جست‌وجوی استاد و پژوهشگر

Henrik Gordon Petersenمشاهده پروفایل

استاد

• Robotics
• Robot Manipulation
• Actuator Engineering
• +۴ مورد دیگر

Henrik Gordon Petersen is a Professor at the Maersk Mc-Kinney Moller Institute within the University of Southern Denmark (SDU), where he is a leading figure in SDU Robotics. With a prolific research output of 86 publications and active involvement in 14 projects including the major MADE REACT initiative (100 million DKK), Petersen's work centers on advancing robotic systems for industrial automation and sustainable production. His expertise spans robot engineering, actuator design, and computer vision with 100% fingerprint concentration in Robotics and significant contributions to Actuator Engineering (77%) and Vision Systems (68%). Petersen's research focuses on practical robotics applications including robot manipulation techniques for peg-in-hole assembly and disassembly in circular economies, precision machining with trajectory correction systems, and computer vision solutions for pose estimation and surface tracking. His work bridges theoretical innovation with industrial implementation through projects like MADE REACT which develops AI-powered resilient manufacturing systems. Recent investigations also explore energy-aware teleoperation and deep learning-based human modeling for physical human-robot interaction. Analysis of his 2022-2024 publications reveals strong trends toward sustainable robotics—designing disassembly systems for circular economies, developing resilient end effectors, and creating correction methods for precision machining. These efforts align with broader industrial resilience goals through integration of digital technologies and AI, particularly evident in the MADE REACT project's focus on flexible production systems. Petersen actively supervises two PhD candidates: Luo R. on safe energy-aware robotic teleoperation (2025-2028) and Zhou Y. on deep learning human modeling for physical human-robot interaction (2024-2027). His substantial grant portfolio includes the 13-year CAPeX project for P2X materials discovery, EUROfusion BB RH DEMO for fusion power control, and the flagship MADE REACT initiative demonstrating consistent success in securing competitive national and EU funding. Based at the Maersk Mc-Kinney Moller Institute, Petersen contributes to SDU Robotics' ecosystem which includes the MADE Open Lab for industry collaboration. This environment enables rapid prototyping and deployment of robotic solutions through strong partnerships with Danish manufacturing, as highlighted in 148 press/media features including the global robotics summer school in Odense and coverage of the MADE React project's 100-million-DKK impact on industrial resilience.

Ankit Agrawalمشاهده پروفایل

استادیار

• Cyber Physical Systems
• CPS Safety
• Simulation
• +۶ مورد دیگر

Dr. Ankit Agrawal serves as an Assistant Professor in the Department of Computer Science within the College of Arts and Sciences at Saint Louis University. His academic journey includes a Ph.D. in Computer Science from the University of Notre Dame (2022), where he worked under Dr. Jane Cleland-Huang. Prior to his current position, he conducted research on drone surveillance systems and human-machine interfaces for search and rescue operations. Dr. Agrawal's research focuses on the intersection of Software Engineering and Safety-Critical Systems, with particular emphasis on Cyber Physical Systems, CPS Safety, and Simulation. His work bridges theoretical foundations with practical applications in autonomous aerial platforms. Current research areas include Software Validation for testing and verification of cyber-physical systems, Simulation modeling of complex socio-technical systems, Requirements Engineering for safety-critical systems, and Human-Computer Interaction design for complex technical systems. His recent publications demonstrate a strong trend toward integrating AI and simulation technologies for validating autonomous drone systems. Research increasingly focuses on human-drone collaboration in emergency response scenarios, safety validation in realistic environmental conditions, and leveraging large language models for automated testing. The work spans both theoretical frameworks and practical tool development, with emphasis on bridging simulation-to-reality gaps. Honorable Mention at CHI Conference 2024 for HIFuzz: Human Interaction Fuzzing for small Unmanned Aerial Vehicles Best Paper at SPLC Conference 2020 for Requirements-Driven Configuration of Emergency Response Missions with Small Aerial Vehicles Fifth Place in Poster Presentation Award at NASA ImaginAviation 2024 Dr. Agrawal actively mentors graduate and undergraduate students through his UAV Research Lab at Saint Louis University. His lab currently supports multiple Ph.D. and Masters students working on projects including DroneReqValidator, DroneResponse, and React-G. The lab has secured research funding for projects related to drone safety validation and human-autonomy teaming, with collaborations including NASA Langley Research Center. Dr. Agrawal has served on program committees for major conferences including ASE, ICSE, and Requirements Engineering. The UAV Research Lab at Saint Louis University investigates software systems for autonomous aerial platforms, with three primary research thrusts: Software Engineering for Autonomous Systems (developing reliable software architectures and testing frameworks), Human-Autonomy Interaction (designing intuitive interfaces for human oversight), and Intelligent Software Systems (building AI-powered solutions for dynamic environments). The lab maintains active collaborations with NASA and emergency response organizations.

