جست‌وجوی استاد و پژوهشگر

Zoltán Sütőمشاهده پروفایل

دانشیار

• Power Electronics
• Control Systems
• Power Converters
• +۵ مورد دیگر

Zoltán Sütő is an Associate Professor at the Budapest University of Technology and Economics, affiliated with the Department of Automation and Applied Informatics. His research focuses on advanced power electronics and control systems, with expertise in real-time implementation using FPGA technology. He maintains an active presence through institutional contacts at Budapest 1117, Magyar tudósok krt. 2., Q.B114, and can be reached via phone (+36 1 463-2337) or email (Suto.Zoltan@aut.bme.hu). Dr. Sütő's research encompasses: Design and optimization of power converters (dual active bridge, multilevel inverters) Real-time control algorithms for grid-connected systems and microgrids FPGA-based hardware-in-the-loop simulation methodologies Nonlinear dynamics in power electronic systems Artificial intelligence applications for fault diagnosis in drive systems His work bridges theoretical control models with practical implementations in renewable energy integration and power quality management. Recent publications demonstrate a strong focus on predictive control techniques, adaptive compensation methods, and optimization of power converter topologies. Research trends emphasize real-time validation, FPGA implementation, and AI-enhanced diagnostics across applications ranging from energy storage systems to industrial drives. Articles consistently address efficiency improvements, stability challenges, and novel modulation strategies in power conversion.

Hongjie Wangمشاهده پروفایل

استادیار

• Power Electronics
• Electric Vehicle Charging
• Resonant Converters
• +۲ مورد دیگر

Hongjie Wang is an Assistant Professor in Electrical and Computer Engineering at Utah State University, where he serves as co-director of the Utah State University Power Electronics Laboratory and leads the NSF ASPIRE ERC Charging Stations of the Future project. His research focuses on power electronics for transportation electrification, particularly extreme fast charging systems and dynamic wireless power transfer. Research domains include: High-efficiency resonant converter design Grid integration of EV charging infrastructure Second-life battery applications in energy storage Dynamic wireless power transfer for in-motion charging Thermal management of power electronics Recent publications demonstrate innovations in unfolding-based AC-DC converters, load modeling for large-scale charging infrastructure, and reinforcement learning approaches for grid-integrated charging optimization. His work has received multiple best paper awards including recognition from IEEE ECCE and IEEE IAS.

Ian Brownمشاهده پروفایل

استاد

• Energy Conversion
• Electric Machines
• Adjustable Speed Drives
• +۶ مورد دیگر

Ian Brown is a Professor of Electrical and Computer Engineering at Illinois Institute of Technology, part of the Armour College of Engineering. He holds a Ph.D. (2009), M.S. (2003), and B.S. (1999) in Electrical and Computer Engineering from the University of Wisconsin-Madison and Swarthmore College. His research focuses on energy conversion, electric machines, and renewable energy systems, with emphasis on sensorless control, machine design optimization, and traction motor development for electric vehicles. He has extensive industry experience as a principal engineer at A.O. Smith, contributing to electric machine and drive technologies. Research interests include adjustable speed drives, high-power density motors, and applications in sustainable energy. He has advised multiple graduate students and published over 50 peer-reviewed articles in IEEE Transactions and conferences. His recent work explores superconducting circuit breakers, thermal management systems, and advanced winding designs to minimize harmonic distortions. Brown's contributions bridge academic research with industrial applications, particularly in improving energy efficiency and reliability in power conversion systems. He is affiliated with the IEEE and has contributed to journal editorials on electric machines in renewable energy. His lab focuses on experimental prototyping and simulation-driven optimization of electric drives. Current projects include developing brushless capacitive excitation systems for traction motors and analyzing driving cycle-based machine design optimization strategies. Teaching responsibilities include graduate courses on electric machines and power electronics. He maintains active collaborations with industry partners like A.O. Smith and Siemens, emphasizing translational research with commercialization potential.

