جست‌وجوی استاد و پژوهشگر

Brandon Luciaمشاهده پروفایل

استاد

• computer architecture
• computer systems
• programming languages
• +۸ مورد دیگر

Brandon Lucia is a Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He holds the Kavčić-Moura Professorship and leads the Abstract research group. As CEO and co-founder of Efficient Computer Corp., he bridges academic research with commercial applications in energy-efficient computing. Dr. Lucia received his Ph.D. in Computer Science and Engineering from the University of Washington in 2013, following an MS from the same institution in 2010 and a BS in Computer Science from Tufts University in 2007. His research focuses on the intersection of computer architecture, computer systems, and programming languages, particularly in energy-constrained environments. His primary research interests include intermittent computing, energy harvesting computers, orbital edge computing, and parallel computing systems. Lucia's work addresses fundamental challenges in creating programmable, reliable computing devices that operate without batteries by harvesting energy from their environments, with applications in sensing, medical implants, and space systems. He also investigates software systems and architectures for making parallel computing correct, reliable, and efficient in the post-Moore's Law era. Lucia's publication record shows a clear trajectory toward orbital edge computing and nanosatellite systems, with recent work focusing on computational constellations, visual navigation for satellites, and energy-efficient processing in space. His research spans both theoretical foundations of intermittent computing and practical implementations in hardware and software. 2021 Sloan Research Fellowship 2018 NSF CAREER Award 2018 ASPLOS Best Paper Award IEEE MICRO Top Picks in Computer Architecture (2009, 2010, 2016) 2015 OOPSLA Best Paper Award 2019 IEEE TCCA Young Computer Architect Award 2022 Engineering Faculty Award As an advisor, Lucia has mentored numerous graduate students including Brad Denby, Zhuo Cheng, and Kyle McCleary, many of whom have become co-authors on his significant publications. His lab developed the world's first batteryless PocketQube nanosatellite (Tartan-Artibeus-1), which was deployed to low-Earth orbit aboard the SpaceX Transporter-3 Rocket. Lucia's research has received funding from sources including NSF, DARPA, Google, and VMware, supporting both fundamental research and practical implementations of energy-harvesting computing systems.

Rogério de Lemosمشاهده پروفایل

مدرس ارشد

• Resilient AI
• Self-adaptive software systems
• Authorisation infrastructures
• +۷ مورد دیگر

Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.

Elisa Donatiمشاهده پروفایل

پژوهشگر

• Neuromorphic Engineering
• Biomedical Signal Processing
• Wearable Healthcare Technologies
• +۵ مورد دیگر

Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .

Cecilia Mascoloمشاهده پروفایل

استاد

• Mobile Systems
• Wearable Computing
• Machine Learning
• +۵ مورد دیگر

Cecilia Mascolo is a Professor of Mobile Systems at the University of Cambridge , specifically in the Department of Computer Science and Technology . She co-directs the Centre for Mobile, Wearable System and Augmented Intelligence and is a Fellow of Jesus College, Cambridge . Her research focuses on mobile systems , machine learning for mobile health , and earable technology . She has been awarded prestigious grants such as the ERC Advanced Research Grant (2019-2025) and the EPSRC Open Research Fellowship (2025-2030). Currently on sabbatical at Harvard University , her work bridges systems and machine learning for health applications. Education: PhD in Computer Science from the University of Bologna, Italy. Previous Affiliation: Faculty at University College London before 2008. Her research spans mobile and wearable systems for health and behavior monitoring, focusing on on-device machine learning , uncertainty-aware models , and audio-based diagnostics . Key areas include federated learning , edge computing , and respiratory disease progression analysis via wearables. She explores earable technology for physiological monitoring, gait analysis, and even toothbrushing tracking using in-ear sensors. Her recent publications highlight advancements in earable-based health monitoring , including heart rate estimation , respiratory rate detection , and ECG analysis using machine learning. She emphasizes longitudinal health data from consumer devices, advocating for scalable diagnostics beyond traditional clinical standards. Scientific Awards: ERC Advanced Research Grant EPSRC Open Research Fellowship Best Paper Award - IEEE Percom 10-Year Impact Award - ACM Ubicomp Computer Laboratory Ring Hall of Fame Best Paper Award Student: Andrea Ferlini - ACM SIGMOBILE Doctoral Dissertation Runner-up She leads the Mobile Systems Research Laboratory , mentoring a team of 15 researchers (postdocs and PhD students), and has graduated over 25 PhD students. Her teaching includes Mobile Health courses at the University of Cambridge, and she serves as Director of Studies for Computer Science at Jesus College.

