جستجوی استاد راهنمای دانشگاهی

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.

• Computer Engineering
• Circuit Design
• Fault Tolerance
• +۶ مورد دیگر

Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.

Burak Ozdoganlarمشاهده پروفایل

استاد

• Manufacturing Processes
• Biomedical Engineering
• Materials Science
• +۷ مورد دیگر

Burak Ozdoganlar is a Ver Planck Endowed Chair Professor of Mechanical Engineering at Carnegie Mellon University (CMU) and Associate Director of the Engineering Research Accelerator. He holds courtesy faculty positions in Biomedical Engineering and Materials Science and Engineering. Ozdoganlar earned his Ph.D. in Mechanical Engineering from the University of Michigan (1999), M.S. degrees from Ohio State University (1993, 1995), and a B.S. in Aeronautical Engineering from Istanbul Technical University (1991). Ph.D., Mechanical Engineering, University of Michigan (1999) MS, Mechanical Engineering, Ohio State University (1995) MS, Aeronautical and Astronautical Engineering, Ohio State University (1993) BS, Aeronautical Engineering, Istanbul Technical University (1991) Ozdoganlar’s research focuses on multi-scale manufacturing processes (macro/micro/nano), precision engineering , structural dynamics , and modal testing , with applications in biomedical device fabrication , microneedle arrays , soft electronics , and 3D ice printing for vascular networks. His work bridges computational modeling with experimental validation. Recent scientific awards include the 2023 AIMBE College of Fellows induction, ASME Fellow (2019), and NSF CAREER Award (2006). He served as interim CTO of the Advanced Robotics for Manufacturing (ARM) Institute and chaired the ASME-MED Manufacturing Equipment Technical Committee. Ozdoganlar leads projects in scalable manufacturing for implantable medical devices , bioelectric medicine , and wearable robotics . His lab develops 3D ice-printed vascular templates for tissue engineering and liquid metal circuits for soft electronics, funded by institutions like the Manufacturing Futures Institute and ARPA-H.

Ronald J. Colomboمشاهده پروفایل

استاد

• Corporate Law
• Securities Regulation
• Financial Regulation
• +۷ مورد دیگر

Ronald J. Colombo is Professor of Law and Associate Dean for Distance Education at Hofstra University's Maurice A. Deane School of Law. He teaches courses in Business Organizations, Securities Regulation, Contracts, and corporate law seminars. He has been on the faculty since 2006 and previously served as Associate Dean for Academic Affairs (2013–2015). Education: JD, New York University School of Law (magna cum laude, Order of the Coif), 1998 BS, Cornell University, 1994 Clerkship: Judge Jerry E. Smith, U.S. Court of Appeals for the Fifth Circuit Professor Colombo’s research focuses on corporate law, securities regulation, financial regulation, and the constitutional rights of corporations, especially First Amendment protections. His work explores the moral and philosophical underpinnings of corporate personhood, religious liberty in business, and the role of trust in financial systems. He is particularly known for bridging legal doctrine with ethical and theological perspectives. His recent scholarly publications reveal a strong thematic trend: the intersection of religion, corporate governance, and constitutional law. He has also contributed to legal education, especially in online teaching methodologies, and continues to publish on financial regulation and corporate ethics. Scientific Awards: Stessin Prize for Outstanding Scholarly Publication Lawrence A. Stessin Prize for Outstanding Scholarly Publication (2008) Professor Colombo has been actively involved in professional service, including serving on the editorial review board of the Review of Business and as an arbitrator for the Financial Industry Regulatory Authority (FINRA). He has not listed any formal research grants or PhD students, but his influence extends through media engagement—quoted in The New York Times , Wall Street Journal , and Bloomberg —and through his widely read op-eds in The Financial Times and Huffington Post . He has held leadership roles in academic administration and is a recognized expert in both practitioner and scholarly legal communities. His treatise Law of Corporate Officers and Directors is republished annually by Thomson Reuters, indicating sustained scholarly and practical impact.

