جست‌وجوی استاد و پژوهشگر

Andrew Childsمشاهده پروفایل

استاد

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +۲ مورد دیگر

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

Callie Haoمشاهده پروفایل

استادیار

• Software/Hardware Co-design
• Reconfigurable Computing
• Graph Computing
• +۵ مورد دیگر

Callie Hao is an Assistant Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology since 2021, holding the ON Semiconductor Junior Professorship. Her research bridges hardware efficiency and algorithmic innovation with significant industry and federal recognition. Education: Ph.D. in Electrical Engineering, Waseda University (2017) M.S. and B.S. in Computer Science and Engineering, Shanghai Jiao Tong University Research Focus: Dr. Hao pioneers software/hardware co-design for edge AI, specializing in hardware-efficient machine learning algorithms, FPGA-based reconfigurable computing, graph neural networks, and electronic design automation (EDA). Her work emphasizes neural architecture search, high-level synthesis optimization, and memory-efficient systems for embedded and IoT applications, driven by the philosophy that "1 + 1 > 2" for transformative efficiency gains. Publication Impact: Her 15 most recent publications (2023-2026) reveal a strategic shift toward machine learning-driven EDA tools, with 60% focused on high-level synthesis frameworks and 40% on graph neural network acceleration. Key trends include simulation speed breakthroughs (LightningSim), automated accelerator generation (GNNBuilder), and cryptographic hardware innovations (Cryptonite), predominantly published in top-tier venues like MICRO, ICCAD, and DAC. Awards & Recognition: NSF CAREER Award (2024) and Intel Rising Star Faculty Award (2023) Best Paper Awards at MLCAD 2024 and GLSVLSI 2021 ON Semiconductor Junior Professorship (2025) and Sutterfield Family Early Career Professorship (2022) DAC-SDC competition championships (2018-2020) Mentorship & Funding: Dr. Hao advises 8+ Ph.D. students in the Sharc Lab, with Rishov Sarkar winning the Oscar P. Cleaver Award and Qualcomm Innovation Fellowship. Her research is funded by DARPA (2021) for ultra-light video intelligence systems and supported by industry awards from Amazon and Sony. She actively serves on program committees for DAC, ICCAD, and DATE conferences. Lab Leadership: As director of the Sharc Lab (Software/Hardware Co-design lab), she cultivates interdisciplinary research at the intersection of FPGA design, machine learning, and EDA, requiring expertise in Verilog/HLS, GNNs, and compiler technologies while maintaining strict focus on real-world hardware implementation.

Andrea Fumagalliمشاهده پروفایل

استاد

• Optical Networking
• Photonic Slot Routing
• Wavelength Routing and Protection
• +۷ مورد دیگر

Andrea Fumagalli is a Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science , The University of Texas at Dallas. He earned his Ph.D. (1992) and Laurea (1987) in Electrical Engineering from Politecnico di Torino, Italy. Research Interests: All-Optical Network Architectures, Photonic Slot Routing, Wavelength Routing and Protection, Sensor Networks, Cooperative Wireless Networks, Network Optimization, Next Generation Internet (NGI), and Multi-hop Optical Networks. Education: Ph.D., Electrical Engineering, Politecnico di Torino (1992) Laurea, Electrical Engineering, Politecnico di Torino (1987) Key Research Trends: His recent publications focus on 5G networking, optical network automation, elastic optical networks, network reliability, and cross-layer optimization. He explores FPGA acceleration in 5G Low-PHY functions, live migration of containerized network components, and spectral fragmentation mitigation in EONs. Scientific Awards: Best Teaching Award, Electrical Engineering, UTD (2002) Best Thesis Award for Ph.D. Advisee Isabella Cerutti (2002) IEEE ComSoc Distinguished Lecturer Tour (2000) Best Paper Award (1999): 'An Optimal Design Algorithm for Photonic Slot Routing Networks Migrating to Optical Packet Switching' Advising and Grants: He advised Ph.D. student Isabella Cerutti. In 2001, he secured a $300,000 grant from FUNDACAO CPqD for optical network reliability research. He leads the Optical Networking Advanced Research (OpNeAR) Lab at UTD, collaborating on international projects like the Italian government-funded grid computing initiative (2002) and the OMEGA Test-bed for differentiated reliability. Laboratories and Teams: He directs the OpNeAR Lab , which develops tools for optical network emulation and reliability testing. His projects involve partnerships with institutions in Brazil (Unicamp), Sweden (KTH), Italy (Politecnico di Torino, Scuola Superiore Sant'Anna), and CNR/CNIT.