Philipp Alexander Raithمشاهده پروفایل

پژوهشگر

• Edge Intelligence
• Edge Computing
• Serverless Edge Computing
• +۱ مورد دیگر

Philipp Alexander Raith is a PreDoc Researcher and PhD student at the Distributed Systems Group of the Institute of Information Systems Engineering at Vienna University of Technology (TU Wien). His research focuses on edge intelligence, serverless edge computing, and AI operations, with a strong emphasis on resource optimization and infrastructure management across the edge-cloud continuum. BSc in Software Engineering (2018) from TU Wien MSc in Software Engineering & Internet Computing (2021) from TU Wien Research Interests encompass: Edge Intelligence Serverless Edge Computing AI/ML Operations Resource-aware Scheduling Distributed Systems Computing Continuum Publication Trends highlight his work in edge-cloud orchestration, neural feature compression, and quantum computing integration. Key areas include elasticity, serverless frameworks, and energy-aware architectures. Scientific Awards : UCC 2022 Best Paper Award SEC 2019 Best Demo Award 2020 Netidee Grant Winner Shortlisted for TU Wien Distinguished Young Alumnus Advising : Supervised multiple Master’s theses on edge-cloud autoscaling, AI workloads, mobile edge computing, and resource-aware offloading. Projects : Key contributor to AUTO-Cloud (2013–2025) and RAINBOW (2020–2022) projects.

Tirado Franciscoمشاهده پروفایل

استاد

• Power Aware Computing
• Heterogeneous Computing
• Applications optimization
• +۴ مورد دیگر

Francisco Tirado is a Full Professor of Computer Architecture at Complutense University of Madrid since 1986. He has held leadership roles including Vice-Chancellor for Research (2012-2015), Dean of the Faculty of Physics (1994-2002), and Director of the Complutense Supercomputing Center (2002-2007). He is a founding member of the Spanish Society for Computer Science (SCIE) and Spanish Society for Computer Architecture (SARTECO). His research focuses on power-aware computing, heterogeneous systems, bioinformatics, and hardware design automation. He has authored over 242 publications and supervised 15 PhD theses. His professional service includes chairing 138 international conferences and serving on numerous committees for EUROMICRO, IEEE, and national research agencies. Education: No explicit details provided, but has been active at Complutense University since 1978. Affiliations: Member of COSCE Executive Board (2012), IEEE Senior Member (2005), and EUROMICRO Board (1991-2004). Research Interests: - Optimizing energy efficiency in high-performance computing systems - Design of heterogeneous architectures and accelerators - Bioinformatics applications through hardware/software co-design - Parallel programming models for emerging architectures - Automation tools for FPGA and embedded systems development Conference Contributions: Played multiple roles (General Chair, Program Chair) for major events like ParCo, HPCA, and EUROMICRO PDP conferences. Delivered 64 keynote/plenary lectures globally. Scientific Awards: Doctor 'Honoris Causa' from universities in Spain, Paraguay, and Peru 2013 National Computer Science Award IEEE Senior Membership Advising: Supervised 15 PhD students. Active in technology transfer contracts with industry. Labs/Teams: Founder and leader of the ArTeCS research group at Complutense University, specializing in computer architecture and high-performance computing innovations.