Trey Portoمشاهده پروفایل

استاد مدعو

• Quantum Physics
• Ultra-cold Atoms
• Quantum Optics
• +۵ مورد دیگر

Trey Porto is an Adjunct Professor at the University of Maryland, affiliated with the Joint Quantum Institute (JQI) and NIST. His research focuses on ultra-cold atoms, quantum optics, and quantum information science. He leads projects on Rydberg atoms, optical lattices, and quantum networking, leveraging cold atom systems to explore novel quantum phenomena and control strategies. Research areas include ultra-cold Rb/Yb mixtures for studying Bose-Einstein condensates and engineered dissipation, as well as photon-photon interactions using Rydberg-dressed polaritons. His work bridges quantum simulation, quantum computing, and precision measurement, with applications in quantum networking and many-body physics. Key achievements include the 2023 UMD Quantum Invention of the Year Award for developing photon-counting methods that preserve quantum states. Porto collaborates with groups such as RQS and JQI, contributing to advancements in subwavelength optical potentials and Floquet-engineered systems. He mentors graduate students in experimental and theoretical aspects of cold atoms and quantum technologies. Publications highlight breakthroughs in Rydberg blockade enhancement, prethermal Bose-Einstein condensation, and compact auto-alignment systems for experimental setups. His lab is based in the Physical Sciences Complex on the UMD campus, with ongoing projects exploring quantum dissipation and photon-atom hybrid systems.

Xiaofan Yuمشاهده پروفایل

استادیار

• Embedded Systems
• Edge AI
• Neuromorphic Computing
• +۵ مورد دیگر

Xiaofan Yu is an Assistant Professor in the Department of Electrical Engineering at the University of California, Merced. He holds a Ph.D. (2025), M.S. (2020), and B.S. (2018) from the University of California, San Diego and Peking University, respectively. His research focuses on embedded systems , edge AI , and neuromorphic computing , with applications in IoT, federated learning, and hyperdimensional computing. ML&Systems Rising Star (2024) CPS Rising Star (2023) EECS Rising Star (2022) His work addresses on-device AI for real-world IoT deployments, reliability-driven sensor networks , and next-generation edge intelligence . Recent publications highlight advancements in federated learning (TIOT 2025), multimodal sensor interaction (IMWUT 2025), and noise-resilient sensor systems (Sensors 2024). Key subfields include hyperdimensional computing , asynchronous distributed training , and resource-efficient edge models . Dr. Yu actively mentors students across institutions and programs, including the Early Research Scholarship Program (UCSD) and ENLACE Summer Research Program. He has advised projects on smart elderly monitoring , LLM-based sensor reasoning , and hyperdimensional algorithm optimization . Collaborations span UCSD, TUM, and Stanford, with industry partnerships in IoT design automation (RelIoT simulator) and biomedical applications (bladder fullness restoration system).

