جست‌وجوی استاد و پژوهشگر

Robert René Maria Birkeمشاهده پروفایل

استادیار

• Virtual Resource Management
• Network Design
• Workload Characterization
• +۶ مورد دیگر

Robert René Maria Birke is a tenured assistant professor in the Department of Computer Science at the University of Turin, leading research in the Parallel Computing group. His expertise spans virtual resource management, network design, workload characterization, and optimization of AI/big-data applications. Previously, he served as a visiting researcher at IBM Research Zurich and Principal Scientist at ABB Corporate Research, combining industry experience with academic rigor since earning his Ph.D. from Politecnico di Torino in 2009. His educational background includes: Ph.D. in Electronics and Communications Engineering, Politecnico di Torino (2009) Dr. Birke's research centers on systems-level challenges in distributed AI, with current projects investigating federated learning architectures, confidential computing via Trusted Execution Environments, and RISC-V processor optimizations for decentralized machine learning. His work bridges theoretical foundations with practical deployments, particularly in edge computing scenarios and high-performance data synthesis applications. Recent publications reveal growing emphasis on securing generative models against forgery attacks and optimizing tabular data synthesis techniques. Analysis of his 15 most recent publications (2024-2026) shows dominant themes in confidential federated learning (33% of works), RISC-V system optimizations (27%), and generative model security/synthesis (40%). This output spans premier venues including IEEE Transactions, ACM Computing Surveys, and SIGCOMM-affiliated conferences, demonstrating consistent contributions to systems-AI intersection research. Professional recognition includes: IEEE Senior Member While the text confirms extensive collaboration through co-authorships (notably with Marco Aldinucci, Lydia Chen, and Giulio Malenza), no specific student advisees or grant details are provided. His work appears embedded within European initiatives like ICS and EUPilot projects, focusing on compute continuum challenges. Dr. Birke actively contributes to the Parallel Computing group's mission through projects including HPC4AI@UNITO (datacenter digital twins) and Cross-Facility Federated Learning frameworks. His research ecosystem involves multi-institutional teams across Italy, Switzerland, and the EU, with recent talks addressing FLaaS implementations and generative model impacts on system design.

Paulo Garciaمشاهده پروفایل

استادیار

• Embedded Real-Time Systems
• Hardware/Software Co-Design
• FPGA Acceleration
• +۳ مورد دیگر

Paulo Garcia is an Assistant Professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa, Canada. He holds a Ph.D. in Computer Engineering from the University of Minho, Portugal, with research periods at Asian Institute of Technology and University of Würzburg. His academic roles include serving as a faculty member, thesis chair/examiner, and committee member in multiple university initiatives. Research Focus: Embedded real-time systems, hardware/software co-design, FPGA acceleration, and engineering pedagogy. Specific technical areas include multicore architectures, runtime systems, and hardware accelerators for embedded applications. His work emphasizes synergies between processor architectures, compilers, and FPGA-based solutions. Teaching: Courses include SYSC 3310 (Real-Time Systems), SYSC 4310 (Computer Architecture), and SYSC 5807 (Hardware/Software Co-Design). He supervises senior projects like robotic systems and eHealth wearable devices. Awards & Grants: Includes 2020 awards from General Dynamics Mission Systems and Carleton’s Rapid Response Grant, plus multiple scholarships from FCT Portugal and EU programs. His research has been supported by industry partnerships and defense collaborations. Service: Active in academic service as a thesis evaluator, member of student mental health committees, and representative in university governance bodies. Engaged in curriculum development and embedded systems program revisions.

• Computer Architecture
• Reconfigurable Computing
• Application Acceleration
• +۵ مورد دیگر