• Engineering Informatics
• Digital Manufacturing
• Intelligent Manufacturing
• +۱۵ مورد دیگر

Professor Ying Liu is a Professor and Chair in Intelligent Manufacturing at the School of Engineering, Cardiff University, UK, a position he has held since August 2021. He leads the High-value Manufacturing research group within the Department of Mechanical Engineering. Prior to this, he served as an Assistant Professor at the National University of Singapore (2010–2013) and the Hong Kong Polytechnic University (2006–2010). PhD, Innovation in Manufacturing Systems and Technology (IMST), Singapore-MIT Alliance (SMA), National University of Singapore (2006) MSc, Singapore-MIT Alliance (SMA), Nanyang Technological University (NTU) MEng & BEng, Mechanical Engineering, Chongqing University, China His research spans engineering informatics, digital and intelligent manufacturing, AI and machine learning in engineering design, and advanced ICT in manufacturing. He has published over 160 scholarly articles and contributed to major journals and conferences in the field. His recent work focuses on knowledge graphs, digital twins, human-robot collaboration, and energy modeling in smart manufacturing, often integrating large language models and advanced deep learning techniques. The most recent publications highlight a strong trend toward integrating AI, particularly large language models and knowledge graphs, into smart manufacturing systems. Themes include predictive maintenance, battery state estimation, human fatigue modeling, and sustainable manufacturing. His work increasingly emphasizes human-centric approaches aligned with Industry 5.0 principles. Best Paper Award 2022, CCF Transactions on Pervasive Computing and Interaction ESI Highly Cited Paper and Hot Paper, Research and Application of Machine Learning for Additive Manufacturing 2020 Reviewer of the Year, ASME Journal of Computing and Information Science in Engineering (JCISE) Professor Liu actively supervises postgraduate students and has advised several successful PhD candidates, including Dr. Chong Chen and Mr. Zhouyang Ding. His research is funded by major agencies such as EPSRC (UK), GRF (Hong Kong), MOE (Singapore), A*STAR, and NSF (China), as well as industrial partners. He serves as Associate Editor for ASME JCISE, IEEE T-ASE, and several other journals, and was recently appointed Senior Editor of the Journal of Engineering Design. He also leads special issues and topical collections on AI in engineering. He leads the High-value Manufacturing research group at Cardiff University, focusing on digital transformation in manufacturing. His team works on projects involving digital twins, knowledge graphs, and AI-driven design innovation, often in collaboration with international institutions.

Alvaro Torralbaمشاهده پروفایل

دانشیار

• Symbolic Search
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Alvaro Torralba is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with the Technical Faculty of IT and Design. His research focuses on symbolic search, heuristic functions, and planning algorithms within artificial intelligence and machine learning. Notable projects include the ConAn initiative exploring contrastive analysis for state-space exploration. He has contributed extensively to classical planning, probabilistic planning, and automated planning competitions, earning awards such as the First Prize in the Agile Track of the 10th International Planning Competition (IPC’23). His work often bridges theoretical advancements with practical applications, including game-based network update synthesis and believable non-player character development. Research outputs include over 60 publications since 2011, with a focus on optimizing search algorithms and enhancing planning efficiency through techniques like operator-potential heuristics and bidirectional search strategies. His scientific contributions span algorithmic innovation, verification methodologies, and large-scale abstraction evaluation. Collaborations and datasets include foundational work on PDDL generators and pattern databases, with open-access resources available via Zenodo. As a program committee member and award-winning researcher, Torralba actively contributes to advancing the frontiers of AI planning and decision-making systems.

• Computer Science
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Yang Cao is a Professor at the University of Science and Technology of China , Department of Automation, Hefei, China. He holds a PhD from Northeastern University (2004, Shenyang, China) and has active affiliations with institutions like Virginia Tech and Huazhong University of Science and Technology. Research Focus: Spatiotemporal modeling, event-based vision, 3D human-object interaction, and industrial defect detection. Publications: 15 recent articles highlight his work in diffusion models, transformers, and state-space networks for tasks like traffic emission imputation, eye tracking, and PCB defect detection. Collaborative Work: Co-authored with Zheng-Jun Zha, Wei Zhai, Yu Kang, and others in journals like IEEE Transactions on Neural Networks and CVPR Workshops. Scientific Contributions: His research bridges computer vision, machine learning, and industrial applications, emphasizing real-world challenges such as low-light enhancement and sensor fusion.