Duncan Wilsonمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Artificial Intelligence (AI)
• Smart Cities
• +۷ مورد دیگر

Duncan Wilson is a Professor of Connected Environments at the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London. His work bridges academia and industry, focusing on IoT, AI, and spatial analysis to enhance understanding of built and natural environments. Current role: Professor of Connected Environments at UCL Education: PhD in Artificial Intelligence and Machine Vision (UCL, 1997), BEng (Hons) in Electrical Engineering (Loughborough University, 1993) Research interests include: Cognitive computing at the network edge Extraordinary sensory systems for data capture Spatial reasoning and digital twins IoT for healthcare and biodiversity Edge AI and TinyML Recent articles span digital twin development , IoT for biodiversity monitoring , and smart healthcare infrastructure . He has received recognition for collaborative R&D approaches during his directorship at Intel's Sustainable Connected Cities institute. Teaching: Leads MSc Connected Environments and modules on IoT ethics, AI on microcontrollers, and sensor network deployment Projects: IoT Living Lab at UCL, Project Hercules for eye clinic analytics, and Shazam for Bats environmental monitoring Professional activities: Former Director of Intel Collaborative Research Institute (2012-2018), ex-member of Smart London Board (2017-2022)

Felix Xiaozhu Linمشاهده پروفایل

دانشیار

• Systems Software
• Operating Systems
• Computer Architecture
• +۴ مورد دیگر

Felix Xiaozhu Lin serves as Associate Professor and William Wulf Faculty Fellow in the Department of Computer Science at the University of Virginia's School of Engineering and Applied Science, where he directs the Computer Science Ph.D. Program and MCS/MS Program. Previously a tenured Associate Professor at Purdue University's School of Electrical and Computer Engineering, Lin joined UVA Engineering in August 2020 after completing his doctoral research at Rice University. His educational credentials include: Ph.D. in Computer Science, Rice University (2014) M.S. in Computer Science, Tsinghua University (2008) B.S. in Automation, Tsinghua University (2006) Lin's research centers on systems software at the intersection of operating systems, compilers, and computer architecture, with emphasis on accelerating and safeguarding software systems. His current projects target on-device large language models and speech processing for low-cost hardware ( Analysis of his recent publications reveals a strong trajectory in edge computing and efficient AI systems. His research demonstrates increasing focus on hardware-software co-design for autonomous devices, with significant contributions in video analytics for energy-constrained cameras, kernel virtualization for heterogeneous architectures, and stream processing frameworks leveraging emerging memory technologies. The work consistently addresses real-world constraints like power limitations and network intermittency while maintaining rigorous academic standards. His scientific recognition includes: National Science Foundation CAREER Award (2019) Google Faculty Research Award (2016) NSF CISE Research Initiation Initiative Award (2015) ACM ASPLOS Best Paper Award (2014) Lin leads the XSEL research group mentoring graduate and undergraduate students in systems software development. His educational initiatives include CS4414/CS6456, a modern operating systems course featuring Arm64 baremetal kernel development, multicore systems, trusted execution environments, and filesystem forensics. The course's experiential approach has received strong student feedback for its modern content and practical relevance. His group actively recruits for projects spanning on-device AI, hardware-accelerated speech processing, and next-generation OS development. Based in Charlottesville, Virginia, Lin's research benefits from UVA's proximity to Shenandoah National Park and collaborative opportunities within the university's vibrant computing ecosystem, including the 2024 LLM Workshop he co-organized with Professor Yangfeng Ji.

• Electrical and Computer Engineering laboratory curriculum
• Digital systems design
• CAD for VLSI
• +۴ مورد دیگر

Mark C. Johnson is a Senior Lecturer at the Elmore Family School of Electrical and Computer Engineering at Purdue University, West Lafayette. He serves as Director of Instructional Laboratories and Associate Director for Design - Semiconductor Degree Program , overseeing laboratory infrastructure, CAD software administration, and curriculum development for courses like ECE337, ECE437, and ECE364. Education: Ph.D. in Electrical Engineering (1998), Purdue University M.S. in Electrical Engineering (1991), Wichita State University B.S. in Electrical Engineering (1983), Purdue University - Calumet His research focuses on electrical and computer engineering laboratory curriculum innovation , digital systems design , and CAD for VLSI . Over 15 recent publications highlight his work in SoC prototyping , low-power circuit design , and educational technology , spanning projects like FPGA filter optimization, dual-core processor experiments, and active learning strategies. Leadership Roles: Proceedings Chair (2003), MSE Program Chair (2005), MSE General Chair (2007), MSE Steering Committee Member, MSE & European Workshop on Microelectronics Education Chair, ECE Instructional Innovation Group (2004-2012) Secretary/Webmaster, ASEE Illinois/Indiana Section (2002-2011) He directs the ECE437 Computer Architecture Prototyping Lab and System on Chip Extension Technologies (SoCET) team , and co-advises the STARS semiconductor readiness program. Outside academia, he is an organist at Faith Presbyterian Church and composes keyboard music.

