT Product Design from University of Southern Denmark BSc in Industrial Design from Eindhoven University Research interests include: Laser cutting portability 3D modeling tools Fabrication error prevention Accessible haptic interfaces Recent publications address asynchronous hardware troubleshooting (SplatOverflow, CHI'25), medical robotics (HRI'25), and fabrication artifact data storage (StructCode, SCF'23). His work has received multiple Best Paper Honorable Mentions at CHI and UIST conferences. Scientific contributions include: Key role in CHI meta (2018-present) Chair of German Networking Events at CHI Subcommittee leadership in DIS, CHI, and UIST Active in lab collaborations and invited talks at institutions like Stanford, MIT, and University of Tokyo. Also a World Major Marathon Finisher (Chicago 2023, Berlin 2019).

Jaime dos Santos Cardosoمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Medical Image Analysis
• +۱۱ مورد دیگر

Jaime dos Santos Cardoso is a Full Professor at the Department of Electrical and Computer Engineering (DEEC) in the Faculty of Engineering of the University of Porto (FEUP), Portugal. Simultaneously, he is involved in research and development activities at INESC TEC in the Centre for Telecommunications and Multimedia, where he co-founded the Breast Research Group and the Visual Computing and Machine Intelligence (VCMI) Group. His research focuses on computer vision, pattern recognition, and machine learning with applications in medical decision support systems, biometrics, and visual information processing. University of Porto, Faculty of Engineering (2006-present) INESC TEC, Centre for Telecommunications and Multimedia (current) Co-founder of Visual Computing and Machine Intelligence (VCMI) Group Ph.D. in ECE (Computer Vision) from University of Porto (2006) Professor Cardoso's research interests span computer vision, machine learning, deep learning, medical image analysis (particularly breast and cervical cancer), biometrics, and medical decision support systems. His work emphasizes interpretable models, data-efficient learning approaches, and tackling challenges like class imbalance and ordinal data in visual information processing. The VCMI group under his leadership pursues never-ending visual information learning systems to empower intelligent systems with visual reasoning capabilities. His research has significant applications in medical imaging, particularly in breast cancer screening and diagnosis, breast cancer surgery planning and evaluation, and cervical cancer screening. The group develops Computer-Aided Diagnosis (CAD) systems that can be integrated into clinical workflows to improve detection, diagnosis, and treatment planning. World's Top 2% Scientists recognition Extensive publication record in top-tier computer vision and medical imaging conferences and journals Leadership in multiple research projects including AI-RBD, AI-Care4U, OBJECT, and AI4Lungs Professor Cardoso has supervised numerous PhD and Master's students, with many completing their degrees under his guidance. His students have worked on diverse topics including breast cancer aesthetic assessment, multimodal biometrics, medical image analysis, and deep learning applications in healthcare. He has received research funding for various projects focused on applying machine learning to medical challenges, particularly in oncology and medical imaging. The Visual Computing and Machine Intelligence (VCMI) group, which he co-founded, has evolved significantly since 2011, becoming the main research group within the Information Processing and Pattern Recognition (IPPR) Area at CTM. The group maintains a balance between senior and junior researchers, fostering a collaborative environment for advancing research in visual computing and machine intelligence.

• Animation
• Animation Short Film Creation
• Health Communication
• +۳ مورد دیگر

Liao Shasha serves as a Lecturer in the Department of Animation at Tongji University's School of Art and Media, where she has taught since 2007 while holding administrative roles as Secretary of the Animation Department and Director of the College Library. Her academic journey includes a Bachelor's in Computer Science from North China University of Technology (2002) and a Master's in Software Engineering from Peking University (2007). Her research centers on animation short film creation and health communication , with significant contributions to experimental animation pedagogy, 3D animation production, and the integration of traditional Chinese crafts like Diancui (kingfisher feather art) into contemporary art education. She has developed specialized courses including Animation Storyboarding, 3D Animation, and Traditional Art Design that emphasize hands-on learning and interdisciplinary approaches. Analysis of her 11 publications (2006-2022) reveals a clear trajectory toward educational applications of animation, particularly in health communication initiatives and digital preservation of intangible cultural heritage. Her work consistently bridges technical animation skills with social impact through projects like medical科普 (science popularization) and traditional craft revitalization. Liao Shasha's scholarly impact is reflected in numerous awards: 2005-2007: Multiple awards for animations 'Plant' and 'Injustice' including China Academy Award wins and DigiCon6+3 Gold 2018: 1st Prize at 'Guoqing Cup' for 'Kingfisher Phoenix Headwear' 2020: Tongji University Xincheng Award and dual 'Excellent Mentor' titles 2020-2022: Nine national teaching awards including NCDA 'Excellent Guidance Teacher' honors As an educator, she has secured eight principal-investigator teaching grants totaling over 500,000 RMB, including the 'Virtual Simulation Software for Digital Shadow Play Animation' project (2020). Her mentorship has guided students to 32 competition awards including the National Network Culture Festival Animation First Prize (2019). She actively contributes to Tongji's Media Experiment and Practice Teaching Center and Omnimedia Research Institute, developing innovative animation pedagogy that merges traditional craftsmanship with digital media.

Alessandra Suttiمشاهده پروفایل

دانشیار

• Materials Science
• Sustainable Textiles
• Environmental Science
• +۲ مورد دیگر

Alessandra Sutti is an Associate Professor at Deakin University's Institute for Frontier Materials , focusing on polymers, textiles, and sustainable material solutions. Her work bridges industry collaboration with environmental stewardship, particularly through microplastics research and STEM education initiatives. PhD in Materials Science from Universita' degli Studi di Parma (2007) Active in Australian Research Council-funded projects and industry partnerships