• 3D Integrated Circuits
• Hardware Security
• AI Accelerators
• +۴ مورد دیگر

Krishnendu Chakrabarty is the Fulton Professor of Microelectronics in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU). He also serves as CTO of the SWAP Hub for the Department of Defense Microelectronics Commons and Director of the ASU Center for Semiconductor Microelectronics (ACME). Previously, he was the John Cocke Distinguished Professor and Chair of Electrical and Computer Engineering at Duke University. Education: B.Tech from IIT Kharagpur (1990), M.S.E. and Ph.D. from the University of Michigan (1992, 1995). His research focuses on 3D integrated circuits, hardware security, AI accelerators, and microfluidic biochips. He has authored 27 books, 930 peer-reviewed papers, and holds 24 patents. His work has been supported by NSF, DARPA, NIH, and industry partners like Intel and NVIDIA. Key awards include NSF CAREER Award, IEEE Technical Achievement Awards, Humboldt Research Award, and Distinguished Alumnus from IIT Kharagpur. He advises 44 PhD graduates and collaborates with industry leaders such as Synopsys and Cisco. His leadership roles include Editor-in-Chief of IEEE Transactions and Fellowships in ACM, IEEE, and AAAS. Research highlights include pioneering test methodologies for 3D ICs, developing AI-driven biochip solutions, and securing hardware against cyber-physical threats. His labs and teams focus on advancing semiconductor technology and healthcare applications through interdisciplinary innovation.

Huaming Chenمشاهده پروفایل

مدرس ارشد

• Software Engineering
• AI
• Cybersecurity
• +۳ مورد دیگر

Huaming Chen is a Senior Lecturer at the School of Electrical and Computer Engineering, The University of Sydney (equivalent to Associate Professor in the US system). He specializes in trustworthy AI, software security, and computational biology. His research focuses on integrating AI techniques into software engineering and scientific domains to enhance system reliability and ethical compliance. Currently, he advises PhD and master's students on projects involving AI in intelligent building systems, blockchain-driven governance frameworks, and open-source AI security. He holds roles as Area Chair for ACM MM, PC member for venues like ACM CCS and IJCAI, and Guest Editor for Computers & Security . His service extends to IEEE/ACM memberships and discipline expertise in Software Engineering and Electrical & Computer Systems. Awards include the 2020 IEEE CIS Student Grant and 2017 travel fellowships for bioinformatics and services computing conferences. Research interests span adversarial machine learning, AI ethics, computational biology applications, and secure AI system design. Key contributions include work on federated learning security, adversarial attacks on vision transformers, and privacy-aware STI/HIV risk prediction models. He actively promotes responsible AI through workshops and interdisciplinary collaborations.

• Digital Signal Processing (DSP)
• Field-Programmable Gate Arrays (FPGA)
• Machine Learning Hardware Acceleration
• +۱۳ مورد دیگر

Gian Carlo Cardarilli is a researcher specializing in digital hardware design and machine learning acceleration. His work focuses on FPGA implementations, Residue Number System (RNS) architectures, and reconfigurable computing for applications in wireless communication, edge AI, and fault-tolerant systems. Key collaborations with institutions like IEEE and ACM through publications. Active in translating theoretical algorithms into practical hardware solutions for real-time systems. Research interests include: Optimizing deep learning models for heterogeneous platforms. Developing radiation-hardened memory systems. Creating energy-efficient signal processing architectures. Advancing reconfigurable functional units for embedded processors. His article analyses span fields like Quantum Cellular Automata , Variable Fractional Delay Filters , and RNS-Based Position Estimation , reflecting a trend toward adaptive, low-power, and domain-specific hardware.

