جست‌وجوی استاد و پژوهشگر

Lei Yangمشاهده پروفایل

استادیار

• Hardware/Software Co-Exploration for Neural Network Architectures
• Embedded Systems
• Automated Machine Learning
• +۴ مورد دیگر

Dr. Lei Yang is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University, focusing on Hardware/Software Co-Exploration for Neural Network Architectures, Embedded Systems, and High-Performance Computing. Previously, she served as an Assistant Professor at the University of New Mexico and held post-doctoral and research scholar positions at Notre Dame, UC Irvine, and the University of Pittsburgh. Research Interests: System-Level Optimization for Applied Machine Learning Automated Machine Learning (AutoML) Federated Learning for Medical AI and Drug Discovery Quantum Neural Networks and Dark Silicon Many-Core Systems Thermal-Aware and Energy-Efficient Computing Award Trends: 50+ publications in premier venues like DAC, ICCAD, and IEEE Transactions, with multiple Best Paper Awards and Nominations. Notable recognitions include the 2021 IEEE TCAD Donald O. Pederson Best Paper Award and the 2017 ICCD Best Paper Award. Honors & Service: General Chair, SIGDA Student Research Forum at ASP-DAC 2023 Organizer, E2ML Workshop at GLVLSI 2021 Registration Chair, ICCD 2021 TPC Member, DAC 2022, ICCAD 2021, and IEEE SOCC 2020

• Computer Architecture
• GPU Systems
• Accelerators for Machine Learning
• +۴ مورد دیگر

Jose Luis Abellan Miguel is a Ramón y Cajal Fellow and Tenure-Track Associate Professor at the University of Murcia's Department of Computer Engineering and Technology. He leads the EcoArTech team and is a European R3 researcher. Previously, he held roles at the University of Ferrara, Boston University, and Universidad Católica de Murcia. His research focuses on GPU architectures, accelerators for machine learning, and privacy-preserving computing, particularly Fully Homomorphic Encryption (FHE). He has authored over 70 peer-reviewed publications and contributed to conferences like ISCA, HPCA, and MICRO. Education: Bachelor's, Master's, and PhD in Computer Science and Engineering (University of Murcia, 2007–2012) Research Interests: Abellan's work emphasizes architectural enhancements for GPU systems, customized accelerators for ML and FHE, and efficient synchronization/communication in many-core architectures. His contributions include tools like MGPU-Sim and STONNE for simulation, and frameworks like FIDESlib for FHE on GPUs. Recognition: HiPEAC Paper Awards (2011, 2019–2024) Top Picks in Hardware and Embedded Security 2024 European R3 Certificate (2024) Editorial roles at ACM TACO and Frontiers in Electronics Grants & Leadership: Recipient of a Ramón y Cajal fellowship and a Consolidación Investigadora grant. He chairs sessions at conferences like ISPASS and serves on TPCs for venues including DATE, HPCA, and MICRO. His lab collaborates with institutions like Georgia Tech, Northeastern University, and Intel. Labs/Teams: He leads the EcoArTech team, focusing on next-gen computing systems via architectural simulators. Collaborators include researchers from MIT, Boston University, and industry partners like NVIDIA and Intel.

João Paiva Cardosoمشاهده پروفایل

استاد

• Reconfigurable Computing
• Compilers
• Embedded Systems
• +۵ مورد دیگر

João Paiva Cardoso is a Full Professor at the Department of Informatics Engineering, Faculty of Engineering of the University of Porto, Portugal, and a Senior Researcher at INESC TEC's Human-Centered Computing and Information Science Centre since July 1, 2011. He earned his PhD in Electrical and Computer Engineering from the Technical University of Lisbon in 2001 and has built an extensive career spanning academia and industry. Former positions: IST/UTL (2006-2008), Senior Researcher at INESC-ID (2001-2009), University of Algarve (1993-2006) Industry experience: PACT XPP Technologies, Inc., Munich, Germany (2001/2002) Professional affiliations: Senior Member of IEEE, Member of IEEE Computer Society, Senior Member of ACM His research centers on compilation techniques, domain-specific languages, reconfigurable computing, and high-performance embedded systems. Recent publications reveal a strong focus on hardware/software co-design, with particular emphasis on FPGA acceleration and source-to-source compilation techniques for optimizing CPU-FPGA applications. His work addresses critical challenges in High-Level Synthesis compatibility, task graph representations, and holistic partitioning approaches. Professor Cardoso has served in leadership roles for numerous international conferences including General Chair of FPL'2013 and General Co-Chair of multiple ARC symposia. His supervised theses cover diverse topics from energy-efficient classification techniques to FPGA-based kNN accelerators, demonstrating the breadth and practical application of his research vision.

