جست‌وجوی استاد و پژوهشگر

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.

Douglas Densmoreمشاهده پروفایل

استاد

• Synthetic Biology
• Microfluidics
• Computer Architecture
• +۴ مورد دیگر

Roles and Affiliations: Douglas Densmore is a Professor of Electrical and Computer Engineering at Boston University, holding the Tegan Family Distinguished Faculty Fellowship. He leads the CIDAR Group and directs the Biological Design Center. His primary appointment is in the College of Engineering, with affiliations in Biomedical Engineering, Bioinformatics, and Materials Science & Engineering. He also serves as an affiliated PI in the Engineering Biology Research Center and NSF CELL-MET ERC. Education: He earned a PhD in Electrical Engineering from UC Berkeley (2007), following MS (2004) and BS (2001) degrees from UC Berkeley and the University of Michigan, respectively. His postdoctoral research included work at UC Berkeley and the Synthetic Biology Engineering Research Center (SynBERC). Research Interests: Densmore focuses on synthetic biology tools, microfluidics, and design automation. His work integrates electronic design automation (EDA) principles with biological systems to create high-level abstraction frameworks. Key areas include: Development of domain-specific languages for genetic circuit design Standardization of biological parts and data exchange Hardware-software-wetware co-design for synthetic systems Microfluidic platforms for high-throughput experimentation Awards and Recognition: He has received prestigious honors such as the AIMBE Fellowship (2021), Inaugural DAC Under-40 Innovators Award (2017), and NSF CAREER Award (2013). His contributions span academic, entrepreneurial, and editorial roles in synthetic biology. Grants and Labs: His research is supported by grants from NSF, NIH, DARPA, and industry partnerships. He leads the CIDAR lab, which combines computational and experimental approaches. He co-founded companies like Lattice Automation and Asimov, advancing bio-design automation commercially.

Andreas Venerisمشاهده پروفایل

استاد

• Computer Engineering
• Blockchain Technology
• Formal Methods
• +۴ مورد دیگر

Professor Andreas Veneris, currently at the University of Toronto , holds cross-appointments in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering , Department of Computer Science , and the Munk School of Global Affairs & Public Policy . He earned his Diploma in Computer Engineering from the University of Patras (1991), M.S. in Computer Science from USC (1992), and Ph.D. in Computer Science from UIUC (1998). AAAS ACM Fellow IEEE Fellow Professional Engineers of Ontario Technical Chamber of Greece Planetary Society NSERC COHESA Network Director His research spans two decades of CAD/VLSI design automation followed by blockchain technology focusing on CBDCs , smart contract verification , DeFi mechanisms , and techno-legal Web3.0 policy . Recent work includes ASTRAEA decentralized oracle , DeFi insurance protocols , and privacy-preserving CBDC architectures . Award highlights: ACM SIGSOFT Distinguished Paper (ICSE 2024) IEEE Best Paper Awards (2024, 2022, 2020) ACM SIGARCH Maurice Wilkes Award MICRO Hall of Fame He advises Ph.D. candidates in blockchain and machine learning while leading research sponsored by Ripple (UBRI) , Huawei , and IBM . His group develops value-based accelerators for deep learning and formal verification frameworks for smart contracts. Selected projects include: HEMVM (Interoperable Blockchain VMs) BAKUP (DeFi Insurance Protocol) SigVM (Event-Driven Smart Contracts) CnvluTin (Ineffectual Neuron-Free CNNs) Stripes (Precision-Variable DL Accelerators)

• Federated Learning
• Internet of Things
• Computer Architecture
• +۴ مورد دیگر

Erich Malan is a PhD Student in Computer and Systems Engineering (2022-2025) at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, where he also serves as an External Lecturer and Teaching Assistant. He holds an M.Sc. in Data Science and Engineering from the same institution (2021). His research focuses on developing efficient deep learning solutions for IoT networks, with expertise in: Distributed and federated learning optimization Communication efficiency for low-power IoT nodes Privacy-preserving techniques in edge computing Automated data annotation and security His publications concentrate on federated learning optimizations, featuring techniques like layer freezing, homomorphic encryption, and learning rate tuning to address challenges in edge computing environments. Awards include: Speaker recognition at IEEE ICECS 2024 Speaker recognition at IEEE ISLPED 2023 Teaching activities include serving as Course Collaborator for Computer Science courses in Aerospace Engineering and Computer Science Engineering programs. He conducts research with the Electronic Design Automation (EDA) Group at DAUIN.