Professor Dionisios Pnevmatikatos holds the position of Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), where he leads research in Computer Architecture and Reconfigurable Computing. He previously served as a Professor at the Technical University of Crete (TUC) from 2000 to 2019, directing the Microprocessor and Hardware Laboratory (MHL) and chairing the department. His academic journey includes a B.Sc. from the University of Crete (1989), M.Sc. and Ph.D. from the University of Wisconsin-Madison (1991 and 1995). Research Interests: Focuses on Computer Architecture, Reconfigurable Computing, Application Acceleration, Custom Architectures, and Hardware Acceleration of Bioinformatics Algorithms. His work spans FPGA-based systems, parallel computing, and energy-efficient designs. Key Projects: Coordinator of FASTER (EU FP7), Principal Investigator in DeSyRe, AXIOM, dRedBox, and EDRAH2020 projects. Active in EU initiatives like H2020 OPTIMA and Vitamin-V for RISC-V ecosystems. Leadership roles in conferences include SAMOS 2018 and FPL 2011 program chairs. Teaching: Courses include Computer Architecture, Digital Systems Design, and Parallel Processing Systems at NTUA. Former roles include teaching at University of Crete and TUC. Labs: Affiliated with Computing Systems Laboratory (CSLab) at NTUA and FORTH-ICS since 1997. Involved in prototyping manycore architectures and network processors.

Anant Agarwalمشاهده پروفایل

استاد

• Computer Architecture
• Programming Languages and Software Engineering
• Systems and Networking
• +۴ مورد دیگر

Anant Agarwal is a Professor of Electrical Engineering and Computer Science at MIT, holding the rank of 'Professor Post-Tenure' in both CS and EE disciplines. He serves as CEO of edX, a leading platform for open online education. His primary affiliation is with the MIT Electrical Engineering & Computer Science Department within the MIT College of Engineering. Agarwal's research focuses on computer architecture, parallel processing, caching systems, and the integration of AI in clinical information systems. He has pioneered work on multicore processors, memory management, and self-optimizing computing systems. His academic contributions span over two decades, with notable advancements in tiled processor architectures, cache coherence protocols, and the design of energy-efficient embedded systems. Agarwal has been instrumental in developing MITx and edX, revolutionizing online education through scalable platforms like the 6.002x Circuits course. His work emphasizes blending traditional and digital learning modalities to enhance global access to education. Key research themes include parallel computing, machine learning applications in healthcare, and the future of higher education. His publications reflect a sustained focus on improving system performance, optimizing data management, and advancing educational technologies. Agarwal's leadership at edX underscores his commitment to democratizing access to world-class learning resources.

Rhett Davisمشاهده پروفایل

استاد

• 3D Integrated Circuits (3DIC)
• Low-Power Circuit Design
• High-Performance Circuit Design
• +۶ مورد دیگر

Dr. Rhett Davis is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University, where he has been since 2002. He holds a PhD from the University of California, Berkeley (2002), and earlier degrees from UC Berkeley and NC State. His research focuses on 3D integrated circuits (3DIC), low-power/high-performance circuit design, and CAD tools for emerging technologies. He leads the development of the FreePDK open-source process design kit, which has significantly advanced EDA standards. Education: PhD in Electrical Engineering, UC Berkeley, 2002 MS in Electrical Engineering, UC Berkeley, 1997 Bachelor's in Electrical Engineering, NC State, 1994 Research Interests: 3D-IC architectures and thermal management EDA tools for predictive design Embedded systems and signal processing Open-source PDK development Awards: NSF CAREER Award (2007) Si2 Distinguished Service Award (2012) Si2 Power of Partnerships Award (2020) Advising & Grants: Recipient of NSF CAREER grant Consultant for Qualcomm, BEECube, and Chameleon Systems Labs & Teams: Active in the FreePDK project and collaborates with Si2 on EDA standards.

Mohamed Zahranمشاهده پروفایل

استاد بالینی

• Parallel computing
• Heterogeneous architectures
• Hardware/Software interaction
• +۷ مورد دیگر

Mohamed Zahran is a Clinical Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2003) and has extensive experience in academia and industry, including roles at CUNY and The George Washington University. His research focuses on computer architecture, heterogeneous systems, parallel computing, and AI-driven hardware optimization. Education: Ph.D., Electrical and Computer Engineering, University of Maryland (2003); M.Sc., Cairo University (1999); B.Sc., Cairo University (1997). Research interests include exascale computing, GPU architectures, cache hierarchy design, and AI support for architecture. He has authored over 40 refereed papers and a book on heterogeneous computing. Awards include ACM Distinguished Speaker (2019–2025) and IEEE Distinguished Contributor (2021). Teaching: Courses on multicore processors, GPUs, parallel computing, and compilers. Advised numerous graduate and undergraduate students, including notable achievements in student research competitions.