• Parallel Computing Systems
• Multi-core Embedded Systems
• System-level Design
• +۵ مورد دیگر

Prof. A.D. Pimentel holds a full professorship at the Informatics Institute of the University of Amsterdam, leading the Parallel Computing Systems (PCS) group within the Systems and Networking Lab. His research focuses on multi-core and multi-processor systems, emphasizing performance, energy efficiency, dependability, and productivity in system design and runtime management. He earned his PhD and MSc in Computer Science from the University of Amsterdam in 1998 and 1993, respectively. Current roles: Chair of PCS group, Board member of Advanced School for Computing and Imaging (ASCI), and ICT Research Platform Nederland (IPN) Teaching: Courses on Multi-core Processor Systems, Embedded Software, and Architecture Research interests span edge AI, sustainable computing, and system-level modeling. Recent work includes innovations in energy-efficient scheduling, thermal management in 3D-stacked systems, and adaptive CNN inference at the edge. Over 25 years of contributions to embedded systems design space exploration and hardware/software co-design have been recognized through awards like the IEEE CEDA Outstanding Service Award (2025). Awards: IEEE DATE Fellow (2025), NWO Knowledge & Innovation Covenant grant lead Active in conference organization, serving as General Chair for Embedded Systems Week (2026) and Design Automation and Test in Europe (DATE 2024). Engages in cross-disciplinary projects like improved secure semiconductor evaluation (ISSE) and energy labeling for digital services.

Aggelos Bletsasمشاهده پروفایل

استاد

• Wireless Communication
• Sensor Networking
• RFID Technology
• +۷ مورد دیگر

Aggelos Bletsas is a Full Professor in the Department of Electrical and Computer Engineering at Rutgers University. Previously, he held academic positions at the Technical University of Crete, where he served as Assistant Professor (2009–2014), Associate Professor (2014–2018), and Full Professor (2018–2024). His research focuses on scalable wireless communication, sensor networks, RFID systems, energy harvesting, and low-power IoT devices. He leads projects on batteryless backscatter sensors for precision agriculture and ambient-powered inference networks. Education: Ph.D. in Media Arts & Sciences (MIT, 2005) M.Sc. in Media Arts & Sciences (MIT, 2001) Diploma in Electrical & Computer Engineering (Aristotle University of Thessaloniki, 1998) Research interests include wireless sensor networks , RFID localization , signal processing for communication , and energy harvesting . His work emphasizes ultra-low-power, low-cost sensors deployable in agriculture and environmental monitoring. Key contributions include commodity-radio-based RFID localization and smartphone-readable backscatter sensors. Honors include IEEE Fellow (202?), IEEE Communications Society Distinguished Lecturer (2022–2024), and multiple best paper awards. His students have won IEEE VTS/AES Greek Chapter Best Thesis Awards (2012, 2013) and ComSoc Student Competition prizes. He serves as Area Editor for IEEE Transactions on Wireless Communications and is a top-2% global scientist per Stanford rankings. Advising and grants: Supervised over 15 students, with notable advisees listed in 'students'. His research has received ERC Starting Grant (A rating) and industry collaborations. Active in IEEE committees and conference organization. Labs and teams: Co-director of WINLAB (Wireless Information Network Laboratory) at Rutgers, focusing on wireless systems and IoT. Collaborates with industry partners on RF energy harvesting and backscatter communication prototypes.

Jens Rettkowskiمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Prof. Jens Rettkowski is a leading academic specializing in advanced computing architectures, particularly focusing on multi-core systems, reconfigurable hardware (FPGAs), and networks-on-chip (NoC). His work bridges theoretical computer architecture with practical applications in embedded systems, real-time processing, and autonomous technologies. Research Interests: Multi-Core Architecture Design and Optimization Networks-on-Chip (NoC) for High-Performance Systems Reconfigurable Computing and FPGA-Based Systems Hardware-Software Co-Design for Embedded Applications Real-Time Systems and Energy Efficiency Sensor Data Fusion and Autonomous Driving Publications reflect a strong focus on optimizing communication and computation in heterogeneous systems, with recent work emphasizing power savings in multi-core architectures and event-based debugging frameworks. His contributions include frameworks like MPSoCSim for simulating reconfigurable systems, and software-defined FPGA approaches for adaptive computing. He has led research in robotics applications for assisted living environments, combining navigation algorithms with real-time sensor processing. His work also addresses security aspects of FPGA configuration and partial bitstream analysis using machine learning.