Benjamin C. Pierceمشاهده پروفایل

استاد

• Programming Languages
• Type Systems
• Formal Verification
• +۳ مورد دیگر

Benjamin C. Pierce is Henry Salvatori Professor of Computer and Information Science at the University of Pennsylvania, with appointments in the School of Engineering and Applied Science. A Fellow of the ACM, his research spans programming languages, formal verification, and security-privacy technologies. He directs the DeepSpec project on verified systems infrastructure and leads climate computing initiatives. Research interests focus on: Formal methods for reliable software via proof assistants like Coq Bidirectional programming and data synchronization Language-based security and differential privacy Publication trends show consistent contributions to type theory foundations, with recent emphasis on property-based testing methodologies and real-world verification. Articles frequently appear in top PL/SEC venues with practical applications in compilers and secure systems. Scientific Awards: ACM Fellow (systems verification) SIGPLAN Distinguished Educator Award (textbook innovations) Advises graduate students through the Penn PL Club. PI for NSF Expeditions in Sustainable Computing. Leads the VERSE project for verified C code and Unison file synchronizer. Directs the Penn Programming Languages Research Group collaborating with industry partners including Amazon and Microsoft Research.

Ewelina Rupnikمشاهده پروفایل

پژوهشگر

• Photogrammetry
• Pose Estimation
• Image-based 3D Reconstruction
• +۷ مورد دیگر

Ewelina Rupnik is a prominent researcher in photogrammetry and remote sensing, currently holding a researcher position at the Laboratory on Geographic Information Science (LaSTIG) at the French National Institute of Geographic and Forest Information (IGN) since 2017. She also serves as an associate researcher at the Paris Institute of Earth Physics (IPGP). Rupnik has established herself as a leading expert in historical imagery processing, neural radiance fields, and bundle adjustment techniques. Her educational background includes a PhD in photogrammetry from the Vienna University of Technology (2015), an MSc in Engineering in Photogrammetry from AGH University of Science and Technology, Poland (2005-2010), and an Erasmus exchange at the Technische Universitaet Muenchen, Germany (2009/2010). She recently completed her Habilitation from Université Gustave Eiffel in June 2025. Rupnik's research focuses on advancing photogrammetric techniques for processing historical imagery, developing novel neural radiance field approaches for satellite imagery, and improving bundle adjustment methodologies. Her work bridges traditional photogrammetry with modern deep learning techniques, particularly in the context of sparse satellite views and historical multi-epoch imagery. She has made significant contributions to the open-source MicMac photogrammetry software project. Her recent publications demonstrate a strong trend toward integrating deep learning with traditional photogrammetric methods, with a particular emphasis on satellite and historical imagery analysis. The research spans from fundamental algorithm development (like SparseSat-NeRF and Pointless Global Bundle Adjustment) to practical applications in earth sciences (landslide, earthquake, and glacier volume mapping). 2022 EuroSDR PhD Award for Corona satellite imagery processing Best Paper Award for BRDF-NeRF research Outstanding Reviewer at CVPR 2025 Rupnik actively contributes to the academic community through editorial and leadership roles, including serving as Editor-in-Chief of the French Journal for Photogrammetry and Remote Sensing (2021-2025), Advisory Board Member of the International Journal of Photogrammetry and Remote Sensing (2024-present), and Co-chair of the ISPRS Working Group on Image Orientation and Sensor Fusion (2022-2026). She regularly teaches at Université Paris Cité & ENSG (~30 hours/year since 2015) and has conducted numerous workshops worldwide on photogrammetry with historical images and MicMac software.