Phuoc Hung Phamمشاهده پروفایل

استادیار مهمان

• Machine Learning
• Cloud Computing
• Optimization Algorithms
• +۴ مورد دیگر

Phuoc Hung Pham is a Visiting Assistant Professor in the Department of Computer Science at Providence College, contributing to both Computer Science and Mathematics & Computer Science programs. His research focuses on Machine Learning, Cloud Computing, Optimization Algorithms, and Physics-Informed Neural Networks. His recent work explores hybrid approaches for cloud scheduling, federated learning, and blockchain-based financial systems. Articles span topics like gradient descent optimization for EDA, unsupervised image-text fusion, and regional integration dynamics in ASEAN. Phuoc Hung Pham’s publications emphasize practical applications of machine learning in computational sciences and distributed systems, with no scientific awards or student advisement details provided in the available text.

Shawn Blantonمشاهده پروفایل

استاد

• Hardware Security
• Semiconductor Test and Diagnosis
• Data Mining for Integrated Systems
• +۳ مورد دیگر

Shawn Blanton is a Professor in the Electrical and Computer Engineering Department at Carnegie Mellon University's College of Engineering. He serves as the Associate Head of Research and founded the Advanced Chip Test Laboratory (ACTL) , focusing on data-mining techniques for secure and efficient integrated systems. Ph.D., Electrical and Computer Engineering, University of Michigan, Ann Arbor (1995) MS/BS in Electrical and Computer Engineering/Engineering, University of Arizona and Calvin College (1989) Blanton's research spans hardware security, semiconductor test methodologies, and machine learning applications in electronic design automation. He founded TestWorks, a CMU spinout analyzing IC test data, and co-founded the Security Assurance of Fabricated Electronics Center (SAFECENTER) under CyLab. His recent work includes the BRIDGE framework integrating graph models and large language models for EDA, published at the 2025 IEEE International Conference on LLM-Aided Design. His publications and patents reflect 30+ years of innovation in chip testing and security. NSF CAREER Award (1997) IBM Faculty Partnership Awards (2005, 2006) Lifetime Achievement in Academia Award (2022) Best Paper Award at GLSVLSI (2024) Blanton has delivered >100 invited talks across academia and industry, including Stanford, IBM, and Qualcomm, and held editorial/leadership roles in IEEE/ACM conferences and journals.

Mihailo Kneževićمشاهده پروفایل

استادیار

• Computer Engineering
• Integrated Circuit Design
• Computer Systems Engineering
• +۶ مورد دیگر

Mihailo Knežević is an Assistant Professor at the Department of Computer and Software Engineering within the Faculty of Technical Sciences in Čačak , part of the University of Kragujevac . His academic background includes completing Bachelor's and Master's studies in Electrical and Computer Engineering . Email: mihailo.knezevic@ftn.kg.ac.rs Office: Saint Sava 65, Čačak, Serbia Contact: +381 032/302-721 His research focuses on integrated circuit design , computer systems engineering , and application of neural networks . Key subfields include LoRa technology , open-source hardware tools , and scientific computing . Publications address topics like code analysis , EDA tools in education , and radiation detection simulations . Notable work includes studies on LoRa wireless technology for military and agricultural applications and democratization of IC design .

• Heterogeneous computing systems
• High-level synthesis (HLS)
• Hardware specialization for machine learning
• +۳ مورد دیگر

Zhiru Zhang is a Professor at Cornell University in the School of Electrical and Computer Engineering , leading research at the Computer Systems Laboratory . His work focuses on algorithms, methodologies, and design automation tools for heterogeneous computing systems. Recent publications emphasize high-level synthesis (HLS), hardware specialization for machine learning, and programming models for software-defined FPGAs. Education: Ph.D. in Computer Science, UCLA B.S. in Computer Science, Peking University M.S. in Computer Science, UCLA Research Interests: Heterogeneous computing systems High-level synthesis (HLS) optimization FPGA-based hardware acceleration Sparse data format compilers Machine learning for electronic design automation Scientific Awards: IEEE Fellow Intel Outstanding Researcher Award NSF CAREER Award DARPA Young Faculty Award Multiple Best Paper Awards at ASPLOS, ISPD, FPGA, AutoML, FCCM Research Group: Mentors 12 current students including Jordan Dotzel, Jie Liu, and Grace Dinh, with 14 alumni now at institutions like AWS AI, NVIDIA, Google DeepMind, and Microsoft. His lab develops tools like UniSparse for sparse format customization, presented at OOPSLA'24 and IEEE CAL.

