جستجوی استاد راهنمای دانشگاهی

Ichiro Takeuchi is an Affiliate Professor at the University of Maryland, specializing in materials science and engineering with a strong focus on autonomous materials discovery and machine learning integration. He leads research in phase-change materials, elastocaloric cooling systems, and high-throughput experimentation platforms. His work bridges theoretical physics, computational methods, and experimental material synthesis. Key research areas include developing AI-driven tools for materials design, optimizing phase-change-based photonic devices, and advancing sustainable cooling technologies through elastocaloric effects. He pioneers automated platforms like the JARVIS-Leaderboard and SANE optimization frameworks, enabling rapid discovery of novel materials for energy and electronics applications. Takeuchi’s contributions span interdisciplinary collaborations, integrating neutron diffraction, scanning probe microscopy, and multi-modal data analysis. His group’s innovations in reconfigurable photonics and combinatorial library screening have positioned him as a leader in next-generation materials engineering.

• Materials Science
• Machine Learning in Materials Discovery
• Phase-Change Materials
• +۷ مورد دیگر

Dr. Jacob Taylor is an Adjunct Professor at the University of Maryland and a Fellow at the Joint Quantum Institute (JQI) and the National Institute of Standards and Technology (NIST). His research focuses on quantum information science, dark matter detection, and the development of quantum sensors. Taylor leads the Taylor Research Group, which explores mechanical quantum sensing, quantum computing applications, and gravitational interactions. He has advised numerous graduate students, including Prabin Adhikari, Andrew Glaudell, and Haitan Xu, and collaborates with postdoctoral researchers such as Vanita Srinivasa and Minh Tran. His work spans theoretical and experimental domains, with notable contributions to dark matter detection methodologies, including proposals for ultraheavy dark matter searches using mechanical pendulums and optomechanical sensors. Taylor has also pioneered quantum computing automation techniques, leveraging machine learning to optimize quantum dot systems. His research has been recognized with prestigious awards, including the 2020 Department of Commerce Gold Medal for expanding U.S. leadership in quantum information science. In recent years, Taylor's team has published extensively on topics like backaction-evading receivers, cavity-mediated spin qubit entanglement, and pressure sensing via atomic collisions. These studies highlight his interdisciplinary approach, blending quantum mechanics, engineering, and computational methods. His laboratory work emphasizes both fundamental physics and practical applications, such as improving cryogenic systems for dark matter experiments like DarkSide-20k. Awards: Department of Commerce Gold Medal Award (2020) Grants and Funding: Supported by NIST and DOE projects in quantum sensing and dark matter detection Lab Affiliations: Taylor Research Group (JQI), QuICS (Quantum Information and Computer Science)

• Quantum Information Science
• Dark Matter Detection
• Quantum Sensors
• +۳ مورد دیگر

Eyad H. Abed is a Professor of Electrical and Computer Engineering at the University of Maryland, College Park, affiliated with the Institute for Systems Research (ISR). He has held leadership roles, including Director of ISR (2002–2008) and Dean of the College of Information Technology at UAE University (2009–2012). His research focuses on control theory, electric power systems, and complex networks. He has been a Program Director at NSF (2014–2017) and is an IEEE Fellow (2001). Education: S.B. in Electrical Engineering, MIT (1979) M.S. and Ph.D. in Electrical Engineering, UC Berkeley (1981, 1982) Research Interests: System and control theory, electric power dynamics, aerospace control, nonlinear dynamics, bifurcation control, and complex networks (communication/social). Key Contributions: Developed bifurcation control approaches, guardian map stability analysis, and modal participation theory. Applied control theory to power systems, internet protocols, and aerospace systems. Awards: NSF Presidential Young Investigator (1987) O. Hugo Schuck Best Paper Award (1994) IEEE Fellow since 2001 Advising & Grants: Advised students like Van Sy Mai and P. Ranjan. Contributed to NSF-funded research and editorial roles in IEEE Transactions on Automatic Control and Nonlinear Dynamics. Labs/Teams: Collaborated with ISR and UMD teams on projects involving power systems, control algorithms, and nonlinear dynamics.

