جستجوی استاد راهنمای دانشگاهی

Zhidan Zheng is a researcher at the Technical University of Munich (TUM), working within the Chair of Electronic Design Automation led by Prof. Ulf Schlichtmann. His office is located in room 0509.05.911 at Arcisstr. 21, 80333 Munich, with direct contact available via email zhidan.zheng@tum.de and phone +49 (89) 289 - 23692. Zheng holds a Master of Science degree as indicated by his academic title M.Sc. and has been actively contributing to the field of optical interconnects and network-on-chip design. Zheng's research focuses on wavelength-routed optical networks-on-chip, with particular expertise in network topology optimization, fault tolerance mechanisms, waveguide routing algorithms, and bandwidth allocation strategies. His work addresses critical challenges in photonic integrated circuit design, including thermal variation effects, crosstalk mitigation, and lifetime extension for communication-intensive systems. Zheng has developed several innovative methodologies including ToPro+ for topology projection, LightR for fault-tolerant architectures, and WROXIM for network-level simulation. Analysis of Zheng's publication trends from 2021-2025 reveals a consistent focus on practical implementation challenges of optical networks-on-chip. His research has evolved from foundational topology design (Light, 2021) to increasingly sophisticated solutions addressing reliability (LightR, 2023) and comprehensive system integration (ToPro+, 2025). The work demonstrates strong collaboration with researchers including Mengchu Li, Tsun-Ming Tseng, and Ulf Schlichtmann across multiple high-impact venues including DAC, DATE, ICCAD, and ASP-DAC. Zheng actively contributes to the Electronic Design Automation research group at TUM, participating in projects related to analog EDA, emerging technologies, and optical networks. His research is situated within TUM's broader initiatives in photonic integration and high-performance computing architectures, working closely with Prof. Schlichtmann's team on funded projects in the optical NoC domain.

• Optical Networks-on-Chip
• Wavelength-Routed Optical Networks
• Electronic Design Automation
• +۴ مورد دیگر

Patrick H. Madden is an Associate Professor and Director of the MS Information Systems program at the School of Computing, Binghamton University. His research focuses on combinatorial optimization, VLSI physical design automation, and algorithmic solutions for NP-Hard problems. He is also involved in interdisciplinary work in cryptography and biology-related optimization. Education: BS and MS from New Mexico Institute of Mining and Technology PhD from University of California, Los Angeles (UCLA) Professional Roles: Chair of ACM/SIGDA (Design Automation Special Interest Group) Chair of Design Automation Conference (DAC) Sponsors Committee Advisor to Binghamton ACM Student Chapter Coach for ICPC Programming Contest Teams Member of Watson School Graduation Committee Research Contributions: Leads the Optimality Research Group, developing optimization algorithms for VLSI CAD and medical software applications. Notable contributions include the Feng Shui placement tool and medical reference apps for iOS/Android platforms. Awards: SUNY Chancellor's Award for Excellence in Professional Service (2015) Grants & Collaborations: Collaborates with Prof. Monte McCollum (Cinema Department) on hybrid cinema projects and Dr. Joshua Steinberg (Physician) on medical software. Active in ACM committees and EDA conferences (DAC, ICCAD, ISPD). Labs/Teams: Directs the Optimality Research Group and oversees medical software collaborations through CS441/580 projects.

• Combinatorial Optimization
• VLSI Design Automation
• Algorithms
• +۳ مورد دیگر

Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.

• CAD tools
• Digital architectures
• Emerging technologies
• +۹ مورد دیگر

Stephen Brown is a Professor at the University of Toronto within the Department of Electrical and Computer Engineering under the Faculty of Applied Science and Engineering. He earned his B.A.Sc and M.A.Sc in Electrical Engineering from the University of Toronto and New Brunswick, respectively, and a Ph.D. in Electrical Engineering from the University of Toronto (1992). His career spans over two decades in academia and industry collaboration. Education : B.A.Sc, University of New Brunswick M.A.Sc, University of Toronto Ph.D, University of Toronto Professor Brown’s research focuses on field-programmable gate arrays (FPGAs) , CAD algorithms , and computer architecture , with applications in machine learning and high-level synthesis . He is a principal investigator in the LegUp project , an open-source high-level synthesis framework that bridges software and hardware design. His work also extends to optimizing FPGA interconnect delays, physical synthesis, and logic block architectures. Key trends in his publications include advancements in high-level synthesis tools, FPGA architecture evaluation, and timing-driven design methodologies. His contributions often intersect with design automation , resource sharing , and embedded systems . Scientific Awards : NSERC 1992 Doctoral Prize Hart Professorship for Innovation in Teaching (2017) Multiple teaching excellence awards Best Paper Award at ICCAD 1990 Best Paper Award nomination at Canadian Conference on VLSI (1989) As Director of the FPGA University Program at Intel Corporation, he leads industry-academia initiatives. His teaching portfolio includes courses like ECE253 (Digital Logic) and ECE1733F (Switching Theory).

