Find Academic Supervisors

• High-speed data converters
• Wireless transceivers
• Digital phase-locked loops
• +7 more

Shiyu Su is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on high-speed data converters, wireless transceivers, digital phase-locked loops (PLL), and AI-assisted analog/mixed-signal design automation. He holds a Ph.D. from the University of Southern California (2019) and teaches courses such as ECE 340 (Electronic Circuits 2) and ECE 432 (Radio Frequency Integrated Devices and Circuits). Education: B.S. from Beijing University of Post and Telecommunication (China) and Queen Mary, University of London (UK), 2011; M.S. and Ph.D. from USC, 2013 and 2019, all in electrical engineering. Research Interests: High-speed ADCs/DACs RF/mm-wave transceivers Time-approximation filters (TAF) Analog/mixed-signal design automation Memristor-based computing Biomedical interfaces Key Awards: IEEE SSCS Predoctoral Achievement Award (2017–2018) Best Student Paper Award at IEEE RFIC (2022) Ming Hsieh Institute Scholar (2019–2020) Lab Focus: The Shiyu Su Lab develops integrated circuits for communications, sensing, and computing, with a focus on AI-driven methodologies and digital-analog co-design. Collaborations include work with Prof. Wei Wu (USC) on memristor-based systems.

• Combinatorial optimization
• Design and analysis of algorithms
• Field-programmable systems
• +7 more

Martin D F Wong serves as the Edward C. Jordan Professor of Electrical and Computer Engineering and Executive Associate Dean for the College of Engineering at the University of Illinois at Urbana-Champaign. He is affiliated with the Coordinated Science Laboratory and has been instrumental in advancing electronic design automation research. His educational background includes: B.Sc. in Mathematics, University of Toronto (1979) MS in Mathematics, University of Illinois at Urbana-Champaign (1981) Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (1987) Wong's research centers on combinatorial optimization and algorithm design for VLSI systems, with particular expertise in lithography-aware physical design, field-programmable systems, and electronic packaging. His work bridges theoretical algorithms with practical semiconductor manufacturing challenges as feature sizes shrink below 20 nanometers. Current research focuses on integrating chip design with next-generation lithography technologies including triple-patterning, self-aligned double patterning, directed self-assembly, and extreme ultraviolet processes. His publication record shows consistent contributions to electronic design automation, with emphasis on manufacturing-aware physical design algorithms and circuit optimization techniques. Recent work addresses the critical interface between circuit layout and lithography processes as semiconductor technology advances to 14nm and beyond. Scientific recognition includes: Fellow of IEEE and ACM 2000 IEEE Donald O. Peterson Best Paper Award Multiple Best Paper Awards at DAC, ICCD, and ICCAD conferences IBM Faculty Awards (2000, 2004) NSF Research Initiation Award Wong has secured significant research funding including a $450,000 NSF grant for lithography-aware physical design and has supervised over 49 PhD students. His work continues the legacy of integrated circuit innovation at Illinois, building on foundational contributions like Jack Kilby's integrated circuit invention. Current research initiatives focus on optimizing chip design for next-generation manufacturing processes where optical interference challenges require co-design of layout and fabrication. He leads research within the Coordinated Science Laboratory, focusing on electronic design automation algorithms that address the growing complexity of semiconductor manufacturing at nanometer scales.

Jason H. AndersonView profile

Professor

• Computer Engineering
• Electrical Engineering
• Computer-Aided Design (CAD)
• +3 more

Professor Jason H. Anderson is a faculty member in the Department of Electrical & Computer Engineering (ECE) at the University of Toronto, affiliated with the Faculty of Applied Science & Engineering. He specializes in computer engineering, with a focus on field-programmable gate arrays (FPGAs) and related computer-aided design (CAD) tools. BSc in Computer Engineering from the University of Manitoba MASc and PhD in Electrical & Computer Engineering from the University of Toronto His research spans FPGA architecture, circuit design, and CAD tool development. He has contributed to strategic R&D projects through his academic and industry roles. Scientific awards include multiple Best Paper Awards at IEEE and ACM conferences (2017, 2014, 2011, 2010, 2009), the Xilinx Ross Freeman Award (2000), and teaching accolades such as the Gordon Slemon Award (2012) and several ECE Departmental Teaching Awards (2009-2014). He served as General Chair and Program Chair for leading FPGA conferences. As Chief Scientific Advisor and Co-Founder of LegUp Computing Inc., he bridges academic research with industry innovation. He is a licensed Professional Engineer in Ontario and an active IEEE/ACM member.