• System and control theory
• Electric power system dynamics
• Aerospace control systems
• +۴ مورد دیگر

Dr. Gareth Conway is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, associated with the Institute of Electronics, Communications & Information Technology (ECIT). His research focuses on wearable and implantable antennas, wireless medical sensors, and electromagnetic propagation for healthcare applications. He holds over 40 publications and five antenna-related patents, with industry collaborations enhancing wearable system performance. Awards include the 2014 Early Career Researcher Impact Prize and the Mobile World Scholar Award (2018). Education: PhD from Queen's University Belfast (2005-2008) Roles: Research & Development Engineer at Wireless Fibre Technologies (2008-2011) Research Fellow at QUB (2011-2013) Senior Lecturer at ECIT (2013-present) Research Interests: Wearable/implantable antennas, human tissue-physics modeling, printable microwave materials, wireless medical sensors, and computational electromagnetism for body-centric networks. His work aligns with UN SDG 3 (Good Health) and SDG 9 (Industry/Innovation). Key Projects: EPSRC grant EP/P000983/1 (implantable antenna repeaters), KTP project with Creagh Concrete (sensor-based concrete production). He organizes conferences like the All-Ireland Workshop on Wearable/Implantable Antennas. Grants/Awards: QUB Vice Chancellor's Early Career Researcher Impact Prize (2014) Mobile World Scholar Award (2018) Award for Sensor-based Digitisation in Concrete Production (2022) Students: Supervised 3 PhD students (e.g., on implantable antennas, frequency-selective surfaces, and wearable identification systems). Labs/Teams: Centre for Wireless Innovation at ECIT, collaborating with industry partners like Sensata Technologies.

• Antenna Design
• Wireless Medical Sensors
• RF/Microwave Devices
• +۴ مورد دیگر

Edoardo Patti is an Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He is actively involved in research and teaching, focusing on artificial intelligence, machine learning, IoT, smart grids, energy communities, co-simulation, and digital twin technologies. He is a member of the EDA (Electronic Design Automation) research group and the Interdepartmental Center IAM@PoliTo for Integrated Additive Manufacturing. His research interests span Artificial Intelligence, Machine Learning, Internet of Things, Smart Grids, Energy Communities, Co-simulation, Distributed Software Infrastructure, Digital Twin, Physics-Informed Neural Networks, and Reinforcement Learning . His work is closely aligned with Sustainable Development Goals such as Affordable and Clean Energy (Goal 7), Sustainable Cities (Goal 11), and Climate Action (Goal 13). The latest publications reveal a strong trend in AI-driven modeling for energy systems, including digital twins for wave energy converters, urban electric mobility simulation, real-time battery health estimation, and co-simulation platforms for integrated energy systems. His work combines machine learning with physical models and large-scale distributed systems to address sustainability challenges. He supervises several PhD students, including Maria Adelaide Loffa, Matia Torlini, Rafael Natalio Fontana Crespo, Pietro Rando Mazzarino, Claudia De Vizia, and Marco Massano. He has led numerous research projects funded by EU (H2020), PNRR, regional initiatives, and corporate contracts, particularly in additive manufacturing, smart grids, and IoT platforms. He is involved in multiple research groups and centers: EDA - Electronic Design Automation (DAUIN) Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +۱۳ مورد دیگر

Andrea Calimera is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is actively involved in teaching and research, contributing to doctoral programs and undergraduate and graduate courses in computer engineering and data science. Full Professor (L.240), Polytechnic University of Turin Department of Control and Computer Science (DAUIN) Member, SmartData@PoliTO - Big Data and Data Science Laboratory Member, College of Computer, Film and Mechatronics Engineering His research interests center on electronic design automation, energy-efficient electronic systems, and low-power design, with strong connections to artificial intelligence, embedded systems, and IoT. His work bridges hardware and software optimization for intelligent edge devices. The recent publications (2023–2025) reflect a focused trend on federated learning, secure and efficient AI deployment on edge devices, and low-power embedded systems. Topics include robust evaluation in federated learning, resource management under label skew, homomorphic encryption for private tensor operations, pipeline optimization for keyword spotting, and side-channel attacks via DVFS for neural network fingerprinting—highlighting expertise in both performance and security of AI systems on constrained hardware. Andrea Calimera supervises PhD and master's students and leads research projects funded by competitive and commercial grants. He has contributed to national and international patents on low-power depth estimation and single-image signal processing. Scientific Director, SENSEI Project (2017–2019): Energy-efficient machine learning on chip for IoT Scientific Director, Commercial Project (2020–2022): Design tools for AI on energy-efficient embedded mobile devices Supervision of PhD student Erich Malan (ongoing, since 2022) on distributed and federated learning over IoT networks Supervision of Bachelor's student Chen Xie (2020–2024) on synthesis of smart sensors He teaches courses such as High-Level Synthesis (PhD), Synthesis and Optimization of Digital Systems, Machine Learning for IoT, and Efficient Computing for Artificial Intelligence across Computer Engineering and Data Science programs. His research group is EDA - Electronic Design Automation (DAUIN), which focuses on hardware-software co-design for intelligent systems.