Yiorgos Makrisمشاهده پروفایل

استاد

• Hardware Security
• Trusted Systems
• Machine Learning in Semiconductor Manufacturing
• +۹ مورد دیگر

Yiorgos Makris is a Professor in the Department of Electrical and Computer Engineering at the Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas, since July 2011. Previously, he was a faculty member at Yale University for over a decade. He holds a Ph.D. in Computer Engineering from the University of California, San Diego, and a Diploma in Computer Engineering from the University of Patras, Greece. Education: Ph.D. in Computer Engineering, University of California, San Diego (2001) M.S. in Computer Engineering, University of California, San Diego (1997) Diploma in Computer Engineering and Informatics, University of Patras, Greece (1995) Research Interests: Hardware Security and Trustworthiness Statistical Side-Channel Fingerprinting Machine Learning in Semiconductor Manufacturing Trusted and Reliable Integrated Circuits Hardware Trojans in Wireless Cryptographic ICs On-Die Learning and Emergent Technologies His work focuses on enhancing hardware security through statistical methods, machine learning, and formal verification, with applications in analog/RF ICs, post-production calibration, and secure IC design. Key Contributions: Co-Founder and Site-PI of NSF CHEST I/UCRC (Hardware and Embedded System Security and Trust) Leader of the Safety, Security, and Healthcare Thrust at TxACE (Texas Analog Center of Excellence) Director of the Trusted and RELiable Architectures (TRELA) Lab Grants and Funding: NSF, NIH, SRC, ARO, AFRL, AFWERX, DARPA, DOE, and industry partnerships with Boeing, Northrop Grumman, IBM, Intel, Qualcomm, etc. Recent grants include projects on DNA storage security, analog neural networks, and malicious hardware detection. Awards and Recognition: IEEE Fellow (2025) Best Paper Awards at DATE'13, VTS'15, DCAS'22 Best Hardware Demonstration Awards at HOST'16 and HOST'18 Erik Jonsson School Faculty Research Award (2020) Labs and Teams: TRELA Lab (Focus: Secure Hardware Design, Trusted Architectures) CHEST I/UCRC (Industry-University Collaboration)

Uwe Meyer-Baeseمشاهده پروفایل

دانشیار

• Digital Signal Processing
• FPGA Design
• VLSI Systems
• +۴ مورد دیگر

Uwe Meyer-Baese is an Associate Professor in the Electrical and Computer Engineering Department at the FAMU-FSU College of Engineering. He holds a Ph.D. (Dr.-Ing. habil) from Darmstadt University of Technology, Germany. His research focuses on Digital Signal Processing with FPGAs, VLSI design, and medical imaging applications. He has authored over 100 publications, 5 books, and holds 3 patents. He has been recognized with awards such as the Humboldt Fellowship (2009) and the FAMU-FSU Teaching Award (2007). Education History: Dr.-Ing. habil (Venia Legendi), Darmstadt University of Technology, Germany, 2003 Ph.D. (Dr. Ing.), Darmstadt University of Technology, Germany, 1995 M.S., Darmstadt University of Technology, Germany, 1989 Research Interests: FPGA-based embedded systems and real-time DSP Low-power VLSI architectures Medical image processing (e.g., breast MRI, brain tumor analysis) Hardware security and intellectual property protection Graph theory applications in biological networks Recent work includes advancements in FPGA implementations for microprocessor systems, brain network controllability studies, and AI-driven medical diagnostics. His lab focuses on bridging hardware design with biomedical applications, emphasizing practical implementations through FPGA platforms. Awards: Max-Kade Award in Neuroengineering (1997) ECE Department Research Award (2005) Humboldt Fellowship (2009) FAMU-FSU Teaching Award (2007) He has advised over 60 master’s theses and contributed to major grants in FPGA-based medical systems. His book Digital Signal Processing with Field Programmable Gate Arrays is a widely used textbook in the field.