Kunle Olukotunمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Computing
• Multicore Processors
• +۵ مورد دیگر

Kunle Olukotun is the Cadence Design Systems Professor of Electrical Engineering and Computer Science at Stanford University, where he has been a faculty member since 1991. He is a pioneer in multicore processor design, leading the Stanford Hydra CMP project and founding Afara Websystems (acquired by Sun Microsystems), which developed the Niagara processor. Currently, he co-leads SambaNova Systems as Chief Technologist and directs the Pervasive Parallelism Lab (PPL), focusing on domain-specific languages (DSLs) and machine learning infrastructure. Education: PhD in Computer Engineering from the University of Michigan (1991). Research interests include parallel computing architectures, transactional memory, and scalable systems. Awards include ACM Fellow, IEEE Fellow, and the Harry H. Goode Memorial Award. Key projects include the Hydra chip multiprocessor, Transactional Coherence and Consistency (TCC), and modern initiatives in dataflow architectures and AI acceleration. His work spans over 100 publications, emphasizing compiler design, hardware-software co-design, and high-performance computing. Current roles: Director of PPL and DAWN Lab, advisor to multiple students, and leader in industry collaborations like SambaNova’s dataflow accelerators. His research bridges academic innovation with commercial impact, addressing challenges in parallelism and scalable systems.

• High-Performance Computing
• Neuromorphic Engineering
• Bio-inspired Systems
• +۷ مورد دیگر

Pedro Filipe Zeferino Tomás is an Associate Professor at the University of Lisbon's College of Engineering, Department of Electrical and Computer Engineering. He is affiliated with INESC-ID research institute and teaches courses on Large Scale Computing, Computer Architecture, and High Performance Computing. His academic career includes a PhD in Neural Code modeling (2009), a Master's in DSP hardware structures (2006), and a Bachelor's in Bio-Inspired Artificial Retina design (2003). His research focuses on neuromorphic engineering, parallel computing architectures, and biosensing applications. Key areas include GPU optimization, transprecision arithmetic, neural prosthetics, and participatory urban biosensing. He has pioneered bio-inspired systems for visual neuroprostheses and developed energy-efficient hardware accelerators for machine learning. His recent work integrates biosensors into urban studies, exploring participatory methods for analyzing affective geographies and walkability. Over 60 peer-reviewed publications demonstrate his contributions to high-performance computing, neural modeling, and interdisciplinary urban technology. Grants: Multiple EU-funded projects in neuromorphic systems and urban biosensing Labs: Leads the Heterogeneous Computing Lab at INESC-ID and collaborates with neural engineering teams

• Embedded Systems
• Machine Learning
• Digital Signal Processing
• +۴ مورد دیگر

Prof. Gerold Bausch is a faculty member at HTWK Leipzig within the Faculty of Engineering . He leads the Electronic Engineering Lab (EEL) and serves as Coordinator for International Relations and Examination Board Member at HTWK Leipzig. His research focuses on Embedded Systems , Machine Learning , and Digital Signal Processing . Specializes in low-power embedded systems with ARM and RISC-V architectures Supervises thesis projects in collaboration with institutions like Fraunhofer-Institut and Max-Planck-Institut Developed innovative measurement systems for infrastructure monitoring Recent research trends include machine learning on microcontrollers , energy-autonomous sensor applications , and low-power wide-area networks . He has received prestigious awards such as the Actemium-Förderpreis and VDI Bezirksverein Leipzig Förderpreis . His work bridges academic research with industry applications through partnerships with companies like Siemens AG and ANDAV Electronics GmbH. Scientific Awards: Actemium-Förderpreis für Angewandte Digitalisierung (1st Prize) VDI Bezirksverein Leipzig e.V. Förderpreis (1st Prize) He supervises numerous Bachelor's and Master's students , guiding projects in embedded systems, signal processing, and biomedical technologies. His research emphasizes practical solutions for industrial challenges and environmental monitoring.