• Electronic Design Automation
• Energy Efficient Electronic Systems
• Low Power Design
• +۱۲ مورد دیگر

Martin Marie Hubert Choux is an Associate Professor at the Department of Engineering Sciences , University of Agder, Norway. He holds dual M.Sc. degrees in Mechatronic Engineering from École Nationale Supérieure d'Art et Métiers (France) and University of Queensland (Australia), and a Ph.D. in Automatic Control from Technical University of Denmark (2011). Education: M.Sc. in Mechatronic Engineering, École Nationale Supérieure d'Art et Métiers, Paris, 2006 M.Sc. in Mechatronic Engineering, University of Queensland, Brisbane, 2006 Ph.D. in Automatic Control, Technical University of Denmark, Copenhagen, 2011 His research focuses on mechatronics , robotics , and battery recycling , with over 15 recent publications (2024–2019) on: Automated Disassembly of lithium-ion batteries Fault Diagnosis in motor drives using structural analysis and neural networks Efficiency Optimization of electric drivetrains in offshore applications Comparative Studies of hydraulic vs. electric actuation systems AI and Robotics for EV battery recycling Control Algorithms for mechanical systems His work spans robotics , automatic control , and sustainable engineering , contributing to electric vehicle and offshore technology advancements.

• Mechatronics
• Robotics
• Automatic Control
• +۴ مورد دیگر

Olaf Schenk is a Professor at the Institute of Computing within the Faculty of Informatics at Università della Svizzera italiana (USI), Switzerland. He serves as Director of the Institute of Computing and Co-Director of the Master in Computational Science. He is also an adjunct member of the Computer Systems Institute at USI. PhD in Information Technology and Electrical Engineering, ETH Zurich (2001) Venia Legendi in Mathematics and Computer Science, University of Basel (2009) Applied Mathematics, Karlsruhe Institute of Technology (KIT), Germany His research focuses on high-performance computing , computational science and engineering , and applied algorithms for extreme-scale simulations. He bridges computer science with scientific computing needs, particularly in parallel algorithms , sparse solvers , graph analytics , and manycore architectures . His work emphasizes scalable software tools and programming models for emerging HPC systems. The 15 most recent publications reflect a consistent focus on sparse matrix computations , parallel and task-based algorithms , graph partitioning , and performance optimization for heterogeneous and manycore systems. Keywords span high-performance computing, numerical linear algebra, and large-scale data analysis, showing strong integration of theoretical algorithm design with practical implementation. Olaf Schenk has received several prestigious honors: Elected Fellow, Society for Industrial and Applied Mathematics (SIAM) Senior Member, IEEE and ACM SIAM Supercomputing Prize 2023 IBM Faculty Award Two Leadership Computing Awards from the U.S. Department of Energy He has held leadership roles as Chair, Vice Chair, and Program Director of the SIAM Activity Group on Supercomputing. He serves as Associate Editor for ACM Transactions on Mathematical Software and on the editorial board of SIAM Journal on Scientific Computing . He has participated in over 60 international program committees, including top-tier conferences such as SC, IPDPS, and IEEE CSE. He advises PhD and Master’s students in computational science and leads research projects funded by national and international agencies. He is also the Founder & Director of Panua Technologies Sagl, focusing on high-end software for simulation and optimization. His research group at USI works on next-generation computing tools for extreme-scale scientific simulations, with ongoing work in adaptive algorithms, resilience, and hybrid CPU-GPU computing. He leads collaborative projects with institutions in Europe and the U.S., aiming to develop scalable, robust, and efficient software for future exascale systems.

• High performance computing
• Computational Science and Engineering
• Scientific computing
• +۷ مورد دیگر

Prasad Enjeti is a Professor and Texas Instruments Jack Kilby Chair in Electrical & Computer Engineering at Texas A&M University, College of Engineering. With expertise in power electronics and renewable energy systems, he has significantly advanced grid-connected technologies, energy storage, and power quality solutions. Ph.D., Electrical Engineering, Concordia University (1988) M.S., Electrical Engineering, I.I.T. Kanpur (1982) B.S., Electrical Engineering, Osmania University (1980) His research focuses on power electronic converters for renewable energy integration, solid-state transformers, high-temperature power systems, grid-edge intelligence, and cybersecurity in distributed energy systems. He has pioneered innovations in AC/DC microgrids, droop control, and advanced filtering technologies. Recent publications emphasize cybersecurity for renewable systems, wide-bandgap semiconductor applications, and AI-driven power electronics optimization. He holds 20+ patents and has supervised 29 Ph.D. and over 50 Master's students, many now in leading academic and industrial positions. IEEE Fellow (2000) R. David Middlebrook Technical Achievement Award (2012) Best Paper Awards at PCIM (2014), IEEE IAS IPCC (2003, 2002, 1998, 1996) NSF Research Initiation Award (1990) Texas A&M Faculty Fellow (1996-97, 2001) He leads the Power Electronics Intelligence at the Network Edge (PINE) research group, with significant contributions to eVTOL energy systems, cryptocurrency mining load analysis, and secure peer-to-peer energy transactions.