Wenjing RaoView profile

Associate Professor

• VLSI Test
• Fault-Tolerance
• Reliability
• +3 more

Wenjing Rao is an Associate Professor at the Department of Electrical and Computer Engineering, College of Engineering, University of Illinois at Chicago (UIC). Her research focuses on VLSI test, fault-tolerance, reliability, and hardware security in emerging nanoelectronic systems. Education: Ph.D. in Computer Science from University of California, San Diego (2008) B.S. in Computer Science from Peking University (2001) Her work explores novel computation paradigms through physical unclonable functions (PUFs), defect-tolerant logic implementation, and scalable fault tolerance in many-processor arrays. Publications emphasize hardware security, reconfiguration strategies, and reliability challenges in nanoscale architectures. Notable honors include the 2017 Harold A. Simon Award for Excellence in Teaching and the 2012 NSF CAREER Award. She has contributed to key journals like IEEE Transactions on Computer-Aided Design and conferences including DATE, ASPDAC, and NANOARCH.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +7 more

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

David Zhigang PanView profile

Professor

• Electronic Design Automation
• Machine Learning
• Hardware Acceleration
• +5 more

David Zhigang Pan is a Professor in the Department of Electrical & Computer Engineering at The University of Texas at Austin. He also holds the Silicon Laboratories Endowed Chair. Prior to joining UT Austin, he was a Research Staff Member at IBM T. J. Watson Research Center from 2000 to 2003. His academic journey began with a B.S. from Peking University, followed by M.S. and Ph.D. degrees from UCLA. Research Areas: Electronic Design Automation (EDA), Machine Learning Hardware, FPGA Prototyping, Optical Computing, Hardware Security, and CAD for Emerging Technologies Academic Timeline: Assistant Professor (2003-2008), Associate Professor (2008-2013), Full Professor (2013-present) His research focuses on design automation for mixed-signal circuits , GPU-accelerated EDA tools , and hardware-software co-design for AI . Recent work explores FFT-based optical neural networks and deobfuscation techniques for integrated circuits , reflecting his interdisciplinary approach at the intersection of machine learning , computer architecture , and semiconductor manufacturing . Key publication trends reveal expertise in: VLSI design , lithography optimization , and deep learning applications for EDA tools. His work has been recognized with multiple Best Paper Awards at top conferences including DAC , ASP-DAC , and HOST . Awards: IEEE Fellow (2014), SPIE Fellow (2017), ACM SRC Graduate Category Honors for students Patents: 8 U.S. Patents in electronic design and hardware optimization Prof. Pan has mentored 40 PhDs and postdocs who now hold key positions in academia and industry. He leads research initiatives involving GPU acceleration frameworks and optical computing architectures . His lab focuses on vertical integration of architecture, CAD tools, and fabrication technologies for next-generation hardware solutions.

Serdar ÖzoğuzView profile

Professor

• Active RC Filters
• Nonlinear Electronic Circuits
• Analog IC Design
• +3 more

Professor Serdar Özoğuz is a full faculty member at the Department of Electronics and Communication Engineering , Istanbul Technical University . Holding a Ph.D. from ITU (2000) and a M.Sc. from ITU (1993) , he has taught courses like Active Network Synthesis , Basics of Electrical Circuits , and Scientific Research Ethics since 2014. His research focuses on Active RC filters Nonlinear electronic circuits Analog integrated circuit design Network synthesis . His recent publications emphasize machine learning applications in RF/microwave design , quantum computing for CAD tools , and emerging memory devices . The department's Devreler ve Sistemler Laboratuvarı Çok Geniş Ölçekli Tümdevre (VLSI) Tasarımı Laboratuvarı likely support his work. Despite no explicit awards listed, his 15+ recent articles in high-impact journals underscore his technical contributions.