Farzaneh Bagheriمشاهده پروفایل

استادیار

• Power Electronics
• Control Systems
• Power Systems
• +۳ مورد دیگر

Farzaneh Bagheri is an active Assistant Professor in the Department of Electrical and Electronics Engineering at Antalya Bilim University, Turkey, since 2021, following her Research Assistant role at the same institution in 2019. She holds a Ph.D. from Eastern Mediterranean University (2019), M.Sc. from Azarbaijan Shahid Madani University (2010), and B.Sc. from Shahid Beheshti University (2005), all in Electrical and Electronics Engineering. As an IEEE and Industrial Electronics Society (IES) member, she serves as a regular reviewer for IEEE, Elsevier, and MDPI journals. Her educational background demonstrates a consistent focus on power engineering: Ph.D. in Electrical and Electronics Engineering, Eastern Mediterranean University, Cyprus (2019) M.Sc. in Electrical and Electronics Engineering, Azarbaijan Shahid Madani University, Iran (2010) Bachelor's in Electrical and Electronics Engineering, Shahid Beheshti University, Iran (2005) Research interests center on power electronics control systems with emphasis on power inverter control , microgrid stability , renewable energy management , and laboratory validation . Her work bridges theoretical control design with industrial applications, particularly in grid-tied systems for solar and wind energy conversion under unstable conditions. Publication trends (2021–2025) reveal deep specialization in sliding mode control variants applied to photovoltaic inverters, dynamic voltage restorers, and battery chargers. Key themes include chattering reduction, grid distortion resilience, and multi-level converter topologies for renewable integration, with increasing focus on AI-driven fault diagnosis and digital twin modeling in her 2025 output. Scientific awards are not explicitly listed in the source material. She contributes to European and national research/industrial projects in power systems and power electronics, though specific grant details are omitted. No student advising roles are documented, but her faculty position suggests graduate mentorship responsibilities. Laboratory validation work implies hands-on experimental leadership. Her IEEE/IES membership and journal reviewing activities indicate active participation in professional communities. Experimental research is conducted within power electronics laboratories, with recent projects emphasizing solar plant integration and AI maintenance tools.

Shan Chenمشاهده پروفایل

استادیار

• Cryptography
• Information Security
• Computer Science
• +۲ مورد دیگر

Shan Chen is an Assistant Professor at the Southern University of Science and Technology (SUSTech) , Shenzhen, China, with research expertise in Cryptography and Information Security , particularly focused on real-world applications and secure protocols. Ph.D. in Computer Science , Georgia Institute of Technology (2020) MEng in Computer Science and Technology , Tsinghua University (2014) BSc in Mathematics and Applied Mathematics , Beijing Normal University (2011) His research addresses practical challenges in cryptographic protocol design, including security analysis of TLS 1.3 and QUIC, causality preservation in secure messaging, and committing authenticated encryption. Key trends include improving protocol efficiency while maintaining provable security against real-world adversaries. He leads the Applied Cryptography Group and teaches courses like Algorithm Design and Analysis and Discrete Mathematics . Contact: chens3@sustech.edu.cn