• Database Systems
• Storage Systems
• Hardware Acceleration
• +۳ مورد دیگر

Alberto Lerner is a Senior Researcher at the Department of Informatics within the Interfaculty Informatics Department at the University of Fribourg. His research focuses on advancing database systems, storage architectures, and hardware-software co-design. He holds a strong interest in computational storage, network-accelerated query processing, and the integration of modern hardware technologies like CXL into database engines. Lerner's work emphasizes performance optimization and scalable solutions in data-intensive computing environments. His research interests include database architecture, storage co-design, hardware acceleration, and network-driven computing. Recent publications highlight innovations in point cloud data processing, reprogrammable storage devices, and software-defined controllers for NAND flash systems. Lerner's articles reflect a trend toward leveraging modern hardware advancements to enhance database and storage performance. He has contributed to frameworks like BABOL and Data Pipes, advancing declarative control over data movement and network-based graph mining.

Minxuan Zhouمشاهده پروفایل

استادیار

• Systems
• High Performance Computing
• Parallel Computing
• +۵ مورد دیگر

Minxuan Zhou is an Assistant Professor of Computer Science at Illinois Institute of Technology. His research focuses on systems, high-performance computing, and parallel computing with an emphasis on processing-in-memory (PIM) acceleration, fully homomorphic encryption (FHE), and hyperdimensional computing. He holds a Ph.D. and M.S. in Computer Science from the University of California San Diego, and a B.S. in Computer Science and Technology from Beihang University. His work spans hardware-software co-design, cryptographic acceleration, and energy-efficient computing systems. Research Interests Processing-in-Memory (PIM) architectures for accelerating machine learning and graph processing Hardware acceleration for secure computation (FHE) Hyperdimensional computing frameworks for edge AI Thermal-aware design and memory optimization in 3D systems Recent Research Trends Recent publications emphasize co-optimization techniques for PIM architectures, FHE hardware acceleration, and privacy-preserving machine learning. His work often bridges theoretical algorithm design with practical hardware implementations using novel memory technologies like ReRAM and 3D-stacked memory. Grants & Labs Engaged in cutting-edge research through collaborations on projects involving PIM accelerators and encrypted computation systems. His lab focuses on developing full-stack solutions for next-generation computing architectures.

Gergely Vakulyaمشاهده پروفایل

دانشیار

• Cybersecurity
• Agricultural Technology
• Sensor Networks
• +۳ مورد دیگر

Dr. Gergely Vakulya is an Associate Professor and Research Fellow at Óbuda University. He specializes in interdisciplinary research spanning cybersecurity, agricultural technology, sensor networks, and image processing. His work integrates hardware design, algorithm development, and real-world applications. Dr. Vakulya’s recent focus includes developing rumen bolus sensors for dairy cattle health monitoring, gamification of cybersecurity training, and innovative methods in camera exposure time measurement. He is affiliated with Óbuda University’s Budai Road and Pirosalma Street campuses, with an office at building F room 316. His research frequently addresses challenges in data collection, sensor fusion, and embedded systems. Research Interests: Dr. Vakulya’s expertise includes cybersecurity frameworks (e.g., CTF challenges), agricultural IoT systems (e.g., rumen bolus sensors for livestock monitoring), and image processing techniques (e.g., genetic algorithms for shape approximation). His work on visible light communication (VLC) and wireless sensor networks highlights his contributions to communication protocols and energy-efficient systems. Recent trends in his publications emphasize cross-disciplinary approaches, such as applying AI methods to agricultural sensor data and optimizing sensor networks for real-time applications. Advising & Grants: No specific advising relationships or grants are listed in available materials. His research infrastructure is likely supported through institutional and collaborative projects. Labs/Teams: While not explicitly stated, his research likely involves collaborations within Óbuda University’s engineering and computer science departments. His work on rumen sensors and VLC systems suggests potential affiliations with robotics, biomedical engineering, or smart agriculture research groups.