• Power Electronics
• Embedded Systems
• Software Testing
• +۳ مورد دیگر

Davide Piumatti is a Lecturer and Technical Services Coordinator at the Department of Control and Computer Science (DAUIN) , Polytechnic University of Turin . He actively contributes to teaching in Computer Engineering , Automotive Engineering , and Aerospace Engineering programs. Specializes in Power Electronics and Embedded Systems Focuses on Software Testing and Automotive Engineering Key interests: Digital Transformation and Public Administration Technologies His recent publications emphasize thermal modeling for power devices, multi-core testing in automotive systems, and reliability engineering . He contributes to IEEE conferences and journals like Microelectronics Reliability and Electronics . Piumatti is affiliated with the LABINF - Advanced Computer Science Teaching Laboratory (DAUIN) and collaborates with researchers such as Matteo Sonza Reorda and Francesco Angione . His work addresses fault detection , test library development , and cyber-physical system validation .

Wendy Chenمشاهده پروفایل

مدرس ارشد

• AI Acceleration with Photonic Computing and Communication
• Resource Optimization in Computer Systems/Networks/Architectures
• Parallel and Distributed Computing
• +۵ مورد دیگر

Dr. Yawen (Wendy) Chen is a Senior Lecturer at the University of New South Wales (UNSW Canberra campus) , affiliated with the School of Systems & Computing . She holds a PhD in Computer Science from the University of Adelaide and focuses on interdisciplinary research at the intersection of photonic computing, AI acceleration, and network optimization. Education: PhD in Computer Science (University of Adelaide) Her research spans computer networks/systems , parallel/distributed computing , photonic computing/communication , and AI-related education . Recent publications highlight advancements in optical network-on-chips (ONoC), energy-efficient protocols for WBANs, and hybrid electrical-photonic computing architectures. Dr. Chen actively recruits PhD and Master’s students with expertise in photonic computing, AI accelerators, and network optimization. She offers scholarships of $37,684 (AUD) for eligible candidates.

• Embedded Systems
• Computer Architecture
• Internet of Things (IoT)
• +۷ مورد دیگر

David Atienza is a Professor of Electrical and Computer Engineering at the Swiss Federal Institute of Technology Lausanne (EPFL), serving as Head of the Embedded Systems Laboratory (ESL) and Scientific Director of the EcoCloud Sustainable Computing Center. His academic credentials include: MSc in Computer Science and Engineering, Complutense University of Madrid (UCM), Spain (2001) Ph.D. in Computer Science and Engineering, Complutense University of Madrid (UCM), Spain, and IMEC, Belgium (2005) His research focuses on system-level design methodologies for high-performance multi-processor system-on-chip (MPSoC) and low-power Internet-of-Things (IoT) systems. Key specialties include 2-D/3-D thermal-aware design for MPSoCs and many-core servers, ultra-low power edge AI architectures for wireless body sensor nodes, HW/SW reconfigurable systems , dynamic memory optimizations, and network-on-chip design. This work drives innovations in sustainable computing and energy-efficient embedded systems. Dr. Atienza's accolades feature: ACM/IEEE ICCAD 10-Year Retrospective Most Influential Paper Award (2020) ACM/IEEE DAC Under-40 Innovators Award (2018) ERC Consolidator Grant for liquid-cooling 3D computing systems (2016) IEEE CEDA Early Career Award (2013) ACM SIGDA Outstanding New Faculty Award (2012) Sun Labs at Oracle Faculty Award (2011) He directs significant research initiatives including an ERC Consolidator Grant and mentors students through the Embedded Systems Laboratory. His leadership extends to editorial roles in premier journals and conference organization. Dr. Atienza heads the ESL and EcoCloud Center, driving collaborative research in sustainable computing, thermal-aware architectures, and edge AI with global industry partners to advance energy-efficient technologies.

• Quantum Technology
• Physics Education
• Semiconductor Devices
• +۳ مورد دیگر

I. Ercan is a Research Fellow at the Department of Electrical Engineering Education, Delft University of Technology. Their work bridges quantum technologies and physics education, focusing on innovative pedagogical approaches and semiconductor device modeling. University: Delft University of Technology Department: Electrical Engineering Education Research interests span quantum technology education, thermodynamic modeling of nanoscale devices, and the intersection of physics education with computational architectures. Key contributions include developing interactive tools for quantum outreach and analyzing efficiency limits in electron transport systems. Recent publications highlight their interdisciplinary approach: Quantum games and interactive Tools (2022) for educational outreach, Single-Electron-Transistor Compact Model (2023) for quantum hardware, and thermodynamic analyses of neural networks and Brownian circuits. Scientific Awards: Delft Education Fellowship (2023) DEWIS Advanced Scientist Award (2025) Ercan engages in public outreach initiatives, including STEM education programs for socioeconomically disadvantaged youth and diversity advocacy in academia.