• Power Electronics
• Digital Signal Control
• Electric Mobility
• +۱۲ مورد دیگر

Vitor Duarte Fernandes Monteiro is a Senior Researcher and Invited Professor at the Industrial Electronics Department of the School of Engineering, University of Minho, Portugal. He is a member of the IE R&D Group at Centro ALGORITMI, where he conducts research in power electronics and energy systems. His work focuses on the intersection of power electronics, renewable energy integration, and electric mobility. Dr. Monteiro received his Ph.D. in Power Electronics and Energy Systems in 2016 and his M.Sc. in Industrial Electronics and Computer Engineering in 2010, both from the University of Minho, Portugal. His research interests span a wide range of topics in power electronics and energy systems, with particular focus on Power Electronics Converters, Digital Signal Control, Electric Mobility, Renewables, Hybrid AC/DC Grids, Power Quality, Power Conditioners, Solid-State Transformers, Energy Efficiency, Wireless Power Transfer, Railway Systems, Energy Storage Systems, and Smart Grid applications. His work emphasizes practical implementation and experimental validation of novel power electronic solutions for modern energy challenges. Analysis of Dr. Monteiro's recent publications (2023-2025) reveals a strong focus on advanced power converter topologies for renewable energy integration, electric vehicle charging infrastructure, and smart grid applications. His research shows a clear trend toward unified power quality solutions, bidirectional power flow control, and innovative approaches to hydrogen energy systems. The interdisciplinary nature of his work bridges traditional power electronics with emerging applications in transportation electrification and smart city infrastructure. Dr. Monteiro serves in several editorial capacities, demonstrating recognition by his peers: Associate Editor of the Journal IET Power Electronics Associate Editor of the Journal IEEE Latin America Transactions Topic Editor of the Journal MDPI Electronics Editorial Board Area Editor of the Journal EAI Endorsed Transactions on Energy Web Associate Editor of the IEEE Transportation Electrification Community eNewsletter Guest Editor for multiple journals including IET Power Electronics, Sustainability, and Energies As a Senior Researcher at Centro ALGORITMI, Dr. Monteiro leads research projects focused on power electronics applications for energy systems. His work involves close collaboration with industry partners and participation in European research initiatives. He mentors junior researchers and contributes to the development of innovative power electronic solutions with real-world applications. Dr. Monteiro is actively involved with the Group of Energy and Power Electronics (GEPE) at the University of Minho, where he contributes to both research and educational activities. His work with GEPE focuses on experimental validation of novel power electronic converters and their application to modern energy challenges including renewable integration, electric mobility, and smart grid technologies.

Longbing Caoمشاهده پروفایل

استاد

• Data Science
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Professor Longbing Cao serves as a Professor at University of Technology Sydney (UTS) in the Faculty of Engineering and Information Technology, specifically within the Data Science Institute. He also holds the position of Distinguished Chair Professor in AI at Macquarie University and is an ARC Future Fellow (Level 3). As a pioneering researcher in AI, data science, and advanced analytics, Professor Cao founded the UTS Advanced Analytics Institute, the first data science initiative in Australia. Professor Cao's research interests span across data science fundamentals, machine/deep learning, behavior informatics, and enterprise data science applications. His work bridges the gap between theoretical research and practical implementation, focusing on non-IID learning, actionable knowledge discovery, and complex behavior modeling. His research has addressed real-world challenges in government services, finance, insurance, banking, telecommunications, transport, and e-commerce sectors. His 15 most recent publications reveal a strong trend toward addressing distributional challenges in machine learning, developing transdisciplinary AI approaches, modeling complex temporal dependencies, and advancing negative sequence analysis. His work consistently integrates theoretical foundations with practical applications, particularly in financial analytics, healthcare, and disaster resilience. Scientific Awards: Eureka Prize for Excellence in Data Science (2019) ACM Distinguished Scientist Professor Cao has made significant contributions to academic leadership and research supervision. He established world-first research degrees at UTS (Master of Analytics and PhD Thesis: Analytics), founded the IEEE Task Force on Data Science and Advanced Analytics, and served as general chair of the KDD conference in 2015 (the first edition in Australia). His funded research portfolio includes multiple ARC grants and industry collaborations focusing on complex data analytics, behavior informatics, and AI applications. He leads the Data Science Lab at UTS, which has become a prominent center for data science research in Australia. The lab focuses on developing fundamental theories and practical applications of data science, with strong industry partnerships that translate research into real-world impact. Professor Cao's leadership in establishing the annual Big Data Summit in 2012 created Australia's first platform for bridging academic research with industry and government applications.

