جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +۵ مورد دیگر

Renan Guarese is a Postdoctoral Researcher in Human-Computer Interaction at KTH Royal Institute of Technology , Sweden, focusing on AR/VR applications for pharmaceutical manufacturing through the SMART Industry project with AstraZeneca. He holds a Ph.D. from RMIT (Australia) and M.Sc. from UFRGS (Brazil), with expertise in assistive technologies, situated data visualization, and accessibility. His roles include teaching assistant for courses like Advanced Graphics and Multimodal Interaction, and M.Sc. thesis supervision. He has over 10 years of academic experience across institutions like RMIT, Halmstad University, and UFRGS, with projects ranging from assistive AR for visually impaired individuals to educational AR platforms. Research Interests: Human-Computer Interaction (HCI), Augmented and Virtual Reality (AR/VR), assistive technologies, situated visualization, and accessibility design. He specializes in applications like sonified AR interfaces, industrial training, and empathy-building experiences for marginalized users. Awards: Best Doctoral Thesis (SVR 2024) Finalist, Cross-Reality Systems Competition (IEEE ISMAR 2023) Nomination for Best Paper Award (IEEE VR 2023) Latin American PhD Scholarship (ATN grant) Advising & Grants: Supervising 3 current M.Sc. theses (2025) and co-authoring grants focused on conversational AI in industrial training and predictive maintenance. His work bridges HCI with real-world industry needs, emphasizing accessibility and immersive solutions. Labs/Teams: Active in KTH's Digital Futures initiative and collaborates with AstraZeneca on pharmaceutical AR/VR applications. Engages in international conferences like IEEE VR, ISMAR, and CHI through peer reviewing, workshop organizing, and panel participation.

Miroslav Bjekićمشاهده پروفایل

استاد

• Electrical Power Engineering
• Electric Machines
• Electromechanical Systems Simulation
• +۳ مورد دیگر

Miroslav Bjekić is a Full Professor at the Department of Electrical Power Engineering, Faculty of Technical Sciences, University of Kragujevac (Čačak, Serbia). His academic journey includes a PhD (2006) and Master's (1995) from Serbian institutions, with undergraduate studies completed at the Technical Faculty in Čačak (1991). He received academic excellence awards during his studies. His research spans electrical machines, energy efficiency, electromechanical simulation, and renewable energy systems . Key focus areas include: Design and optimization of electric motors/drives Energy-efficient industrial systems Educational technology for engineering Smart grid and distributed generation His publications emphasize experimental validation, simulation tools (GeoGebra, MATLAB), and applied solutions for energy challenges , with consistent themes in motor control efficiency, educational innovation, and sustainable energy integration. Awards/Honors: University of Kragujevac & Technical Faculty Čačak Study Excellence Awards Second Prize, International PhD Seminar (Ohrid, 2005) Leadership & Projects: He modernized laboratories for Electrical Machines/Drives and led national projects like TR33016 on energy efficiency in motor drives. International collaborations include TEMPUS initiatives and DAAD-funded programs. He chaired the Rotating Electrical Machines Standards Committee (Serbian Institute of Standardization, 2012–2017). Educational Development: Created original educational software for electrical engineering and accredited teacher training programs. Supervised laboratory development for remote experiments and industrial collaborations.

• Computer Engineering
• Parallel Computing
• Field-Programmable Gate Arrays (FPGAs)
• +۵ مورد دیگر

Zuofu Cheng is a Teaching Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research focuses on parallel computing, FPGA-based machine learning acceleration, GPU optimization, and innovative engineering pedagogy. He has contributed to curriculum development in computer engineering education and advanced mesh optimization algorithms for heterogeneous computing systems. Research interests include: Hardware acceleration for AI/ML systems Parallel algorithm design for multi-core architectures Interactive engineering education methodologies Real-time acoustic simulation engines Publications highlight trends in FPGA/GPU optimization, IoT applications of machine learning, and computational thinking integration in undergraduate curricula. Over 75 citations reflect notable impact in hardware-accelerated computing domains. Active collaborations include work with IEEE conferences and HPC training initiatives.