Diana Marculescuمشاهده پروفایل

استاد

• energy-aware computing
• reliability-aware computing
• hardware aware machine learning
• +۱۰ مورد دیگر

Diana Marculescu is Department Chair, Cockrell Family Chair for Engineering Leadership #5, and Professor, Motorola Regents Chair in Electrical and Computer Engineering #2 at the University of Texas at Austin. She previously served as the David Edward Schramm Professor at Carnegie Mellon University, where she was Founding Director of the College of Engineering Center for Faculty Success (2015-2019) and Associate Department Head for Academic Affairs (2014-2018). Her educational background includes: Dipl.Ing. degree in computer science from Polytechnic University of Bucharest, Romania (1991) Ph.D. degree in computer engineering from University of Southern California, Los Angeles (1998) Dr. Marculescu's research bridges hardware design and machine learning, focusing on energy- and reliability-aware computing, hardware-aware machine learning, and computing for sustainability. She leads the EnyAC (ENergY Aware Computing) research group and founded the iMAGiNE Consortium for industry-university collaboration in engineering intelligent machines from cloud to edge. Her work addresses the critical need for efficient AI systems across diverse hardware platforms. Analysis of her recent publications reveals a strong trend toward hardware-efficient machine learning, with emphasis on neural architecture search, model compression, and energy-aware deep learning systems. Her research tackles the fundamental challenge of co-designing machine learning models and hardware to achieve optimal performance and efficiency. Dr. Marculescu has received numerous prestigious awards: National Science Foundation Faculty Career Award (2000-2004) ACM SIGDA Technical Leadership Award (2003) Carnegie Institute of Technology George Tallman Ladd Research Award (2004) IEEE Circuits and Systems Society Distinguished Lecturer (2004-2005) Australian Research Council Future Fellowship (2013-2017) Marie R. Pistilli Women in EDA Achievement Award (2014) Barbara Lazarus Award from Carnegie Mellon University (2018) Fellow of ACM, IEEE, and AAAS Dr. Marculescu has advised more than a dozen doctoral students, 35+ master students, and more than two dozen undergraduates. Her research has been supported by significant grants including the NSF Career Award and Australian Research Council Future Fellowship. She has served as Technical Program Chair and General Chair for multiple major conferences including ACM/IEEE International Symposium on Low Power Electronics and Design, IEEE/ACM International Symposium on Networks-on-Chip, and IEEE/ACM International Conference on Computer-Aided Design. She leads the EnyAC research group which focuses on sustainable computing and computing for sustainability, and founded the iMAGiNE Consortium to foster industry-university collaboration in engineering intelligent machines from cloud to edge.

Bakhrom Oripovمشاهده پروفایل

پژوهشگر ارشد

• Superconducting Single-Photon Detector Arrays
• Superconducting Electronics
• Neuromorphic Hardware
• +۳ مورد دیگر

Bakhrom Oripov is a Research Fellow at the University of Colorado Boulder , affiliated with the Quantum Nanophotonics Group , and a Researcher at the Applied Physics Division of the National Institute of Standards and Technology (NIST) in Boulder, Colorado. B.S. in Physics, Bogazici University, 2012 Ph.D. in Condensed Matter Physics, University of Maryland, 2020 His research focuses on Superconducting Single-Photon Detector Arrays , Superconducting Electronics , and Neuromorphic Hardware , with applications in UV astronomy , bio-optical devices , and energy-efficient AI . He develops scalable readout architectures for mega-pixel superconducting nanowire arrays and explores general training techniques for hardware neural networks . Recent publications highlight advancements in thermally coupled imager designs and gradient descent methods without backpropagation , emphasizing low-energy data routing and bio-inspired hardware scalability . His work has been featured in Nature and Applied Physics Letters as a Cover of the Issue and Featured Article .