Jiang Huمشاهده پروفایل

استاد

• Electronic design automation
• VLSI physical design
• Optimization of large computing systems
• +۵ مورد دیگر

**Jiang Hu** is a Full Professor of Electrical and Computer Engineering at Texas A&M University, holding a Hans Fischer Senior Fellowship at the Technical University of Munich (TUM-IAS). He earned his B.S. in Optical Engineering from Zhejiang University (1990), M.S. in Physics from the University of Minnesota (1997), and Ph.D. in Electrical Engineering (2001). Before joining Texas A&M in 2002, he worked at IBM Microelectronics. His research focuses on Electronic Design Automation (EDA), VLSI physical design, and hardware security, with notable contributions to machine learning-driven CAD tools and approximate computing architectures. **Education**: B.S., Optical Engineering, Zhejiang University (1990) M.S., Physics, University of Minnesota (1997) Ph.D., Electrical Engineering, University of Minnesota (2001) **Research Interests**: Jiang Hu's work bridges EDA and computer architecture, emphasizing optimization of large-scale computing systems. His projects include automated power modeling frameworks (e.g., APOLLO), neural network-driven placement algorithms, and security-enhanced dataflow architectures. He also explores plasmonic materials and perovskite solar cells through interdisciplinary collaborations. **Awards**: IEEE Fellow (2012) Alexander von Humboldt Research Fellowship (2011) Multiple best-paper awards at IEEE/ACM conferences (2003–2021) **Grants & Leadership**: He served as Technical Program Chair for ACM International Symposium on Physical Design (2011–2012) and co-chaired the ACM/IEEE Workshop on Machine Learning for CAD (2023). His research has led to 10 patents and supervision of 24 Ph.D. students. **Labs & Teams**: His group collaborates with TUM-IAS on projects like *A New and Scalable Methodology for Fast Machine Learning Accelerator Design*, advancing EDA tools for next-generation hardware systems.

• Formal Verification
• Machine Learning
• Computer Architecture
• +۸ مورد دیگر

Ziyad Hanna is a Visiting Professor at the University of Oxford's Department of Computer Science and currently serves as Corporate Vice President and R&D General Manager at Cadence Design Systems, leading their Israel-based formal verification research and development. He holds a PhD in Computer Science from the University of Oxford and has over 30 years of industrial experience in Electronic Design Automation (EDA), with leadership roles at Intel, Jasper Design Automation, and Cadence. Ziyad holds a B.Sc. and M.S. in Mathematics and Computer Science from Tel-Aviv University, and a PhD (DPhil) in Computer Science from the University of Oxford. His doctoral thesis focused on A Symbolic Execution Framework for Algorithmic-Level Modelling and Verification of Computer Microarchitecture . His research interests span Formal Verification methodologies, Machine Learning applications in verification, Computer Architecture, Software Engineering, Hardware Design, and Quantum Computing. He has pioneered advancements in formal equivalence checking, verification IP for chip design, and the integration of AI-driven techniques for bug localization and root-cause analysis. Red Herring Top 100 North America Company (2013) for Jasper Design Automation Intel's highest achievement award (IAA) - received twice Cadence move-the-needle award Israeli presidential award for community volunteering Ranked 39 in TheMarker’s 100 most influential people in Israel (2019) Listed in 'People and Computers' magazine's 2020 influential Hi-Tech list Ziyad has mentored numerous academic research projects and served on program committees for conferences such as FMCAD, SAT, and DAC. He leads a multinational R&D network across 10 centers and has driven Cadence's research agenda in formal verification and machine learning for EDA. His work has been supported by industry collaborations and institutional funding, including a 5-year initiative endorsed by Israel to advance Hi-Tech in the Arab community. He oversees Cadence Israel's advanced formal verification research group, the largest of its kind globally, and chairs the annual Jasper User Group (JUG) conference, a key industry event in formal verification.