Stefan Gumholdمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Medical Imaging
• +۳ مورد دیگر

Professor Stefan Gumhold is a leading academic in computer graphics and visualization at TU Dresden. He has held roles including Head of the Chair for Computer Graphics and Visualization since 2005 and served as Dean of the Faculty of Computer Science from 2010 to 2012. His expertise spans visualization techniques, medical imaging, and immersive technologies. Gumhold earned his Ph.D. in 2000, focusing on mesh compression, and later received a Dissertation Award in the same year. He has contributed to projects like the Heisenberg Scholar Research Group and led the Kommission Umwelt at TU Dresden. His teaching includes courses such as Introduction to Computer Graphics, Data Visualization, and Scientific Visualization. Gumhold’s research emphasizes visualization platforms (e.g., ISAAC), image fusion, and neural network applications in medical diagnostics. His work often integrates virtual reality for data analysis, as seen in tools like VRCellLabeler and ExtremeWeatherVis. Education: Diploma in Computer Science (University of Tübingen, 1998), M.Sc. in Applied Physics (University of Massachusetts Boston, 1996). Research Highlights: Development of visualization frameworks, 3D reconstruction, and invertible neural networks for outlier detection. Awards: Dissertation Award 2000. Grants & Labs: Leadership in TU Dresden’s Computer Graphics lab and contributions to collaborative research projects like Fast-Haptic.

• Computational Intelligence
• Machine Learning
• Time Series Forecasting
• +۵ مورد دیگر

Dr. Hai Yan Lu is an Associate Professor at the School of Computer Science , Faculty of Engineering and Information Technology , University of Technology Sydney (UTS) . She serves as Head of Discipline for Data Analytics and is a core member of the Decision Systems and e-Service Intelligence Lab within the Centre for Artificial Intelligence at UTS. Her academic journey includes a PhD in Engineering (2002) from UTS, Master of Engineering (1988) and Bachelor of Engineering (1985) from Harbin University of Science and Technology , China. She transitioned from a Lecturer at Yanshan University to UTS in 1994. Research Interests: Computational Intelligence, Time Series Forecasting, Data Analytics, Electromagnetic Material Modeling, 3D Human Pose Estimation, Smart Energy Systems Key Projects: Smart Power Grids, Intelligent Multi-Agent Systems, Predictive Analytics for Renewable Energy, Electromagnetic Device Optimization Technical Expertise: Machine Learning, Deep Learning, Federated Learning, Multi-Objective Optimization, Granular Computing Professional Affiliations: Senior Member, IEEE Member, ACM Vice Chair, IEEE NSW Section Women in Engineering Secretary/Treasurer, IEEE NSW Computational Intelligence Chapter Her recent publications demonstrate cutting-edge work in: Regularized Deep Learning for Financial Risk Modeling GAN-based Environmental Forecasting Hybrid Forecasting Systems for Solar Energy Advanced Magnetic Material Characterization Explainable AI for Industrial Applications

• Mathematics Education
• Language Training
• Educational Technologies
• +۵ مورد دیگر

ДИАНА ИЛИЕВА ИЗВОРСКА serves as Professor and Head of the Department of Language and Specialized Training at Technical University - Gabrovo. With a Doctorate in Mathematical Sciences, she has established herself as a leading academic in mathematics education, language training, and educational technologies. Her interdisciplinary approach bridges theoretical knowledge with practical applications in technical education. Dr. Izvorska's research spans multiple interconnected domains with a consistent focus on modern educational technologies and competency-based approaches. She has made significant contributions to mathematics education methodology, particularly in critical thinking development, reflection in mathematical training, and individualized learning approaches. Her work on professional competence development in technical university students has been particularly influential, connecting mathematical foundations with language education and pedagogical innovation. Analysis of Dr. Izvorska's recent publications reveals a strong trend toward integrating information technologies with traditional educational methodologies. Her research demonstrates practical applications of theoretical concepts across various educational contexts, from elementary mathematics to advanced engineering education. She has explored computational mathematics systems in higher mathematics training, project-based learning in information technologies, and the development of information competence across different educational levels. 25 research projects led, primarily focused on educational technologies 101 total publications including 9 books and numerous scholarly articles International collaborations across Europe and Ukraine Dr. Izvorska maintains active leadership in her department while continuing to advance educational theory and practice through her scholarly work and project management.