Giovanni De MicheliView profile

Professor

• Computer Architecture
• Electrical Engineering
• Integrated Systems
• +5 more

Giovanni De Micheli is a Professor of Electrical Engineering and Computer Science at EPF Lausanne, Switzerland. He also serves as Director of the Integrated Systems Centre and the Institute of Electrical Engineering at EPFL, and chairs the Scientific Committee of CSEM in Neuchatel. Previously, he held academic roles at Stanford University for 18 years, including Full Professor, Associate Professor, and Assistant Professor in the Department of Electrical Engineering. His research spans synthesis of digital circuits, hardware/software co-design, low-power design, and Networks on Chip (NoC) technology. 2003: IEEE Emanuel Piore Award 2000: Golden Jubilee Medal of the IEEE CAS Society 2000: ACM Fellow 1994: IEEE Fellow 1990: IEEE/CS Distinguished Service Award 1988: NSF Presidential Young Investigator Award His seminal contributions include pioneering C-based synthesis and Boolean matching algorithms for digital circuits, foundational work in dynamic power management using stochastic control, and the development of Network-on-Chip (NoC) technology. His publications, such as "Networks on Chips: A New SoC Paradigm" and "Dynamic Power Management for Portable Systems" , have shaped modern SoC design practices. With over 400 technical articles, 9 books, and an H-index of 56, his work remains highly influential.

• Electrostatic Discharge (ESD) Protection
• Semiconductor Device Modeling
• RF Circuit Design
• +3 more

Prof. Juin J. Liou serves as the UCF Pegasus Distinguished Professor and Lockheed Martin St. Laurent Professor of Engineering in the Department of Electrical and Computer Engineering at the University of Central Florida, where he has held faculty positions since 1987. Education: B.S. (Honors) in Electrical Engineering, University of Florida, 1982 M.S. in Electrical Engineering, University of Florida, 1983 Ph.D. in Electrical Engineering, University of Florida, 1987 Research Focus: Prof. Liou specializes in Electrostatic Discharge (ESD) protection systems critical for integrated circuit reliability, semiconductor device modeling, and RF circuit design. His pioneering work addresses ESD challenges in next-generation technologies including silicon nanowire, organic semiconductors, and gallium nitride (GaN) devices, where miniaturization intensifies vulnerability to electrostatic damage. His research bridges theoretical modeling with practical implementation to solve industry-critical protection failures. Awards and Leadership: Ten teaching/research excellence awards from University of Central Florida Six major awards from IEEE IEEE-EDS Distinguished Lecturer Multiple honorary professorships Research Impact: Secured over $14.5 million in funding from NSF, DARPA, NASA, NIST, and semiconductor industry leaders including Intel, Texas Instruments, and Analog Devices. Authored 10 books, 270+ journal papers (18 invited reviews), and 220+ conference papers while holding 8 U.S. patents (4 pending). Served as IEEE EDS Vice-President, Treasurer, and Board of Governors member, plus editorial roles for Microelectronics Reliability and IEEE journals.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +5 more

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

Gary GrewalView profile

Associate Professor

• Computer-Aided Design (CAD) Tools
• Field Programmable Gate Arrays (FPGAs)
• Machine Learning
• +5 more

Gary Grewal is an Associate Professor at the School of Computer Science , University of Guelph. His research focuses on developing intelligent Computer-Aided Design (CAD) tools for Field Programmable Gate Arrays (FPGAs) , integrating classical optimization techniques with machine learning and deep learning to address challenges in placement and routing for heterogeneous devices. He has received the Michal Servit Award (2017, 2018) for outstanding FPGA research and the University of Guelph Faculty Association Distinguished Professor Award for Excellence in Teaching (2017) . Grewal has held NSERC Discovery Grants annually from 1999 to 2023. Co-founder of the Guelph FPGA CAD Group Key collaborator with institutions like Ryerson University , University of Toronto , and University of British Columbia His work extends to health technology through the IronTracker mobile app , developed with Andrew Hamilton-Wright and students (A. D'Angelo, J. Carter, F. Liu, R. Pattison) to manage Hereditary Hemochromatosis (HHC) . The app, available in four languages and adopted in 100+ countries, was recognized at Parliament Hill and the Ontario Legislature. Scientific Awards : Michal Servit Award (2018) Michal Servit Award (2017) Distinguished Professor Award for Teaching (2017) NSERC Discovery Grants (1999-2023) His recent publications highlight trends in machine learning for FPGA CAD , including reinforcement learning for partitioning, deep learning for congestion estimation, and adaptive algorithms for placement. Grewal remains active in teaching courses like Discrete Optimization (CIS*6070) and Digital Systems I (CIS*3120).