• Embedded Systems
• Artificial Neural Networks
• Signal Processing
• +۳ مورد دیگر

Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.

Steven V. Leyمشاهده پروفایل

استاد

• Organic Chemistry
• Flow Chemistry
• Green Chemistry
• +۴ مورد دیگر

Professor Steven V. Ley leads the Yusuf Hamied Department of Chemistry at the University of Cambridge, focusing on transformative research in flow chemistry, organic synthesis, and green chemistry. His work emphasizes sustainable methodologies and the integration of advanced technologies like microcontrollers and automation to revolutionize chemical processes. In 2018, he received the prestigious Arthur C. Cope Award—the first UK-based recipient—recognizing groundbreaking contributions to organic chemistry. Research interests include developing continuous flow systems for hazardous reaction management, immobilized reagents, and machine-assisted synthesis. Collaborations span academia and industry, notably through spin-off company New Path Molecular , which applies cutting-edge synthesis techniques to pharmaceuticals and agrochemicals. Key publications highlight innovations in flow chemistry applications, sustainable process design, and automation. His work bridges chemistry with engineering, aiming to address global challenges in resource efficiency and environmental impact. Awards: Arthur C. Cope Award (2018) Lab/Teams: Active research group at the University of Cambridge; collaborates with New Path Molecular on commercial applications.

Tingkai Wangمشاهده پروفایل

مدرس ارشد

• Mobile Robots
• Intelligent Systems
• Artificial Intelligence (AI)
• +۵ مورد دیگر

Dr. Tingkai Wang is a Senior Lecturer in the School of Computing and Digital Media at London Metropolitan University. His research focuses on mobile robots, intelligent systems, artificial intelligence, control systems, image/signal processing, and virtual reality. He teaches the Programming for Computer Science module and has led projects like the Virtual Environment and Simulation System (2000-2002) and Navigation and Control of Mobile Robots (1995-1998). His work emphasizes interdisciplinary approaches, combining expert systems, neural networks, and fuzzy logic to address challenges in autonomous systems. Notable contributions include AGV navigation algorithms, hybrid control systems, and predictive modeling. Over 30 publications span robotics, control engineering, and AI applications. He collaborates internationally and has presented at venues like the International Conference on Intelligent Systems Engineering and the IEEE Conference on Engineering in Medicine and Biology. Dr. Wang’s expertise bridges theoretical modeling and practical implementation, with applications in manufacturing automation, environmental monitoring, and industrial management systems. His current research continues exploring adaptive control mechanisms and AI-driven robotics solutions.

Angshuman Karmakarمشاهده پروفایل

استادیار

• Post-Quantum Cryptography
• Computation On Encrypted Data
• Side-Channel Analysis
• +۴ مورد دیگر