Zhenkai Zhangمشاهده پروفایل

استادیار

• Computer Systems Security
• Cyber-Physical Systems
• Hardware Security
• +۴ مورد دیگر

Zhenkai Zhang is an Assistant Professor at the School of Computing, Clemson University. Previously, he held an academic position at Texas Tech University (2019–2021). His research focuses on computer systems security, cyber-physical systems, and hardware vulnerabilities. He holds a Ph.D. from Vanderbilt University (supervised by Prof. Xenofon Koutsoukos), an M.S. from the University of Chinese Academy of Sciences, and a B.S. from Beijing Institute of Technology. His research interests include GPU security, side-channel attacks, memory corruption exploits, and defensive techniques leveraging physical layer information. Recent work involves GPU cache attacks, DNN backdoor insertion, and electromagnetic side-channel exploitation. Received "Distinguished Reviewer" award at CCS'24 . Notable contributions include Graphics Peeping Unit (Oakland 2022), Leveraging EM for Rowhammer Detection (Oakland 2020), and BitJabber (HOST 2020). Current Ph.D. advisees include Hongyue Jin and Fatemeh Moradihaghighi. Alumni Zihao Zhan and Sisheng Liang now hold academic positions. Active grants include NSF projects on rowhammer defenses and secure CPS control. Professional activities include TPC roles at CCS, Oakland, and EuroS&P, plus editorial and organizational roles in security conferences.

• Mechanical Engineering
• Railway Systems
• Multibody Dynamics
• +۳ مورد دیگر

Eduardo Corral Abad is an Associate Professor in the Department of Mechanical Engineering at Carlos III University of Madrid, specializing in multibody dynamics, railway systems, and contact mechanics. His research spans industrial heritage, vibration analysis, and educational technology. Railway axle monitoring and crack detection using advanced signal processing Dynamic modeling of mechanical systems with nonlinear contact and friction forces Development of interactive teaching applications for engineering education Use of parallel computing and GPU acceleration in mechanical simulations His contact email is eduardo.corral@uc3m.es . Recent work includes publications on railway diagnostics, helical gear transmissions, and Android-based educational tools.

Anna Ursynمشاهده پروفایل

استاد

• Art
• Computer Graphics
• Knowledge Visualization
• +۷ مورد دیگر

Anna Ursyn is a Professor and Computer Graphics/Digital Media Area Head at the School of Art & Design , University of Northern Colorado, within the College of Performing and Visual Arts . Her work bridges academic research, artistic practice, and technological innovation. PhD, MFA in Computer Graphics/Digital Media Active in international IEEE, ACM SIGGRAPH, and educational committees Recipient of numerous grants and awards for digital media contributions Her research focuses on knowledge visualization , visual storytelling , and interdisciplinary education . She explores how computer graphics can enhance communication across science, art, and education through projects like NASA's MoonArc and exhibitions at Louvre and NTT Tokyo. Recent publications address data visualization , visual literacy , and creative interface design . Her advising includes students in digital media and computer graphics programs. Awards include ACM SIGGRAPH grants , multiple Who’s Who listings, and international art competition recognitions. Editor's Choice Award , International Library of Poetry Artistic Merit Award , Eurographics 1996 Animal Image Award , Argentina Ursyn leads the Digital Art Gallery D-ART iV and SpaceTime competition , while maintaining an active studio practice that combines 3D programming , mixed-media sculpture , and scientific illustration .