Mary Lanzerottiمشاهده پروفایل

استادیار

• Signal Processing
• Control Systems
• Medical Technology
• +۴ مورد دیگر

Mary Lanzerotti is a Collegiate Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. She specializes in signal processing, control systems, and medical evacuation technology. Her research focuses on hoist stabilization for MEDEVAC rescues, RF signal estimation, and material science involving liquid films. She is also deeply involved in educational initiatives, including hybrid course development and student advising strategies. Education: A.B. summa cum laude from Harvard College (1989), M. Phil. from the University of Cambridge (1991), M.S. and Ph.D. from Cornell University (1994–1997). Research Interests: Signal processing algorithms, mechanical stabilization of hoist systems, quantum computing verification, and integrated circuits design. Recent work includes gyroscopic data-driven control systems and multi-tier RF signal estimation methods. Service Roles: Member of faculty search committees, assessment committees, and the Graduate Honor System panel. Active in institutional accreditation and curriculum modernization efforts. Labs/Teams: Collaborates with interdisciplinary teams on projects involving aerospace rescue systems, laser material interaction studies, and microelectronics verification.

Conor Ryanمشاهده پروفایل

استاد

• Genetic Programming
• Genetic Algorithms
• Grammatical Evolution
• +۷ مورد دیگر

Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.

Oliver Diesselمشاهده پروفایل

دانشیار

• Reconfigurable Hardware
• Computer Architecture
• Digital Systems
• +۶ مورد دیگر

Associate Professor Oliver Diessel is a faculty member at the University of New South Wales (UNSW) within the School of Computer Science and Engineering. He has been actively teaching and conducting research at UNSW since at least 2000, with teaching experience spanning various computer architecture and digital systems courses. Dr. Diessel completed his education at the University of Newcastle, Australia, earning a B.E. (Computer, Hons) and B.Math. in 1991, followed by a PhD in 1998. His academic career has focused on reconfigurable computing systems and computer architecture. His primary research interests center around the design, test, and implementation of digital systems in reconfigurable logic devices called Field-Programmable Gate Arrays (FPGAs). Specifically, he focuses on dynamically reconfigurable digital systems where circuits can be modified while the system is operational. His work aims to develop architectures, design methods, and tools that enhance the benefits and reduce the costs of reconfigurable systems. Current research projects include fault-tolerant FPGA-based systems for space applications and fine-grained accelerators for heterogeneous devices. Dr. Diessel has published extensively with 2 books, 1 book chapter, 16 journal articles, 67 conference papers, 1 edited conference proceedings, and 7 conference presentations to his credit. His publications reflect a strong emphasis on reconfigurable technology, computer architecture, and electronic design automation. As a supervisor, Dr. Diessel currently mentors two MPhil students: Tong Wu working on Runtime reconfiguration and Junning Fan working on Fault-tolerance of FPGA-based applications. He has previously supervised six students to completion. His supervision interests include reconfigurable technology and systems, electronic design automation, and computer architecture. Dr. Diessel is an active member of the professional community, serving on the Editorial Board of ACM Transactions on Reconfigurable Technology and Systems and as an IEEE Member. He has taught numerous courses including Configurable Systems (COMP4601), Computer Architecture (COMP3211, COMP4211), Digital Systems (COMP3222), and FPGA Implementation of Digital Systems using Verilog.

Debjit Palمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning for Electronic Design Automation (EDA)
• System-on-Chip (SoC) Verification
• Hardware Verification
• +۶ مورد دیگر