Zhenjiang Huمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Functional Programming
• +۷ مورد دیگر

Zhenjiang Hu is a Chair Professor and Dean of the School of Computer Science at Peking University. He serves as Director of the Programming Languages Laboratory and has held significant academic positions including Professor at the National Institute of Informatics and University of Tokyo. BS and MS from Shanghai Jiaotong University (1988, 1991) PhD from University of Tokyo (1996) Lecturer/Assistant Professor at University of Tokyo (1997) Associate Professor at University of Tokyo (2000) Full Professor at National Institute of Informatics (2008) Full Professor at University of Tokyo (2018-2019) Professor Hu's research primarily focuses on programming languages and software engineering, with special emphasis on functional programming, bidirectional transformation, and software adaptation. His work explores transformational programming approaches for automatic program optimization, systematic parallelization of sequential programs, efficient manipulation of structured documents, and bidirectional model transformation for software development. His research has significantly advanced the field of bidirectional programming, developing foundational theories and practical applications that enable more reliable and maintainable software systems. His recent publications demonstrate a strong trajectory in bidirectional programming, program synthesis, and graph processing. The research shows increasing sophistication in handling program transformations, with growing emphasis on practical applications in software engineering contexts. His work increasingly integrates formal methods with practical programming language design, creating systems that maintain theoretical soundness while addressing real-world software development challenges. The research spans multiple venues including top conferences like PLDI, POPL, ICFP, and OOPSLA, reflecting its broad impact across programming language research. Fellow of JFES (Japan Federation of Engineering Society, 2016) ACM Distinguished Scientist (2016) Member of Academia Europaea (2019) IEEE Fellow (2020) Member of Engineering Academy of Japan (2020) Professor Hu actively mentors students and has welcomed excellent candidates to join his group through Peking University's International Elite PhD Program and Boya Postdoctoral Fellowship Program. He serves on numerous program committees for major conferences including PLDI, POPL, ICFP, and OOPSLA, and holds editorial positions for prestigious journals such as Journal of Functional Programming and Science of Computer Programming. His leadership extends to conference organization, having served as PC Chair for CNCC 2024 and General Co-Chair for SoICT 2019. As Director of the Programming Languages Laboratory at Peking University, Professor Hu leads a research team focused on advancing programming language theory and practice. His lab has developed influential frameworks like BiGUL for bidirectional programming and Fregel for graph processing. The laboratory maintains strong international collaborations and contributes to both theoretical foundations and practical implementations in programming languages and software engineering.

Xing Zhangمشاهده پروفایل

پژوهشگر

• Bidirectional Programming
• Live Programming
• Object-Oriented Programming
• +۳ مورد دیگر

Xing Zhang is a researcher at Peking University specializing in bidirectional programming paradigms and live programming systems. Their work bridges programmatic and direct manipulation approaches, focusing on object-oriented and functional programming environments. Research interests span: Bidirectional Program Transformation Live Programming Environments Direct Manipulation Interfaces Interactive Code Development Software Engineering Tools Language Design for Incremental Computation Key contributions include: 2024: PLDI Artifact Evaluation Committee member 2023: OOPSLA paper on bidirectional object manipulation 2023: LazyBiEval system for partial program updates 2022: ICSE work on incomplete program handling GitHub projects demonstrate prototype implementations of bidirectional programming systems, including BiOOP and FuseDM frameworks.

Simon Beckمشاهده پروفایل

پژوهشگر

• Wireless Power Transfer
• Wireless Communication
• Power Electronics
• +۲ مورد دیگر

Simon Beck is a PhD researcher at the Laboratory for High Power Electronic Systems (ETH Zürich) , focusing on Wireless Power Transfer and Power Electronics . He received his BSc (2014) and MSc (2017) in Electrical Engineering from ETH Zürich, where he designed high-precision PWM schemes for modular multilevel converters in his Master's thesis. Born in Vaduz, Liechtenstein (1992) PhD research since 2021 on wireless energy transfer systems Co-founded an ICT company in Vaduz (2017), developing ERP/CRM applications and managing ISP-grade networking infrastructure His publications include studies on bidirectional converter topologies, modular converter communication schemes, and voltage precision optimization, presented at conferences like ECCE Europe and EPE'22 . Collaborations with Jürgen Biela and Simon Fuchs highlight his work in high-efficiency power electronic systems for railway and wireless charging applications.