Luca SterponeView profile

Professor

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +7 more

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

Azadeh DavoodiView profile

Professor

• Electronic Design Automation (EDA)
• Integrated Circuit Design
• Machine Learning in Hardware
• +5 more

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.

Luca BeniniView profile

Professor

• Embedded Systems
• Low Power Design
• System-on-Chip
• +7 more

Luca Benini is a Full Professor of Electronics at the University of Bologna's Department of Electrical, Computer and Systems Engineering. He also holds a Visiting Faculty Position at the Ecole Polytechnique Federale de Lausanne (EPFL) and serves as Chief Architect of the Platform 2012 project at STMicroelectronics in Grenoble, France. His educational background includes academic positions progressing from Assistant Professor (1998) to Associate Professor (2001) and finally Full Professor (2006) at the University of Bologna. He has held significant industry positions including IC Architecture and CAD Engineer at Integrated Information Technology Inc. (1994), Senior Member of R&D Staff at Synopsys Inc. (1996), and Visiting Researcher at Hewlett Packard Laboratories (1997-2004). Professor Benini's research focuses on designing systems for ambient intelligence, spanning multi-processor systems-on-chip, networks on chip, and energy-efficient smart sensors and sensor networks. His work has expanded into biochips for biological molecule recognition, bioinformatics, and advanced algorithms for in-silico biology. His expertise in low-power design of integrated circuits and systems earned him IEEE Fellow status in 2007. He has received multiple honors including best paper awards at IEEE GLS-VLSI and the European Wireless Sensor Networks Conference (both 2008), with three of his papers featured in 'Design Automation and Test in Europe - The Most Influential Papers of 10 Years' (Springer 2008). IEEE Fellow (2007) for contributions to design technologies for low power design Member of ARTEMISIA Steering Board (elected twice) Member of European Design and Automation Association Main Board Member of MEDEA+ EDA roadmap committee Member of EC Advisory group on Computing Systems Benini has held significant leadership roles in the academic community, serving as General Chair of the IEEE/ACM Design Automation and Test in Europe Conference (2009), DATE Program Chair (2005), and Program Chair for multiple specialized symposia. He serves as associate editor for several prestigious journals including IEEE Transactions on Computer-Aided Design and ACM Transactions on Embedded Computing Systems, and has organized influential workshops like the Dagstuhl Seminar on Power-Aware Computing Systems.

Andy YeView profile

Associate Professor

• Field-programmable gate array (FPGA) architectures
• Computer-Aided Design (CAD) tools for FPGAs
• Logic synthesis
• +5 more

Dr. Andy Ye is an Associate Professor in the Department of Electrical, Computer, and Biomedical Engineering at Ryerson University, where he conducts research and teaches courses in advanced digital systems. Education : PhD (2004), MASc (1999), and BASc (1996) from the University of Toronto Research Interests focus on: Field-programmable gate array (FPGA) architectures Computer-Aided Design (CAD) tools for FPGAs and VLSI Logic synthesis and hardware implementation Digital communication algorithms and computer vision systems Publication Trends demonstrate expertise in FPGA area modeling, motion estimation architectures, and VLSI design optimization across multiple IEEE and ACM venues. Scientific Achievements : Best Paper Award (2016) at International Conference on Field Programmable Logic and Applications Teaching Contributions include graduate-level FPGA design (EE 8219), low-power digital circuits (ELE 734), and fundamental network theory (ELE 302). He maintains active supervision availability for students.