Debjit Pal is a Post-Doctoral Associate at the School of Electrical and Computer Engineering, Cornell University, and a member of the Computer Systems Laboratory. His research focuses on machine learning techniques for hardware verification, SoC validation, and FPGA optimization. Education: Ph.D. in Computer Engineering (University of Illinois at Urbana-Champaign, 2019) M.S. in Computer Science (IIT Kharagpur, 2012) B.E. in Electronics Engineering (Jadavpur University, 2008) Research Interests: Machine Learning for Electronic Design Automation (EDA) System-on-Chip (SoC) Verification Edge Intelligence as a Service Compiler Optimizations for Reconfigurable and High-Performance Computing Scientific Awards: IEEE CEDA Student Research Award (2016) Best Paper Nomination (ICCAD 2015, DAC 2018, ASP-DAC 2019) E. J. McCluskey Best Doctoral Thesis Competition Semi-Finalist (2020) Travel Grants for ICCAD/DAC/ASPDAC (2018-2019) Professional Roles: Technical Program Committee Member (DAC, VLSID), Reviewer (IEEE TVLSI, DATE, ICCAD). Collaborates with researchers like Zhiru Zhang and Shobha Vasudevan.

• Network Security
• Android Security
• Malware Analysis
• +۶ مورد دیگر

Vijay Laxmi is a Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology (MNIT) Jaipur, India. With over a decade of active research publication from 2014-2024, Dr. Laxmi has established themselves as a prominent researcher in network security, Android security systems, and Network-on-Chip architectures. Their work demonstrates consistent collaboration with Manoj Singh Gaur and numerous doctoral students at MNIT Jaipur. Dr. Laxmi's research interests span Network Security, Android Security, Malware Analysis, Network-on-Chip Architectures, Routing Protocols, Side-Channel Attacks, Wireless Networks, and Mobile Security. Their work bridges theoretical security frameworks with practical implementations, particularly in mobile and embedded systems. Recent publications indicate a growing focus on AI-based security approaches including GAN applications for fuzzing and deep learning for image dehazing. The research trajectory shows increasing sophistication in security analysis techniques, evolving from basic malware detection to advanced side-channel attack analysis and sophisticated network security protocols. Recent publications demonstrate expertise in both theoretical frameworks and practical implementations with applications in real-world security challenges. Dr. Laxmi has mentored numerous graduate students including Vineeta Jain, Anugrah Jain, Sonal Yadav, Mohit Singh, and Gaurav Singal, who appear as co-authors across multiple publications. Their collaborative network extends to researchers at international institutions, indicating strong academic connections beyond their home institution.

Wolfgang Kunzمشاهده پروفایل

استاد

• Hardware Safety and Security
• Formal Hardware Verification
• Embedded Computing Systems
• +۵ مورد دیگر

Wolfgang Kunz is a Full Professor (C4, W3) and Chair of Electronic Design Automation at the Technische Universität Kaiserslautern since 2001. His academic career spans multiple prestigious institutions, including Goethe-University Frankfurt/Main and the University of Massachusetts, Amherst. He has held leadership roles such as Dean (2005-2007) and Vice-Dean (2007-2009) at TU Kaiserslautern. Habilitation (Dr. rer. nat. habil.), Computer Science, University of Potsdam (1996) Doctoral degree (Dr.-Ing.), Electrical Engineering, University of Hannover (1992) Dipl.-Ing. degree, Karlsruhe Institute of Technology (1989) His research focuses on hardware verification, security, and optimization, particularly in embedded systems and processors. His work on formal verification methods has been commercialized by companies like Synopsys, Mentor Graphics, and Siemens EDA. His 2016-2021 publications address critical security issues such as Spectre/Meltdown and introduce innovative verification frameworks adopted by industry leaders like Infineon and OneSpin Solutions. Scientific awards include the IEEE Fellow (2006), German IT Society Award (2005), and TU Kaiserslautern Distinguished Teaching Award (2016). He has served on editorial boards of major journals and coordinated the Erasmus Mundus European Master Program in Embedded Computing Systems since 2010. Key students: Jörg Bormann, Raik Brinkmann, Tobias Ludwig Collaborations: Siemens EDA, Infineon, AbsInt, Intel SCAP Spin-offs: LUBIS EDA, OneSpin Solutions

Tobi Delbruckمشاهده پروفایل

استاد

• Neuromorphic Engineering
• Event-Based Vision Systems
• Silicon Retinas
• +۶ مورد دیگر

Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.