Dejan Markovicمشاهده پروفایل

استاد

• Implantable neuromodulation systems
• Domain-specific compute architectures
• Design methodologies
• +۳ مورد دیگر

Dejan Markovic is a Professor of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), holding the Mukund Padmanabhan Term Chair in Electrical Engineering and serving as Area Director for Circuits and Embedded Systems. His research spans implantable neuromodulation systems, domain-specific compute architectures, and energy-efficient design methodologies for biomedical and embedded applications. Dr. Markovic earned his PhD (2006) and MS (2000) from UC Berkeley and BS (1998) from the University of Belgrade, Serbia. His research focuses on ultra-low-power integrated circuits for neural interfaces, including artifact-free stimulation/sensing platforms and neural recording front-ends, alongside domain-specific architectures for sparse linear algebra in IoT and mobile computing. Recent work demonstrates strong trends in medical neuromodulation and energy-efficient VLSI for biomedical signal processing and wireless communications. His scientific contributions have been recognized with prestigious awards including IEEE Fellow (2021), ISSCC Lewis Award (2014), ISSCC Jack Raper Award (2010), and NSF CAREER Award (2009). Additional honors include UC Berkeley's David J. Sakrison Memorial Prize (2007) and multiple best paper awards. Dr. Markovic co-founded semiconductor IP startup Flex Logix Technologies (2014) and leads the DMGroup research lab at UCLA. He teaches core courses including ECE 115C (Digital Integrated Circuits), ECE M216A (VLSI Design), and BME M260 (Neuroengineering), mentoring students in cutting-edge VLSI design for medical and communication applications. The DMGroup lab specializes in developing implantable neuromodulation systems, domain-specific compute engines, and novel design methodologies, with recent projects featured in UCLA's coverage of brain-computer interface technology and Anari AI's $2M funding for personalized AI hardware.

Zihe Gaoمشاهده پروفایل

استادیار

• Optics
• Integrated Photonics
• Quantum Optics
• +۵ مورد دیگر

Zihe Gao serves as a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering since August 2023, following postdoctoral research at the University of Pennsylvania and industry experience at Meta (Facebook Reality Labs). His academic foundation includes: PhD in Electrical and Computer Engineering, University of Illinois Urbana-Champaign (2018) MS in Physics, University of Illinois Urbana-Champaign (2012) BS in Physics, Nanjing University (2011) Dr. Gao's research integrates optics, microelectronics, and physics to develop programmable photonic systems. His work focuses on controlling collective behaviors in multi-element photonic systems for scalable integrated chips, with applications spanning dynamically steerable laser sources and reconfigurable quantum optical platforms . Key methodologies include non-Hermitian physics, topological photonics, and spin-orbit coupling engineering. Analysis of his 2023-2025 publications reveals dominant trends in non-Hermitian photonic switching , high-dimensional quantum state manipulation , and topological semiconductor laser arrays . His team pioneers lithography-free reconfigurable photonics and spin-orbit microlasers for quantum key distribution, demonstrating strong industry-academia translation from prior Meta work on AR/VR structured-light systems. His scholarly trajectory shows continuous progression from VCSEL array fundamentals (PhD under Prof. Kent Choquette) to quantum-topological photonics (postdoc with Prof. Liang Feng), now establishing independent research at Auburn with emphasis on integrated quantum-classical hybrid systems.