• Field-Programmable Gate Arrays (FPGAs)
• Computer Architecture
• CAD Algorithms
• +۴ مورد دیگر

Stefan Hougardy is a Professor at the Research Institute for Discrete Mathematics, part of the Mathematisch-Naturwissenschaftliche Fakultät at the University of Bonn. He is actively engaged in research and teaching, with a focus on discrete mathematics and combinatorial optimization. He contributes to academic governance through roles in examination boards, teaching mentoring, and faculty committees. Stefan Hougardy's research lies at the intersection of theoretical computer science and practical optimization. His primary interests include approximation algorithms, the Traveling Salesman Problem (TSP), Steiner trees, graph theory, and VLSI design automation. He develops efficient algorithms for NP-hard problems and analyzes their theoretical performance guarantees. His work often bridges theory and application, particularly in electronic design automation and mathematical programming. His recent publications demonstrate a strong focus on the complexity and approximation of combinatorial optimization problems. Key themes include the analysis of local search heuristics like k-opt for TSP, edge elimination techniques, fast matching algorithms, and optimal legalization in chip design. His work combines rigorous theoretical analysis with practical implementation and computational experiments. MPC 'Outstanding Paper of the Year' Award 2024 Stefan Hougardy supervises graduate students and leads seminars on discrete mathematics and optimization. He is involved in the Bonn International Graduate School of Mathematics and the Hausdorff Center for Mathematics, contributing to doctoral education and mentoring. While specific grant details are not listed, his sustained research output and leadership roles suggest active funding support. He also contributes to curriculum development and academic quality assurance through various institutional committees. He is affiliated with the Research Institute for Discrete Mathematics at the University of Bonn, a leading center for combinatorial optimization and algorithmic research. The institute is closely linked with the Hausdorff Center for Mathematics, fostering collaboration in discrete and applied mathematics.

• Discrete Mathematics
• Combinatorial Optimization
• Approximation Algorithms
• +۶ مورد دیگر

Dr Graeme Bragg is a Senior Teaching Fellow at the University of Southampton within the Department of Electronics and Computer Science . His work spans teaching, research, and technical development with a focus on event-driven computing, bioinformatics, and computational modeling. He actively supervises PhD students and collaborates on interdisciplinary projects. Research Interests: Parallel computing, event-driven systems, genotype imputation, Petri net simulations, subglacial hydrology modeling Teaching: Specializes in hardware description languages and computational methods for engineering students Technical Expertise: RISC-V architecture, FPGA acceleration, bespoke compute fabric development His recent publications demonstrate expertise in applying event-driven computing to diverse problems including: 2025: Automated marking systems for SystemVerilog labs 2025: Seasonal dynamics in subglacial hydrology 2023: Genotype imputation using custom hardware 2022: Optimization algorithms and graph analysis Current research explores: Custom RISC-V FPGA clusters for bioinformatics Event-triggered systems for scientific simulations Parallel computing solutions for molecular modeling Contact: gmb@ecs.soton.ac.uk | +44 23 8059 2784

• Parallel Computing
• Event-driven Systems
• Bioinformatics
• +۵ مورد دیگر

Alberto Macii is a Full Professor in the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin. He is also a member of the Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing and serves on two colleges: College of Computer, Film and Mechatronics Engineering and College of Mechanical, Aerospace and Automotive Engineering. His research interests include: Digital circuits and systems Electronic systems, modeling, and simulation Energy-efficient circuits and systems Energy management and battery systems Embedded systems and cyber-physical systems Low energy building technologies His work aligns with several Sustainable Development Goals including affordable and clean energy (Goal 7), industry innovation and infrastructure (Goal 9), and sustainable cities and communities (Goal 11). His publication record shows a consistent focus on energy efficiency in electronic systems spanning over two decades, with particular emphasis on battery modeling and power management. Recent work has expanded into environmental applications with transformer neural networks for flood forecasting, demonstrating the evolution of his research into new application domains while maintaining core expertise in energy optimization. His scientific awards include: Best paper award ACM/IEEE Great Lakes Symposium on VLSI (2008) IEEE Fellow (2007-) Senior Member IEEE He has served as Editor-in-Chief for the Journal of Embedded Computing (2005) and as Program Chair for EUC2005: Embedded & Ubiquitous Computing. Professor Macii has advised PhD students including Alberto Bocca (2019-2023) whose thesis focused on compact modeling techniques for energy analysis and optimization of complex systems. He has led numerous research projects including CANP (2018-2020), R3-PowerUP (2017-2021), SERENA (2017-2020), AMable (2017-2021), and STAMP (2016-2019), demonstrating sustained research leadership across multiple funding mechanisms. He is active in the EDA - Electronic Design Automation research group and LAB 4 research laboratory at DAUIN, with research spanning VLSI-CAD, Smart City technologies, and Industry 4.0 applications. His work bridges theoretical computer engineering with practical applications in energy conservation across multiple domains.