Forrest Sheng Baoمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Electronic Design Automation (EDA)
• +۳ مورد دیگر

Forrest Sheng Bao is an Assistant Professor of Computer Science at Iowa State University (ranked 63rd in U.S. CS departments). His research focuses on AI, NLP, EDA, and medical data analytics. He holds a Ph.D. in Computer Science (with Electrical Engineering minor) from Texas Tech University (2012), followed by a postdoc at Stony Brook University. Previously, he served as an Assistant Professor at the University of Akron (2013–2017). His work is funded by NSF, FAA, AFRL, Microsoft, and others, with media coverage in MIT Technology Review and Lancet Neurology. Education: Ph.D., Computer Science (minor in Electrical Engineering), Texas Tech University, 2012 Postdoc, Stony Brook University (2012–2013) Research Interests: AI/ML, NLP (NLG metrics, review analysis), EDA (circuit routing, HDLs), medical signal/image processing (EEG/MRI). His publications span top conferences like ACL, NAACL, EMNLP, DAC, and DATE, with notable work in EDA using reinforcement learning and NLP metrics. He advises students on NLP and EDA projects, co-founding startups Funix.io and Codepod.io. His lab focuses on applying ML to PCB/IC design and biomedical applications. Awards: Best Paper Award at HPCC 2019, NSF grants totaling $462k. Teaching: Courses in NLP, Machine Learning, and Python. Actively mentors students through research and TA/RA opportunities. He engages in entrepreneurship (AI and hardware startups) and maintains active GitHub repositories for educational projects like PyEEG and Mercury.

• Analog IC Design
• Machine Learning
• Optimization Algorithms
• +۲ مورد دیگر

Nuno Horta is a researcher at Instituto de Telecomunicações specializing in electronic design automation. His work integrates machine learning with analog IC design, developing optimization methodologies for RF circuits and biomedical devices. Recent publications focus on neural network-based placement tools, millimeter-wave power amplifiers, and ultra-low-power wearable sensors. Collaborative projects include automated design flows for radiation-hardened space electronics and ANN-based yield optimization techniques. He co-leads research on AI-driven circuit synthesis and serves as reviewer for IEEE TCAS and Integration journals. Current NSF-funded projects explore physically integrated design concepts for additive manufacturing.

Simon Baleمشاهده پروفایل

مدرس ارشد

• Radio Frequency Engineering
• Electromagnetic Compatibility (EMC)
• Atomic Clocks and Oscillators
• +۳ مورد دیگر

Dr. Simon Bale is a Senior Lecturer and 4th year engineering project coordinator at the University of York’s School of Physics, Engineering & Technology. He holds a PhD in radio frequency electronics and microwave engineering (2012) from the same institution. His research focuses on oscillators/atomic clocks, electromagnetic compatibility (EMC), shielding, and bio-inspired optimization methods. He is a co-investigator on major projects such as the EPSRC-funded “Compact Quantum Clocks For Precise And Autonomous Position Navigation And Timing” and the EU’s “European Doctoral Network for Safe and Sustainable Electromagnetic Shielding Solutions for Mobility.” Teaching responsibilities include courses on electrical circuits, AC machines, power electronics, computer architectures, and embedded systems for FPGAs. His academic contributions span over 30 publications in top-tier journals and conferences, emphasizing practical applications in EMC testing, oscillator design, and evolutionary computation. He actively collaborates with industry partners like QinetiQ and Keysight, translating research into real-world solutions. Awards include Fellow of the Higher Education Academy (FHEA). His work bridges theoretical innovation and industrial needs, with a focus on optimizing electronic systems through multi-objective approaches. Ongoing projects explore ultra-low phase noise oscillators, shielding effectiveness measurement methodologies, and AI-driven circuit design optimization.

Rajit Manoharمشاهده پروفایل

استاد

• Asynchronous VLSI Design
• Concurrency
• Formal Methods
• +۵ مورد دیگر

Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.

• AI-driven electronic design
• Machine Learning
• Optimization techniques
• +۵ مورد دیگر

Bo Liu is a Professor of Electronic Design Automation at the University of Glasgow, specializing in AI-driven electronic design. He holds a B.Eng. from Tsinghua University (2008) and a Ph.D. from KU Leuven (2012). Previously, he was a Humboldt Research Fellow (2012–2013), Lecturer at Wrexham Glyndŵr University (2013–2020), and promoted to Reader (Associate Professor) in 2016 before joining Glasgow in 2020. Research focuses on AI-driven methodologies for analog ICs, antennas, and microwave systems. Key contributions include pioneering AI-assisted optimization in RF design and first industrial-use AI tools for mm-wave ICs. His work bridges machine learning and domain knowledge, addressing bottlenecks in electromagnetic simulations and antenna design complexity. He leads the AIDAC lab and collaborates with industry on EDA tools. Scientific awards include Fellow of IET and Senior Member of IEEE. He serves as an associate editor for IEEE Transactions on CAD and Complex and Intelligent Systems. Current research explores AI-driven design tools, including funded PhD projects on microwave filters, analog IC optimization, and 5G antennas.