Nicholas Wrightمشاهده پروفایل

پژوهشگر

• High Performance Computing (HPC)
• Computer Architecture
• Performance Analysis
• +۵ مورد دیگر

Nicholas Wright serves as the NERSC Chief Architect and Advanced Technologies Group Lead at Lawrence Berkeley National Laboratory's National Energy Research Scientific Computing Center (NERSC) since 2009. He holds a PhD in Chemistry from the University of Durham, United Kingdom. Role: Focuses on evaluating emerging technologies for scientific computing Key Contributions: Chief architect for NERSC-10 procurement (2026), optimized Perlmutter machine architecture His research explores performance analysis of HPC applications and architectural evaluation for future technologies. Recent publications address: GPU frequency optimization using DNN-based models FPGA acceleration for HPC workloads Quantum computing cost scaling Disaggregated memory system evaluation Scientific workflow characterization Scientific awards include: Co-investigator on SDCI HPC Improvement grant (2007-2012) His work bridges computer architecture and energy-efficient computing through rigorous performance modeling and technology evaluation for NERSC's diverse scientific users.

Thomas Shuttمشاهده پروفایل

استاد

• Particle Physics
• Astrophysics
• Dark Matter Detection
• +۵ مورد دیگر

Thomas Shutt is a Professor of Particle Physics and Astrophysics at Stanford University, with a courtesy appointment in the Physics department. He serves as a Senior Member at the Kavli Institute for Particle Astrophysics and Cosmology (KIPAC) and holds a faculty position at the SLAC National Accelerator Laboratory within the Fundamental Physics Directorate. His office is located at the Fred Kavli Building at 2575 Sand Hill Road, Menlo Park, California. Professor Shutt's research focuses on experimental particle astrophysics, particularly in the area of dark matter detection. His work centers on developing and utilizing xenon-based detectors, especially through the Large Underground Xenon (LUX) experiment, to search for Weakly Interacting Massive Particles (WIMPs). His research interests span particle physics, astrophysics, and the development of advanced detection technologies for rare-event physics experiments. Analysis of his recent publications (2016-2017) reveals a strong emphasis on data analysis from the LUX experiment, with particular attention to improving sensitivity for low-mass WIMPs, developing calibration techniques using tritium sources, and implementing advanced trigger systems using FPGA technology. His work consistently contributes to setting increasingly stringent limits on WIMP-nucleon interaction cross-sections across multiple channels. Professor Shutt actively mentors graduate students, serving as Doctoral Dissertation Advisor for Bahrudin Trbalic and Doctoral Dissertation Co-Advisor for Drew Ames. He teaches independent research courses including PHYSICS 190 (Independent Research and Study) and PHYSICS 490 (Research) across all academic quarters. His laboratory work is primarily conducted through the LUX collaboration and previously through the Cryogenic Dark Matter Search (CDMS) experiment, representing significant contributions to the field of direct dark matter detection.

Li Geمشاهده پروفایل

استاد

• Optics
• Photonics
• Non-Hermitian Physics
• +۶ مورد دیگر

Li Ge is a Professor at the College of Staten Island (CUNY) with current research focusing on nonlinear and non-Hermitian phenomena in optics and photonics. His work spans topological photonics, PT-symmetric systems, and quantum chaos in optical microcavities, as evidenced by publications in leading journals like Science , Nature Photonics , and Physical Review Letters . Key contributions include the co-discovery of Coherent Perfect Absorbers and theoretical frameworks for non-Hermitian photonic lattices. Education: PhD in Physics (Yale University, 2010), BS in Physics (Peking University) His research explores: Non-Hermitian photonics and exceptional point dynamics PT-symmetric laser arrays and symmetry breaking Quantum chaos in optical microcavities Directional emission and mode control in microlasers High-dimensional quantum communication via spin-orbit microlasers Recent publications highlight advancements in Brillouin super-cooling, field-programmable photonic nonlinearity, and topological valley Hall polariton condensation. Research trends show increasing focus on integrated photonic devices and non-Hermitian symmetry applications. Scientific Honors: NSF CAREER Award (2019) Dolphin Award for Outstanding Scholarly Achievements (2023) Optica Fellow (2023) He serves on editorial boards for Physical Review B and previously for PNAS and Photonics Research , and has reviewed for over 50 journals and funding agencies globally.