• Power Electronics
• Renewable Energy Systems
• Smart Grid Technologies
• +۳ مورد دیگر

Assoc. Prof. Dr. Kadir Vardar is an Associate Professor at the Department of Electrical and Electronics Engineering, Faculty of Engineering, Dumlupınar University. He has held academic and administrative roles since 2012, including Vice President of Department (2015–2019). His research focuses on power electronics, embedded systems, renewable energy, and neural network applications in control systems. Education: BSc (2001) and MSc (2004) from Dumlupınar University; PhD (2011, English Program) from Dokuz Eylül University. Projects: Over 15 projects, including TÜBİTAK-funded initiatives on smart home automation, PV inverters, and embedded HIL simulators. Awards: 2011 Dokuz Eylül University Doctoral Publication Honor Award; 2001 Department First Place at Dumlupınar University. Research interests span power electronics (inverters, active filters), renewable energy systems (PV), and embedded systems (STM32, microcontrollers). He has published 29 articles and supervised multiple theses. Current courses include Power Electronics, Advanced Microcontrollers, and System Programming.

• Power Electronics
• Embedded Systems
• Renewable Energy Systems (PV)
• +۳ مورد دیگر

Dr. Hendra I Nurdin is a Senior Lecturer in the School of Electrical Engineering and Telecommunications at the University of New South Wales (UNSW), where he has been a faculty member since 2012. His academic background spans Electrical Engineering and Applied Mathematics with a focus on systems and control theory, with significant research intersections in quantum physics and power engineering. He serves as an Associate Editor for IEEE Control Systems Letters (IEEE L-CSS) starting from January 2024. Dr. Nurdin's research spans quantum systems and control, nonlinear control of microgrids, and neuromorphic computing for nonlinear systems. His work in quantum control intersects with quantum physics while his research on microgrid control intersects with power engineering. His research has resulted in numerous publications across prestigious journals including Nature Communications, Physical Review Research, IEEE Control Systems Letters, and IEEE Transactions on Automatic Control. His recent publications (2020-2025) predominantly focus on quantum reservoir computing, quantum parameter estimation, control of non-Markovian quantum systems, and applications of control theory to energy systems. The research demonstrates a clear trajectory toward practical implementations of quantum computing concepts and advanced control methodologies for both quantum and classical systems. Associate Editor for IEEE Control Systems Letters (IEEE L-CSS) from January 2024 Dr. Nurdin has supervised several PhD students to completion and currently mentors PhD candidate Wen Liu. His research group has produced significant work in quantum control systems, with former students including Wenxing Li, Yihuan Liao, Jiayin Chen, Jiacheng Li, Muhammad Ali, Zhan Shi, and Onvaree Techakesari. He actively seeks new students with strong academic backgrounds for research in his areas of interest, particularly in quantum systems and control. His laboratory work focuses on quantum systems control, quantum reservoir computing, and microgrid control systems. He has developed courses including ELEC9782 Special Topics in Electrical Engineering 2 (Quantum Control) and teaches ELEC4631 Continuous-Time Control System Design.