• Digital circuits and systems
• Electronic systems
• Modeling
• +۷ مورد دیگر

Andrea Costamagna is a researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL), working within the School of Computer and Communication Sciences and the Department of Communication Systems. His research focuses on logic synthesis, digital circuit design, and the intersection of machine learning with hardware implementation. His work includes optimizing digital circuits using techniques like resynthesis, resubstitution, and decomposition, with applications in FPGA design and low-power systems. Recent publications explore symmetry-based synthesis, glitch-aware power minimization, and the use of resistive switching devices in machine learning hardware. His research also extends to quantum physics modeling with deep learning.

• Logic Synthesis
• Digital Circuit Design
• Machine Learning
• +۳ مورد دیگر

Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.

• Computer Engineering
• Embedded Systems
• Hardware Acceleration
• +۵ مورد دیگر

Vidya A. Chhabria is an Assistant Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. She holds a Ph.D. and M.Sc. in Electrical and Computer Engineering from the University of Minnesota (2022, 2018) and a B.E. in Electronics and Communication Engineering from M.S. Ramaiah Institute of Technology (2016). Education Ph.D. Electrical and Computer Engineering, University of Minnesota (2022) M.S. Electrical Engineering, University of Minnesota (2018) B.E. Electronics and Communication Engineering, M.S. Ramaiah Institute of Technology (2016) Her research focuses on computer-aided design (CAD) for VLSI systems, particularly addressing physical design challenges through optimization and analysis algorithms. She also explores intersections between machine learning (ML) and electronic design automation (EDA), with emphasis on sustainable computing solutions. Scientific recognition includes the ICCAD Best Paper Award (2021), the University of Minnesota Graduate School's Best Dissertation Award (2024), and a Doctoral Dissertation Fellowship (2021). She mentors students through honors directed study, thesis supervision, and doctoral research courses (EEE 525 VLSI Design, EEE 598 Special Topics). Scientific Awards ICCAD Best Paper Award (2021) University of Minnesota Graduate School Best Dissertation Award (2024) Doctoral Dissertation Fellowship (2021) Her industry experience includes internships at Qualcomm (2017) and NVIDIA Research's ASIC VLSI Research Group (2020-2021). She maintains active research through the VLSI Design and Automation (VDA) Lab at ASU.

• Computer-aided design (CAD) for VLSI systems
• Machine learning (ML) for electronic design automation (EDA)
• VLSI design
• +۳ مورد دیگر

Professor Forrest Brewer is a faculty member in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB), affiliated with the College of Engineering. His research spans VLSI design, computer-aided design tools, and low-power computing, with a focus on unconventional engineering solutions. Education: PhD in Computer Science, University of Illinois BS in Physics (with honors), California Institute of Technology His work includes CMOS pulse-gate asynchronous logic for high-performance systems, sigma-delta modulation for signal processing, and formal verification strategies for asynchronous circuits. Applications range from radiation-hardened communication links for the Large Hadron Collider (LHC) to spiking neural networks for low-power computing in LIDAR/RADAR systems. Affiliations: California Nanosystems Institute Allosphere Steering Committee (Media Technology) With over 100 publications and 40 years of systems design experience, Brewer has contributed to defense programs, founded UCSB's Computer Engineering program, and served as Intel Faculty Fellow (1997). His lab, the Systems Synthesis Lab, explores collective dynamics and high-resolution, low-latency computation.

• VLSI Design
• Computer Engineering
• Electronic Design Automation
• +۷ مورد دیگر

Dr. Patrick W. C. Ho is a Lecturer in the Department of Electrical & Computer Systems Engineering (ECSE) at Monash University Malaysia School of Engineering. He holds a PhD in Electronics Engineering from the University of Nottingham Malaysia Campus (2016), with research focusing on non-volatile FPGA architectures using memristors. His academic journey includes roles as a Scholarly Teaching Fellow and unit coordinator for courses like ECE2131 Electrical Circuits and ECE4063 Large Scale Digital Design. He has industry experience with Intel Microelectronics and Altera Corporation, alongside teaching A-level Physics at Methodist College Kuala Lumpur. Education: BEng (First Class Honours) in Engineering (2009) MSc in Science (2012) PhD in Electronics Engineering (2016) Research Interests: Dr. Ho specializes in memristor-based non-volatile memory systems, VLSI design, and FPGA architectures. His work bridges hardware design with emerging materials, as seen in his Q1 journal article on memristive LUTs. Collaborations with CAD-IT expand his focus into AI, image processing, and object recognition. Recent projects include studies on memristor substrate performance (2023–2026) and UAV communication reliability (2021–2024). Teaching and Industry Engagement: As ECSE’s Industrial Training Advisor and IAP representative, he actively connects academic curricula with industry needs. His teaching spans foundational engineering courses and advanced digital design modules. Labs and Collaborations: Active in CAD-IT partnerships for student FYP co-sponsorship. Research groups focus on nanotechnology, machine learning integration in UAV systems, and memristor material analysis.