Hai Linمشاهده پروفایل

استاد

• Computer Graphics
• Scientific Visualization
• Volume Rendering
• +۲ مورد دیگر

Hai Lin is a Professor at the State Key Lab of CAD&CG (Zhejiang University, China). His research spans computer graphics, scientific visualization, volume rendering, virtual reality, and graphical electromagnetic computing. He earned B.Eng and M.Eng degrees from Xidian University (1987, 1990) and a Ph.D. in Computer Science from Zhejiang University. Current Position: Professor, Zhejiang University (1990–Present) Research Fellow, Medical Visualization, De Montfort University (2000–2003) Visiting Professor, University of Bedfordshire Research Focus includes: Medical Imaging: AI-driven tumor segmentation (colorectal, liver), retinal disease classification (SatFormer), and mandible segmentation via LRVRG. Electromagnetic Computing: Shape deformation optimization, GPU-based wave propagation prediction, and scattering analysis. Scientific Visualization: Graph convolutional networks for volume data, voxel2vec representations, and dynamic network exploration. Collaborations involve PhD students (Huan Liu, Yiming Li, YanKai Jiang, Han Wang) and teams at Zhejiang University. His work integrates AI with electromagnetic and medical imaging domains, emphasizing GPU acceleration and novel algorithm design.

Arne Schmitzمشاهده پروفایل

پژوهشگر

• Radio Wave Propagation
• Computer Graphics
• Wireless Network Simulation
• +۳ مورد دیگر

Dr. Arne Schmitz is a researcher at the Department of Computer Science, RWTH Aachen University, specializing in computational methods for wireless communications and computer graphics. His work bridges radio wave propagation physics with advanced visualization techniques, focusing on practical applications for mobile network planning and mobile device interfaces. His primary research domains include: Radio wave propagation modeling in urban environments GPU-accelerated beam/ray tracing algorithms Antenna pattern compression using spherical harmonics Real-time 3D visualization for resource-constrained mobile devices Ad-hoc multi-display systems for collaborative mobile applications Analysis of his publication timeline reveals an evolution from foundational radio propagation models (2006) toward increasingly sophisticated urban simulation frameworks (2011-2012), with consistent emphasis on computational efficiency. His most impactful contributions integrate computer graphics rendering techniques with telecommunications engineering, particularly in adapting beam tracing for radio wave simulation and developing novel mobile visualization paradigms that overcome hardware limitations through client-server architectures. Dr. Schmitz maintains a strong collaborative relationship with Professor Leif Kobbelt and colleagues at RWTH Aachen, with co-authorship appearing in 9 of his 10 documented publications. His research demonstrates consistent funding support through participation in IEEE and ACM conferences, though specific grant details are not disclosed in the available materials.

Saverio Bolognaniمشاهده پروفایل

پژوهشگر ارشد

• Control Systems
• Model Predictive Control
• Sensorless Control
• +۴ مورد دیگر

Saverio Bolognani is a Research Fellow at the Massachusetts Institute of Technology (MIT), focusing on advanced control systems for electric drives and power systems. His work bridges graphical models, Bayesian networks, and sensorless control techniques for synchronous and induction motors. Current affiliation: MIT, USA Past affiliation: Department of Information Engineering, University of Padua Research interests include: Model Predictive Control for electric drives Sensorless and self-sensing motor control Microgrid topology identification Machine learning applications in power systems His publications reveal a focus on optimization algorithms for electric vehicles, reliability of electrified transportation systems, and real-time control strategies using Kalman filters and digital twins. Key subfields include deadbeat control, high-frequency signal injection, and torque ripple minimization.

Suzana Loshkovskaمشاهده پروفایل

استاد

• Programming
• Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Suzana Loshkovska, PhD , is a Full Professor at the Faculty of Computer Science and Engineering of Ss. Cyril and Methodius University in Skopje , Macedonia. Since 1992 she has held continuous academic appointments, interrupted only by a visiting-researcher stay at the Academy of Sciences of Lower Austria (1993–1994) where she designed a medical information system for Krems Hospital. Education : BSc (1989) and MSc (1992) in Computer Science and Automation, Faculty of Electrical Engineering, Skopje PhD (1995) in Technical Sciences, Technical University of Wien, Austria Research Interests span programming, visualization, human–computer interaction, virtual reality, medical imaging, and modelling/visualization of medical processes. Her work integrates advanced algorithmic techniques—such as hierarchical multi-label classification, support-vector machines, predictive clustering trees, and Bayesian networks—into practical medical and multimedia applications. Across more than one hundred peer-reviewed publications, her recent articles concentrate on content-based medical image retrieval , annotation of medical images , visual concept detection , and interactive medical systems . These contributions collectively advance computer-aided diagnosis, clinical decision support, and efficient management of large-scale medical data sets. Scientific Awards & Recognition : Member, Editorial Board, INFORMATICA (international journal, Slovenia) Projects & Funding : Principal investigator or participant in bilateral and EU-funded projects including SEE-ERA.NET Plus, TEMPUS DL@WEB, TEMPUS M.Sc. E-Learning, and multiple Macedonian Ministry of Science grants covering medical imaging, environmental modelling, distance learning, and electromagnetic-effects visualisation. While no specific research group or laboratory name is provided, her sustained involvement in national and international projects indicates active leadership within the university’s medical-informatics and multimedia-research community.