• Quantum Control
• Quantum Systems
• Systems Theory
• +۱۰ مورد دیگر

Federico Ciccozzi is an Associate Professor in Computer Science at Mälardalen University's School of Innovation, Design and Engineering, where he leads the ASSO research group and the VR ORPHEUS project. He also serves as Head of Research Education in Computer Science and Electronics at the university. His academic journey includes a M.Sc. in Global Software Engineering (via the GSEEM program) and a Ph.D. in Computer Science and Engineering from Mälardalen University (2014), followed by promotion to Docent (Associate Professor) in 2017. Education: M.Sc. in Global Software Engineering (GSEEM program, joint between Mälardalen, L'Aquila, and Amsterdam) Ph.D. in Computer Science and Engineering (Mälardalen University, 2014) Docent (Associate Professor) in Computer Science (Mälardalen University, 2017) His research focuses on model-driven engineering, robotics software engineering, and software architecture. He has pioneered work in blended modeling approaches, EAST-ADL extensions, and formal verification of complex systems, particularly in robotics and automotive domains. Recent projects emphasize industrial collaborations, such as optimizing ROS2 multi-robot systems and enhancing safety-critical software through model-based methodologies. Research Contributions: Developed frameworks for transforming surface languages into augmented EAST-ADL models Advanced blended modeling techniques across JetBrains MPS and Eclipse tools Examined consistency management in industrial model-driven development Edited special issues on model-driven engineering and low-code development His work bridges academic innovation and industrial practice, with notable projects like the Rubus Component Model for vehicular systems. He actively organizes workshops (e.g., RoSE, ASYDE) and contributes to standardization efforts like the Portable Test and Stimulus Standard. Labs/Teams: Leads the ASSO research group, focusing on advanced software engineering methodologies and robotics systems development.

• Model-Driven Engineering
• Robotics Software Engineering
• Software Architecture
• +۳ مورد دیگر

Georgia Dede is an Assistant Professor at the Department of Informatics and Telematics, School of Digital Technology, Harokopio University of Athens. Her expertise lies in evaluating systems and electronic services, with a focus on cybersecurity, telecommunications, and operations research. She holds a PhD from National and Kapodistrian University of Athens (2015), a Master’s in Management and Economics of Telecommunications Networks (2007), and an undergraduate degree in Informatics and Telematics (2005). Education: PhD: Decision Making Methods and Uncertainty Study (2015), National and Kapodistrian University of Athens Master’s: Management and Economics of Telecommunications Networks (2007), National and Kapodistrian University of Athens Bachelor’s: Informatics and Telematics (2005), National and Kapodistrian University of Athens Research Interests: Georgia’s research spans cybersecurity frameworks, pairwise comparison methodologies for decision-making, and economic modeling of telecommunications infrastructure. She explores topics like resilient IoT systems, AI applications in governance, and competitive dynamics in energy and telecom markets. Her work integrates technical and socio-economic perspectives to address challenges in network security, service evaluation, and policy design. Grants and Projects: Leading and participating in EU-funded programs under Horizon Europe and Digital Europe initiatives Prior roles as senior advisor/administrator at Netcompany Intrasoft and ENISA Labs/Teams: Her involvement in projects at Harokopio University and collaborations with institutions like the University of Patras emphasize applied research in digital technology and policy innovation.

• Cybersecurity
• Telecommunications
• Operations Research
• +۵ مورد دیگر

Christian Fibich is a Researcher and Lecturer at the Department of Electronic Engineering, University of Applied Sciences Technikum Wien, Austria. He leads the Research Group Embedded Systems, focusing on FPGA reliability and high-level synthesis. His roles include project management for R&D initiatives like VECS (2013-2018), INES (2018-2023), and the 2024 Drohnentechnik integration project. Fibich holds an MSc in Embedded Systems from Technikum Wien and has been active in the field since 2010. Research interests include fault-tolerant FPGA design, reliability analysis of SRAM-based FPGAs, and high-level synthesis optimization. His work emphasizes practical applications of open-source tools and automated design exploration. Recent projects explore temperature-dependent fault effects and drone integration in academic programs. Publications span FPGA reliability, fault injection methods, and embedded systems design, with a focus on open-source IP cores and hardware security. His contributions include Fiji (a fault injection tool) and HLShield (a reliability framework for HLS).

• Fault-Tolerant FPGA Design
• Reliability Analysis of SRAM-Based FPGAs
• High-Level Synthesis

Thomas Spyrou is an Assistant Professor in the Department of Product and Systems Design Engineering at the University of the Aegean. He holds a Physics degree from the National and Kapodistrian University of Athens and a PhD in Decision Support Systems - Artificial Intelligence from the University of the Aegean. His research focuses on Information Systems, Design Methodologies, and Sustainability, with an emphasis on Decision Support Systems, Simulation, and Cybernetics. Key affiliations include the Department of Product and Systems Design Engineering at the University of the Aegean, where he has contributed to curricula development and interdisciplinary projects. His work spans design theory, digital tools for art and sustainability, and systems thinking applied to creative processes. Research interests include Design Support Systems, Biomimetic Service Design, and the integration of tacit knowledge into design frameworks. His recent projects involve tools like DDArtS for street art creation and Spyractable for tangible user interfaces. Over 50 publications highlight his contributions to design, technology, and cybersecurity.

• Information Systems
• Design Methodologies
• Product and Systems Design Engineering
• +۷ مورد دیگر