• Memristor
• Non-volatile memories
• VLSI
• +۷ مورد دیگر

Azadeh Davoodi is a Vilas Distinguished Achievement Professor and Associate Chair of Undergraduate Studies in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on Electronic Design Automation (EDA), integrated circuit debug, and machine learning applications in VLSI design. She holds editorial roles in journals like IEEE TCAD and ACM TRETS, and has chaired major conferences such as ISPD 2015 and served on technical program committees for DAC, ICCAD, and others. Education: PhD in Electrical Engineering, University of Maryland-College Park (2006) Research Interests: Machine learning for VLSI chip design VLSI design automation for machine learning IC-CAD for emerging nanotechnologies Hardware security Recent Research Trends: Her work bridges machine learning and hardware design, with publications on neural network optimization, distributed inference, and explainable AI for circuit design. She emphasizes energy-efficient CNNs, latency reduction in edge computing, and security in split manufacturing. Awards: 2025 DATE Best Paper Candidate 2024 Vilas Distinguished Achievement Professor 2015 ACM Best Paper Award 2011 NSF CAREER Award Service and Grants: Leads NSF-funded projects on explainable ML for CAD and holds grants for distributed neural network synthesis. Her service includes roles as IEEE HKN member and editorial board positions. Labs/Teams: Engages in interdisciplinary research teams at UW-Madison, focusing on EDA innovation and hardware-software co-design.

• Electronic Design Automation (EDA)
• Integrated Circuit Design
• Machine Learning in Hardware
• +۵ مورد دیگر

Pierre-Emmanuel Gaillardon is a Professor in the Department of Electrical & Computer Engineering and Adjunct Professor in the School of Computing at the University of Utah. He holds a joint appointment since July 2024, having previously served as Assistant Professor (2016–2019) and Adjunct Assistant Professor in Computing (2016–2019). His research focuses on FPGA design, VLSI systems, nanoelectronics, and hardware security. He leads projects in emerging devices like TIGFETs, compute-in-memory architectures, and radiation-hardened FPGA fabrics. Teaching includes courses on Digital VLSI Design, Embedded Systems Design, and thesis supervision. He has secured grants from NSF, DARPA, and industry partners totaling over $10M, addressing topics like FPGA redaction, neuromorphic systems, and environmental sensors. Notable awards include the NSF CAREER Award (2018) and IEEE Senior Member elevation (2016). He actively serves on IEEE committees for nanoelectronics and EDA tools, contributing to standards like OpenFPGA.

• FPGA Design
• VLSI Systems
• Logic Synthesis
• +۷ مورد دیگر

Tsung-Yi Ho is a Professor in the Department of Computer Science at National Tsing Hua University, Taiwan. He holds the Hans Fischer Fellowship at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). His primary research focuses on design automation for microfluidic biochips and nanometer integrated circuits, emphasizing reliability, optimization, and interdisciplinary applications in bioengineering. Ho received his Ph.D. in Electrical Engineering from National Taiwan University in 2005. He has held positions at National Cheng Kung University and National Chiao Tung University before joining National Tsing Hua University. His work bridges algorithmic design with practical biochip fabrication, addressing challenges like contamination control, routing optimization, and fault tolerance in microfluidic systems. His research interests span design automation for emerging technologies, including paper-based biochips and 3D microfluidic architectures. He has pioneered methods for integrating hardware-software co-design principles into biochip development, enhancing both functionality and reliability. His contributions include novel routing algorithms, contamination mitigation techniques, and reliability-aware synthesis frameworks. Ho has authored over 100 publications, including influential papers in IEEE Transactions on CAD and ACM journals. He serves on the editorial boards of multiple top-tier journals and chairs professional chapters for ACM and IEEE. His awards include the Humboldt Research Fellowship, Dr. Wu Ta-You Memorial Award, and Best Paper Awards at VLSI Test Symposium and IEEE Transactions on CAD. His current projects involve optimizing control-fluidic co-design for paper-based biochips and developing AI-driven frameworks for microfluidic functionality prediction. He collaborates widely, leading cross-disciplinary initiatives at TUM-IAS and Taiwan's academic institutions.

• Design Automation for Microfluidic Biochips
• Nanometer Integrated Circuits
• Embedded Systems
• +۳ مورد دیگر