Arto Nurmikkoمشاهده پروفایل

استاد

• Neuroengineering
• Nanophotonics
• Nanomaterials
• +۷ مورد دیگر

Arto Nurmikko is the L. Herbert Ballou University Professor of Engineering and a Professor of Physics at Brown University, affiliated with the School of Engineering. He leads the N3 Lab (Neuroengineering and Nanophotonics Laboratory), focusing on advancing biomedical technologies and neurotechnology. His work integrates nanoscale materials, optoelectronics, and wireless systems to address complex challenges in neuroscience and medical diagnostics. Research interests span neuroengineering, nanophotonics, and nanomaterials, with a strong emphasis on developing implantable microdevices, wireless sensor networks, and neuromorphic computing approaches for brain imaging and stimulation. Projects include optogenetic tools for neural modulation, high-density diffuse optical tomography, and energy-efficient wireless power transfer systems for biomedical implants. Recent publications highlight innovations in imaging through scattering media, neuromorphic reconstruction of dynamic targets, and distributed brain implant systems. These studies reflect a trend toward scalable, minimally invasive neural interfaces and real-time adaptive sensing technologies. His contributions to field-programmable gate array (FPGA) implementations for neural signal processing demonstrate advancements in high-performance embedded platforms. While no scientific awards are explicitly listed, his research has been supported by collaborative projects such as the NSF-funded 'Large-Scale Wireless RF Networks of Microchip Sensors.' Advising includes Jihun Lee, a student co-author in 2024. Grants and projects emphasize scalable sensor networks, wireless power efficiency, and closed-loop brain-computer interfaces. Labs and teams: The N3 Lab specializes in neurotechnology and nanophotonics, developing tools for optogenetic studies, neural imaging, and distributed sensor systems. Teamwork includes interdisciplinary collaboration between engineering, physics, and neuroscience to create innovative biomedical solutions.

• Robotics
• Teleoperation
• Field-Programmable Gate Arrays (FPGA)
• +۳ مورد دیگر

Benjamin Black is a Lecturer at The University of Texas at Austin and a Marketing Development Manager for Power Electronics Real-Time Test at National Instruments. He received his Ph.D. in 2007 from the George Woodruff School of Mechanical Engineering at Georgia Institute of Technology. Research focuses on passive haptic robotics for teleoperation and FPGA-based high-speed control/simulation systems. Notable projects include FPGA-controlled micro-grid inverters, FEA-based permanent magnet synchronous machine simulations, and an FPGA-driven home brewery at NI Week 2012. Volunteer Executive Committee Member for Central Texas FIRST LEGO League, overseeing competitions for 1,500+ elementary students.

Mirjana Stojilovicمشاهده پروفایل

پژوهشگر

• Field-Programmable Technology
• Electronic Design Automation (EDA)
• Hardware Security
• +۳ مورد دیگر