Angshuman Karmakar is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur, India. His research focuses primarily on Post-Quantum Cryptography (PQC) and Computation On Encrypted Data (COED), which are critical areas in modern cryptography and computer security. Dr. Karmakar received his Ph.D. from Katholieke Universiteit Leuven (KU Leuven), Belgium, where he worked under Prof. Ingrid Verbauwhede in the COSIC research group. He was awarded the prestigious Erasmus Mundus fellowship for his doctoral studies and the FWO (Fonds voor Wetenschappelijk Onderzoek – Vlaanderen) fellowship for his post-doctoral research at KU Leuven. His research spans theoretical development of cryptographic schemes, implementation algorithms, side-channel and fault attack analysis, and countermeasure development. Dr. Karmakar has established extensive international collaborations with researchers and engineers worldwide to address complex challenges in cryptography and security. Recent publications demonstrate a strong focus on practical post-quantum cryptographic implementations with particular attention to hardware and software efficiency, side-channel resistance, and novel attack methodologies. His work bridges theoretical cryptography with real-world implementation challenges across diverse platforms from IoT devices to high-performance computing systems. Erasmus Mundus fellowship for doctoral studies at KU Leuven FWO fellowship for post-doctoral study at KU Leuven Google India Research Award for work on practical transition to post-quantum cryptography Dr. Karmakar is actively seeking graduate students and postdoctoral researchers to collaborate on cutting-edge research in cryptography and computer security. His work has significant implications for securing future communication systems against quantum computing threats, with applications spanning blockchain technologies, IoT security, and general-purpose computing systems.

Pasquale Davide Schiavoneمشاهده پروفایل

مدرس

• Embedded Systems
• RISC-V Architecture
• Ultra-low-power Computing
• +۵ مورد دیگر

Pasquale Davide Schiavone holds multiple research and teaching positions at École Polytechnique Fédérale de Lausanne (EPFL), serving as a Lecturer at the School of Computer and Communication Sciences (IC) and as a Scientist at both the Embedded Systems Laboratory (ESL) within the School of Engineering (STI) and PAT Administration. His interdisciplinary work bridges computer architecture, embedded systems design, and biomedical applications, with office located at ELG 136 in Lausanne, Switzerland. Dr. Schiavone's research focuses on ultra-low-power computing systems, particularly RISC-V architectures and TinyML applications for edge devices. His work develops open-source hardware platforms like X-HEEP and HEEPOCRATES that enable energy-efficient AI at the edge, with applications spanning biomedical monitoring, neural interfaces, and wearable computing. He explores innovative hardware-software co-design approaches to overcome energy constraints in resource-limited environments. His recent publications reveal a consistent research trajectory centered on open, configurable computing platforms for specialized applications. The work spans from fundamental RISC-V architecture improvements (ARCANE, e-GPU) to application-specific implementations for biomedical contexts (BiomedBench, neural interfaces). A strong emphasis on energy efficiency permeates all his research, whether through novel arithmetic approaches (Posit), system architecture (near-memory computing), or specialized accelerators (Strela, Quadrilatero). Lecturer, School of Computer and Communication Sciences (IC) Scientist, Embedded Systems Laboratory (ESL), School of Engineering (STI) Scientist, PAT Administration, School of Engineering (STI) Dr. Schiavone teaches courses on hardware compilation, presenting algorithms and methods for transforming hardware description languages into optimized circuit implementations. His Embedded Systems Laboratory work places him at the forefront of developing practical, open-source solutions for next-generation computing challenges in energy-constrained environments.

Alexander Deanمشاهده پروفایل

دانشیار

• Computer Architecture
• Embedded Systems
• Compiler Technology
• +۵ مورد دیگر

Alexander Dean is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on embedded systems, leveraging compiler technology, computer architecture, and real-time systems to enhance concurrency and energy efficiency in cost-effective hardware. He has held industrial experience at United Technologies Research Center, working on embedded systems for aerospace, automotive, and building systems. Dr. Dean holds a Ph.D. (2000), M.S. (1993), and B.S. (1991) in Electrical and Computer Engineering from Carnegie Mellon University and the University of Wisconsin at Madison, respectively. His research interests include real-time systems, compiler optimization for concurrency, energy-efficient embedded designs, and memory allocation strategies. He is the recipient of the NSF CAREER Award (2002) and multiple teaching awards, including the NC State Thank a Teacher Award (2011). Dr. Dean teaches courses such as ECE 460/560 (Embedded System Architectures) and ECE 461/561 (Embedded System Design), emphasizing hands-on embedded systems development. His work also involves MCU control of power converters and robust system design methodologies.