Tolga Soyataمشاهده پروفایل

دانشیار

• Cyber-Physical Systems
• Digital Health
• FPGA-Based High-Performance Computing
• +۵ مورد دیگر

Tolga Soyata is an Associate Professor in the Department of Electrical and Computer Engineering at George Mason University's College of Engineering, specializing in cyber-physical systems, digital health, and high-performance computing. Previously, he served as an Associate Professor at SUNY Albany (2016-2019), Senior Lecturer at Johns Hopkins University (2020), and Assistant Research Professor at the University of Rochester (2008-2016). PhD, Electrical and Computer Engineering, University of Rochester (2000) MS, Electrical and Computer Engineering, Johns Hopkins University (1992) BS, Electrical and Communications Engineering, Istanbul Technical University (1988) His research focuses on cyber-physical systems , digital health applications , and FPGA/GPU-based high-performance computing , with significant contributions in medical cyber physical systems, brain-computer interfaces, and energy harvesting for embedded systems. His work bridges hardware design with healthcare applications and smart city infrastructure. Analysis of his recent publications reveals a strong emphasis on medical applications of cyber-physical systems (30%), smart city infrastructure (25%), energy-efficient computing (20%), and security/privacy frameworks (15%). His work consistently integrates hardware innovation with real-world applications, particularly in healthcare monitoring and urban systems. BEST PAPER AWARD (UEMCON18-BCI) PRESIDENTIAL AWARD FOR UNDERGRADUATE RESEARCH BEST PAPER AWARD (HONET-ICT'15) IEEE Senior Member (2016-present) ACM Senior Member (2016-present) As an advisor, he has mentored 12 PhD students (including 2 who completed degrees under his supervision) and over 25 master's/undergraduate researchers, many of whom received awards for their work. His TTIP directorship at GMU focuses on expanding graduate education in computer engineering through innovative recruitment and bridge programs. His research has been supported by industry partnerships with NVIDIA, Xilinx, and MOSIS. He leads research in medical cyber physical systems and energy-harvesting architectures, with lab facilities supporting FPGA development, GPU programming, and medical sensor integration for digital health applications.

Wei Zhangمشاهده پروفایل

عضو هیئت علمی

• Radiation Dosimetry
• Biomedical Imaging
• Medical Physics
• +۵ مورد دیگر

Wei Zhang is a Research Assistant Professor in the Department of Biomedical Engineering at the University of Michigan. His work focuses on advancing medical imaging technologies for radiation therapy, including ionizing radiation acoustic imaging (iRAI) for real-time dosimetry and treatment guidance. He also explores interdisciplinary areas like wireless power transfer systems and machine learning applications in healthcare. PhD in Biomedical Engineering His research interests include radiation dosimetry, multimodal imaging techniques (e.g., ultrasound and X-ray combinations), and their clinical applications in cancer therapy. He has pioneered the development of iRAI for volumetric dose mapping during radiotherapy, enabling precise treatment monitoring deep within tissues like the liver. Additional interests span driver behavior prediction systems and energy-efficient wireless charging solutions. Dr. Zhang received the BEST IN PHYSICS (THERAPY) Award in 2020 for his work on FLASH radiotherapy dosimetry. His contributions bridge biomedical engineering, physics, and clinical oncology, with a focus on translating innovations into practical clinical tools. He advises on grants related to medical imaging and energy systems, though specific grant details are not listed here. His lab is part of the Biomedical Engineering department’s advanced imaging and therapeutic technologies initiatives.

• Autonomous Vehicles
• Robotics
• Machine Learning
• +۳ مورد دیگر

Dr. Andrew Hill is a researcher at the University of Sydney's School of Aerospace, Mechanical and Mechatronic Engineering and serves as Centre Lead for the Rio Tinto Centre for Mine Automation within the Australian Centre for Field Robotics. With qualifications including a PhD and a BE in Mechatronics, he specializes in autonomous vehicle fleets for industrial applications. Expertise in robotics, machine learning, and transportation optimization Focus on mining automation, agricultural robotics, and environmental sustainability Key contributions to multi-vehicle coordination and sensor calibration His research emphasizes robust planning and control algorithms for autonomous vehicle fleets operating in challenging environments. Recent work explores energy-aware mission planning, radar-based material classification, and dynamic traffic optimization systems. Scientific contributions include: Net Zero Initiative Seed Funding (2022) Pioneering methods for autonomous vehicle slip compensation Innovative approaches to stochastic collection and replenishment optimization Dr. Hill supervises PhD candidates including Isaac Gill, Georgia Markham, and Milan Tomy in projects related to bionic arms, action recognition, and haul-truck dispatch systems. His work bridges theoretical control systems with real-world industrial implementations.