• Embedded Systems
• AI Algorithms
• FPGA/VHDL Design
• +۵ مورد دیگر

Jürgen Wassner is a Professor of Edge Computing and Co-Head of the Competence Center for Intelligent Sensors and Networks at the Lucerne School of Engineering and Architecture (HSLU T&A). He holds a master's degree from Technical University of Dresden and a PhD from ETH Zurich. His career spans industry roles in Silicon Valley Group Inc. and telecommunication R&D before joining academia in 2007. His research focuses on embedded systems, AI at the edge, FPGA/VHDL design, real-time systems, and powerline communication . He leads projects such as 'Visual-Servoing Testbed with AI-Hardware in the Loop' and 'Low-Cost High-Performance Intelligent Camera for Space Debris Mitigation,' collaborating with companies like Diehl Aerospace. Recent publications emphasize wire fault detection using powerline communication, AI-based odor classification systems, and hardware acceleration for CNNs. His work bridges theoretical research with practical applications in avionics, rail freight, and space debris mitigation. Wassner advises Master of Science in Engineering students and has been recognized for his media engagement including a feature in the Luzerner Zeitung. He teaches Digital Design (FPGA, VHDL) and Digital Signal Processing , emphasizing hands-on implementation of cutting-edge systems.

Minesh Patelمشاهده پروفایل

استادیار

• Computer Architecture
• Memory Systems
• Hardware Security
• +۳ مورد دیگر

Minesh Patel is an Assistant Professor at Rutgers, The State University of New Jersey. His research focuses on computer architecture, memory systems, and hardware security, with a particular emphasis on DRAM reliability, RowHammer vulnerabilities, and in-memory computing. He has contributed to frameworks like DRAM Bender and NEON , which explore novel hardware-software co-design approaches. His work bridges theoretical analysis with experimental validation, addressing challenges in modern memory systems such as error mitigation, latency reduction, and security exploits. Recent projects include studying RowHammer under temperature variations and exploring resistive RAM-based neural networks. He has also published in medical informatics, analyzing surgical outcomes during the pandemic, suggesting interdisciplinary collaboration interests. Patel's research has implications for both academic and industry applications, including cloud computing security and embedded systems optimization. His publications span journals and conferences in computer engineering, cybersecurity, and healthcare analytics.

• Security
• IoT
• Computer and Network Security
• +۳ مورد دیگر

Dimitrios G. Myridakis is a Postdoctoral Researcher and Military Research Associate at the Department of Computer Sciences and Biomedical Informatics, University of Thessaly (School of Science). He holds a Ph.D. from the same department and has been affiliated with research teams funded by NOKIA Bell Labs. His roles include Teaching Assistant for the course “Embedded Computer Systems in Biomedicine,” and participation in multiple academic committees such as the Scientific Technical Program Committee of IEEE Potentials Magazine and EAI International Conferences. Education: BSc in Computer Engineering and Computer Technology (2012) MSc in Informatics and Telematics (2014) Ph.D. in Computer Sciences and Biomedical Informatics (2021) His research focuses on IoT Security , Embedded Systems , Hardware-Based Threat Mitigation , and Machine Learning Applications . He explores techniques like power dissipation monitoring, supply current threshold analysis, and biometric security in smart healthcare devices. His work emphasizes real-time anomaly detection and botnet prevention in IoT ecosystems, often with biomedical informatics integration. Scientific Awards: 2018 ICCE Berlin OUTSTANDING PAPERS AWARDS Highlight on Future Internet 2020 Magazine Cover Scholarship & Funding from NOKIA Bell Labs Advising and Grants: While no formal advisees are listed, his research is funded by NOKIA Bell Labs and Nokia. He has contributed to teaching and academic review processes, including roles as a Scientific Jury member and reviewer for conferences like SEEDA-CECNSM 2019 and SecRioT 2019. His work aligns with advancing cybersecurity through hardware and embedded system innovations. Labs and Teams: Member of the Intelligent Systems Laboratory (ISL) , A2rTEST Creative Team , and the IEEE Student Branch at the University of Thessaly. He has developed prototypes for smart healthcare systems and participated in competitions, demonstrating practical applications of his research in IoT security and embedded systems.