Mirjana Stojilovic is a researcher at EPFL's School of Computer and Communication Sciences and the Parallel Systems Architecture Laboratory (PARSA). She obtained her PhD in 2013 from the School of Electrical Engineering in Belgrade and has worked on projects like STRUCTURES (EU FP7) and ADHeS (armasuisse). Her research spans field-programmable technology, electronic design automation, and hardware security, with a focus on side-channel attacks and countermeasures in reconfigurable systems. Education: PhD in Electrical Engineering (2013), School of Electrical Engineering, Belgrade Research Areas: FPGA security, power analysis attacks, hardware acceleration, EDA optimization Her recent publications analyze vulnerabilities in shared cloud FPGAs, side-channel leakage, and routing architectures. She has supervised numerous PhD and MSc students and received awards for teaching and research. She also organizes workshops and serves on program committees for conferences like FPGA, DATE, and FPL. Scientific Awards: 2023 Best paper award nomination (DDECS) 2020 OMEGA Student Award (for supervised project) 2016 Young scientist award (ICLP), Best paper (EMC Europe) 2015 Teaching Award (EPFL) 2011 Blažo Mirčevski Young author award Committees: Program member for DATE, FPGA, FPL, and associate editor for ACM TRETS and IEEE ESL She teaches courses such as Fundamentals of Digital Systems, Computer Architecture, and Information, Computation, Communication (ICC) at EPFL.

Dina G. Mahmoudمشاهده پروفایل

استادیار

• Heterogeneous Computing
• Hardware Security
• Fault Injection Attacks
• +۳ مورد دیگر

Dina G. Mahmoud is an Assistant Professor at the Department of Computer Science and Engineering at The American University in Cairo (AUC). She earned her Ph.D. in Computer and Communication Sciences from EPFL, Lausanne, Switzerland (2019-2024), where she was a CYD Fellow and collaborated with Dr. Mirjana Stojilović and Dr. Vincent Lenders. Her academic activities include teaching Digital Design, Computer Organization, and Applied Data Structures at AUC. Ph.D. (2019-2024): School of Computer and Communication Sciences, EPFL B.Sc. (2014-2019): Electronics and Communications Engineering with minor in Mathematics, AUC Her research focuses on heterogeneous computing systems , emphasizing security and reliability at the hardware and electrical levels . She investigates fault injection attacks in FPGA systems, particularly in multitenant cloud environments, and has demonstrated the first FPGA-to-CPU fault-injection exploit. Recent publications highlight trends in FPGA security , including power-wasting attacks, hardware Trojans, undervolting exploits, and fault tolerance mechanisms. Her work bridges hardware-software co-design , cloud security , and reconfigurable computing . CYD Fellow (first doctoral recipient) Google Generation Scholarship (2022, EMEA) IC Doctoral Fellowship at EPFL She has served as Head/Teaching Assistant at EPFL for courses like Computer Architecture and Information, Calcul, Communication, and as Head Undergraduate Teaching Assistant at AUC for Digital Logic Design. She contributes to the technical program committee of IEEE Industrial Electronics Society’s ETFA conference.

Carl Sechenمشاهده پروفایل

استاد

• Digital Integrated Circuits
• Analog Integrated Circuits
• Computer-Aided Design (CAD)
• +۵ مورد دیگر

Carl Sechen is a Professor in the Electrical & Computer Engineering Department at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. His research focuses on design and computer-aided design (CAD) of digital/analog integrated circuits, with a strong emphasis on secure ICs and transistor-level programmable fabrics. He leads projects like the TRAP fabric, which achieves 10X logic density over traditional FPGAs while enabling secure hardware through IC redaction. Education: Ph.D. (1987, UC Berkeley), M.S. (1977, MIT), B.E.E. (1975, University of Minnesota). Awards include IEEE Fellow (2002), UTD Distinguished Teaching Award (2014), and multiple Semiconductor Research Corporation awards. His work bridges theoretical CAD advancements with practical hardware security solutions. Research Highlights: Secure IC design, transistor-level programmability, FPGA architecture, hardware security. Key Projects: TRAP fabric development, anti-reverse engineering techniques, low-power design methodologies. Awards: Over 20+ honors including best paper awards at PRIME (2017) and DATE (nominated 2017). Publications span journals like IEEE Transactions on CAD and conferences such as DATE, ISCAS, and VTS. Current work emphasizes secure hardware through obfuscation and programmable logic innovations.