• Electrical Engineering
• Energy Systems Optimization
• Building Energy Efficiency
• +۵ مورد دیگر

Benoit Delinchant is a Professor at Université Grenoble Alpes, affiliated with the National School of Energy, Water and the Environment (Ense3) and the Department of Electrical Engineering and Industrial Computing. He serves as co-head of the MAGE research team (Models, Methods and Methodologies Applied to Electrical Engineering) at G2ELab since 2015 and co-facilitator of the Thematic Group for Complex Systems within GdR SEEDS. His educational leadership includes roles as Director of Studies and co-head of the GREEN thematic program at GS@UGA. Education: 2011: Habilitation to Direct Research (HDR), University of Grenoble 2003: Ph.D. in Electrical Engineering, INP Grenoble 2000: DEA in Electrical Engineering (Master's equivalent), INP Grenoble 2000: Engineering Degree in Electrical Engineering, INP Grenoble His research develops methods for modeling, simulation, and optimization of electrical energy systems, spanning electromagnetic components to multi-energy networks and building efficiency. Key focus areas include: Automatic modeling strategies for energy system design Uncertainty management in complex energy networks Optimization techniques for building-grid interactions Human-in-the-loop control systems His work integrates computational intelligence with practical applications in sustainable urban systems. Recent publications emphasize data-driven approaches to energy flexibility, carbon-aware systems, and hybrid modeling. Dominant themes include machine learning applications for load forecasting, lifecycle assessment methodologies, and experimental validation of demand response strategies. Cross-cutting focus on sustainability links building-scale optimizations with grid-level decarbonization challenges. Scientific Awards: No awards mentioned in source materials. Academic Supervision & Projects: Supervised 19 completed PhD theses and 6 ongoing doctoral candidates Led 4 study engineers, 6 post-docs, and managed 28+ Master's internships Major projects: Singapore NRF CREATE DesCartes (2021-26), PEPR TASE HyMES (2022-27), H2020 COLLECTiEF (2021-25), Grenoble IDEX OTE Observatory (2022-25), ANR COSIMPHI/INTENS/PRECCISION Leads research within G2ELab's MAGE team, collaborating with ENEDIS, EDF, ENGIE, Schneider Electric, CEA, and CSTB. Coordinates international partnerships including Brazil (UFSC) and Vietnam (USTH) for energy transition research.

• Distributed Systems
• Network Coding
• Information Theory
• +۳ مورد دیگر

MALAK Derya is an Assistant Professor at EURECOM's Communication Systems department, specializing in networked distributed computing systems. Her research focuses on optimizing communication and computation trade-offs in networks, with a strong emphasis on network coding, information theory, and wireless communication systems. She holds a dual role in advancing theoretical foundations and practical implementations of distributed computing frameworks. Dr. Malak has received prestigious recognitions, including the Best Paper Awards at WiOpt 2023 and WIOPT 2022 for her work on content distribution optimization and random access protocols. Her research explores cutting-edge topics such as non-linear function computation, structured coding for matrix operations, and congestion-aware job scheduling in real-time systems. Key Research Areas: Distributed Algorithms, Network Coding, Machine Learning Systems, Wireless HetNets, and Multi-Server Architectures Awards: WiOpt 2023 Best Paper, WIOPT 2022 Best Paper Professional Activities: Invited speaker at major conferences and workshops, including the National Center on Networks and Systems for Digital Transformation Her work bridges theoretical insights with practical engineering solutions, addressing critical challenges in modern distributed and networked systems.