• Computer Architecture
• Embedded Systems
• Hardware/Software Co-Design
• +۵ مورد دیگر

Hammam Alsafrjalani is an Associate Professor of Practice in the Department of Electrical & Computer Engineering at the University of Miami. His roles include teaching undergraduate and graduate courses such as Computer Architecture, Embedded Systems, and Microprocessors, and supervising senior design projects. He holds a Ph.D. and M.S. in Electrical and Computer Engineering from the University of Florida (2015 and 2011, respectively), and a B.S. from the New Jersey Institute of Technology (2007). His research focuses on computer architecture, embedded systems, heterogeneous-and-configurable systems, AI for cybersecurity, and runtime optimization. Notable achievements include developing optimization techniques for energy, performance, and temperature in multicore systems, yielding up to 25% energy savings. His work has been published in peer-reviewed journals and conferences. Awards include the Faculty Learning Community Fellowship (2022 and 2019), Most Innovative Faculty Member (2020 and 2019), and the Student-Choice Best Engineering Faculty Member Award (2019). He has contributed to proposals in computer science, applied science, and multidisciplinary projects with psychology and communication schools. Teaching tools include Quartus Prime, Gem5, and Python, with a focus on hands-on projects. His research emphasizes practical applications in consumer electronics and augmented reality, leveraging industry experience from internships at Intel and Microsoft, and prior roles at Dialogic and Vonage.

Joseph Timoneyمشاهده پروفایل

استاد

• Audio Signal Processing
• Musical Sound Synthesis
• Digital Audio Watermarking
• +۳ مورد دیگر

Joseph Timoney is a professor at the Department of Computer Science , Maynooth International Engineering College , Maynooth University. He teaches undergraduate programs in Computer Science and Music Technology, with expertise in audio signal processing, musical sound synthesis, and digital modeling of analog subtractive synthesis. His research spans sound synthesis algorithms, audio watermarking, and ubiquitous music ecosystems.

Le Guanمشاهده پروفایل

دانشیار

• Computer Security
• Embedded Systems
• Cyber-Physical Systems
• +۳ مورد دیگر

Le Guan is an Associate Professor at the School of Computing, University of Georgia. His research focuses on embedded systems security, IoT security, and software engineering. He holds a PhD from the Chinese Academy of Sciences and a BEng from the University of Science and Technology of China. His work includes groundbreaking contributions to firmware security, hardware-assisted defense mechanisms, and vulnerability detection in cyber-physical systems. Education: PhD in Information Technology, Chinese Academy of Sciences (2015) BEng in Computer Science, University of Science and Technology of China (2009) Research Interests: Embedded Systems Security Firmware Integrity and Analysis Cyber-Physical System Defense Hardware-Software Co-Security Automated Vulnerability Detection Recent Research Trends: Recent articles highlight innovations in firmware emulation, hybrid fuzzing for IoT devices, and hardware-assisted security mechanisms for microcontrollers. His work frequently bridges theoretical frameworks with practical implementations for real-world embedded systems. Awards: NSF Career Award (2023) Student Career Success Influencer Award (2022) Grants and Collaborations: Co-PI on the 2023 Presidential Interdisciplinary Seed Grant on Deep Fakes. His NSF Career Award supports research into data protection in embedded systems. Collaborates widely with industry and academia on firmware security and automotive systems.