Marina Blantonمشاهده پروفایل

دانشیار

• Applied Cryptography
• Information Security
• Privacy-Preserving Computation
• +۳ مورد دیگر

Marina Blanton is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and Faculty Director of Women in Science and Engineering within the School of Engineering and Applied Sciences. She holds a PhD in Computer Science from Purdue University (2007), along with multiple advanced degrees in Computer Science and Electrical Engineering from prestigious institutions in the US and Russia. Her research focuses on applied cryptography, information security, and privacy-preserving computation and outsourcing. She has pioneered work on secure multi-party computation protocols, privacy-preserving biometric authentication, and secure data analytics across distributed systems. Her contributions include foundational frameworks like PICCO, a compiler for private distributed computation, and advancements in protocols for genomic data analysis and floating-point secure computation. Blanton has been recognized with numerous awards, including IEEE and ACM Senior Membership (2016/2015), the ACM CCS Test of Time Award (2015), and the AFOSR Young Investigator Award (2013). Her research has been supported by grants such as NSF SaTC awards and AFOSR funding. Her work emphasizes practical implementations of secure computation, with applications in healthcare, biometrics, and distributed data systems. She has advised numerous students and contributed to educational initiatives promoting women in STEM through her leadership roles.

• Electrical and Electronic Engineering
• Computer Hardware
• Computer Software
• +۷ مورد دیگر

Professor Peter Y. K. Cheung is a Professor of Digital Systems at Imperial College London, holding dual affiliations within the Department of Electrical and Electronic Engineering and the Dyson School of Design Engineering. His work focuses on reconfigurable systems, FPGA architectures, and high-level synthesis tools. He co-founded one of the UK's leading FPGA research groups with Professor Wayne Luk, addressing challenges in variability mitigation, reliability, and application-specific FPGA deployments. His research spans Field-Programmable Gate Arrays (FPGAs) Reconfigurable computing Neural network acceleration Cryptographic protocols Embedded systems He has pioneered techniques such as logic shrinkage for FPGA-based neural networks and developed frameworks like LUTNet for efficient inference. His contributions also include fault-tolerant FPGA designs and methodologies for distributed computation protocols. Key collaborations include work with the Department of Computing on FPGA-based AI acceleration and cybersecurity applications. His recent work explores edge computing, secure decentralized systems, and pandemic modeling using adaptive control strategies. Notable projects include the DSCS protocol for secure distributed computation, acceleration of gravitational wave detection algorithms, and energy-efficient CNN implementations. His research bridges hardware-software co-design with real-world applications in healthcare, finance, and aerospace.

• Microelectronics
• Nanotechnology
• RF Engineering
• +۳ مورد دیگر

Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.

• Analog Integrated Circuits
• Power-Conditioning ICs
• Energy-Harvesting ICs
• +۳ مورد دیگر

Gabriel Alfonso Rincon-Mora is the Motorola Solutions Foundation Professor at the Georgia Institute of Technology's School of Electrical and Computer Engineering. A Fellow of the National Academy of Inventors, IEEE, and IET, he specializes in analog/power integrated circuits, energy-harvesting systems, and microelectronics. With over 200 articles, 44 patents, and 12 books, his work has produced 26 commercial power-chip products. His research spans: Analog and power-management ICs for efficient energy conversion Self-sustaining microsystems powered by thermal, mechanical, and environmental sources Nano-scale circuit designs for biomedical and wireless sensor applications Recent publications focus on piezoelectric energy harvesting, battery charging optimization, and low-power CMOS designs, demonstrating consistent innovation in power efficiency and miniaturization. Awards include the IEEE Charles A. Desoer Technical Achievement Award, National Hispanic in Technology Award, and recognition as one of "The 100 Most Influential Hispanics." He directs research in power IC design and mentors students through the Georgia Tech Analog Consortium. His laboratory develops integrated solutions for energy-constrained applications, including collaborations with industry partners like Texas Instruments.