Mark McCartneyمشاهده پروفایل

مدرس ارشد

• Chaotic dynamics
• Mathematical ecology
• Mathematics education
• +۳ مورد دیگر

Dr Mark McCartney is Senior Lecturer in Mathematics at Ulster University’s School of Engineering, Belfast campus. His research integrates chaotic dynamics, mathematical ecology, mathematics education, and the history of science. Education: BSc (Hons) Applied Mathematics – Queen’s University Belfast PGCE Secondary Education – Queen’s University Belfast MSc Theoretical Atomic Physics – Queen’s University Belfast PhD Theoretical Atomic Physics – Queen’s University Belfast Research Interests: His work explores nonlinear dynamical systems, predator–prey interactions, and the pedagogical use of mathematical history. He employs coupled map lattices, neural networks, and fractal methods to model complex ecological and physical phenomena, while simultaneously investigating how historical narratives can enrich university mathematics curricula. Awards & Recognition: Catherine Richards Prize – Institute of Mathematics and its Applications (2020) Maths Week Ireland Award (2019) President, British Society for the History of Mathematics (2018–2020) Associate Editor, International Journal of Mathematical Education in Science & Technology Member, Education Committee, London Mathematical Society Grants & Projects: Principal Investigator, Mathematical Motivators: using the history of mathematics to enrich the curriculum (2009–2011) Principal Investigator, Enhancing maths support provision in Scotland and Northern Ireland (2012) Principal Investigator, Instability in mathematical models for traffic flow on a loop (2009) Co-Investigator, Explaining Away in Science and Religion (2013–2015) Co-Investigator, Conjunctive Explanations: how science and religion can work together (2018–2021) Books & Editorial Work: He has co-edited six volumes on the history of mathematics and physics, including Oxford's Sedleian Professors of Natural Philosophy: The First 400 Years (Oxford University Press, 2024, with Chris Hollings).

• Electrical Engineering
• Electric Traction Systems
• Induction Motors
• +۴ مورد دیگر

Dr. Eng. Radu Pentiuc is a Lecturer in the Department of Electrotechnics at the Faculty of Electrical Engineering, University Stefan cel Mare of Suceava. He holds a doctorate in Electrical Technologies (1997) from Universitatea "Gh. Asachi" din Iași and specializes in electric traction systems, industrial power applications, and advanced motor design. With industrial experience prior to his academic career, he bridges theoretical and practical engineering concepts. Research Focus: His work centers on optimizing electric motor efficiency, particularly in hybrid and linear induction systems. Key investigations include electromagnetic field analysis, toroidal inductor configurations, and reducing border effects in motor design. His research extends to industrial power systems, energy conversion technologies, and electric traction applications for railway systems. Publications: His articles (1994-1998) predominantly explore electromagnetic motor design, computational modeling of hybrid systems, and efficiency optimization. Recurring themes include toroidal inductors, magnetic flux analysis, and novel approaches to linear induction motor construction. Student Advising & Projects: Supervised 12+ diploma projects (1993-1998) resulting in functional prototypes, including: Reactive energy compensation devices Electromagnetic braking systems Linear motor designs Industrial power control systems Research Contracts: Coordinated/participated in 13 projects, including: Minimizing technological outputs at SPIT Bucovina SA Optimizing solar energy conversion installations Developing low-speed induction motors Hybrid motor design algorithms Patents: Contributed to 6 inventions including asynchronous linear motors, low-speed induction motors, and electromagnetic drive systems.