Juan Andrade Cettoمشاهده پروفایل

پژوهشگر

• Mobile Robotics
• Computer Vision
• Neuromorphic Systems
• +۳ مورد دیگر

Juan Andrade Cetto is a Researcher at the Institute of Robotics and Industrial Informatics (IRI), part of the Spanish National Research Council (CSIC). He previously served as Director of IRI from 2014 to 2020. His expertise spans mobile robotics, computer vision, and neuromorphic systems. He holds a BSEE from CETYS University (1993), an MSEE from Purdue University (1995), and a PhD in Robotics from the Universitat Politècnica de Catalunya (UPC, 2003), recognized with the EURON Georges Giralt Best PhD Award in 2005. Research Interests: - Mobile Robotics and Autonomous Systems - Event-based Vision and Neuromorphic Sensors - Real-time Sensor Fusion and SLAM - Control Systems for Energy Conversion (e.g., PEM Fuel Cells) - Probabilistic Methods for Robotics and Computer Vision Recent Research Trends: His work emphasizes neuromorphic computing and event-based systems for robotics applications, including optical flow estimation, ego-motion tracking, and real-time SLAM. Collaborations include EU projects like ALLIES (AI for Sustainable Development Goals) and RAMON LLULL (AIRA Postdoctoral Programme). He leads the BOMBUS project (Perception and Navigation for Agile Robotics, 2024–present). Scientific Awards: EURON Georges Giralt Best PhD Award 2005 Grants & Leadership: Principal Investigator in multiple national/EU projects including BOMBUS (CSIC) and ALLIES (European). Advising: - Current Students: José Agustín Aguilar Plazaola (Fuel Cell Control), Raquel De Frutos Arranz (Event Camera-based Collision Avoidance) - Past Students: Not explicitly listed in provided text. Labs & Teams: Active in IRI’s Robotics and Industrial Informatics research groups, focusing on applied robotics and sensor systems.

Christian Vogtمشاهده پروفایل

مدرس

• IoT and Embedded Systems
• Wireless Sensor Networks
• Medical Electronics
• +۳ مورد دیگر

Dr. Christian Vogt Dr. Christian Vogt is a Lecturer at the Department of Information Technology and Electrical Engineering within the Center for Project-Based Learning at ETH Zürich. His research focuses on IoT systems, embedded electronics, and wearable technology with applications in agriculture, healthcare, and urban computing. He specializes in energy-efficient sensor networks, flexible electronics, and real-time data transmission systems. Research Interests Vogt's work bridges hardware innovation and software optimization, emphasizing practical implementations through project-based learning. Key areas include: IoT and Wireless Sensor Networks Low-power embedded machine learning Wearable biomedical devices Flexible/stretchable electronics Ultra-wideband and radar-based sensing Publications Recent work highlights energy-efficient livestock monitoring systems using LoRa, battery-free sensor nodes powered by human body energy, and real-time gesture recognition with novel sensors. His research often involves interdisciplinary collaborations between computer science, electrical engineering, and biomedical applications. Affiliations ETH Zürich - Center for Project-Based Learning Department of Information Technology and Electrical Engineering Contact: christian.vogt@pbl.ee.ethz.ch

• Computer Architecture
• Hardware Acceleration
• Deep Learning
• +۶ مورد دیگر

Hyuk-Jae Lee is a prominent researcher in computer architecture and hardware acceleration for deep learning systems, with an extensive publication record spanning over two decades. His work primarily focuses on hardware implementations for video processing, memory systems, and neural network acceleration. Through numerous collaborations with researchers at Korean institutions (particularly with Hyun Kim, Chae-Eun Rhee, and Xuan Truong Nguyen), Lee has established himself as a leading figure in circuit design for AI applications. Lee's research interests center around computer architecture, hardware acceleration, deep learning systems, video coding and compression, memory systems, and image processing. His work demonstrates a consistent focus on bridging the gap between theoretical algorithms and practical hardware implementations, with particular emphasis on optimizing performance and efficiency for real-world applications. His recent work shows a strong shift toward accelerating large language models and transformer-based architectures, reflecting current trends in AI hardware. Analysis of Lee's recent publications (2023-2025) reveals a clear research trajectory toward solving memory bandwidth and computational efficiency challenges in modern AI systems. His work spans the spectrum from low-level circuit design to high-level system architecture, with particular strength in memory systems optimization and hardware acceleration for neural networks. The consistent publication record in top-tier IEEE journals demonstrates sustained research productivity and impact in the field. Throughout his career, Lee has collaborated extensively with a core group of researchers, suggesting stable research teams and laboratories focused on hardware acceleration. His publications in IEEE Transactions on Circuits and Systems, IEEE Transactions on Computers, and IEEE Transactions on Video Technology indicate recognition by multiple relevant academic communities.