جست‌وجوی استاد و پژوهشگر

Vuk Marojevicمشاهده پروفایل

دانشیار

• Wireless Communications
• Software-Defined Radio
• Open Radio Access Networks (O-RAN)
• +۷ مورد دیگر

Dr. Vuk Marojevic is an Associate Professor in the Department of Electrical and Computer Engineering at Mississippi State University (MSU), holding the Paul B. Jacob Chair. He leads research in wireless communications, focusing on open radio access networks (O-RAN), AI-driven security, and UAV (drone) communications. His work emphasizes software-defined radio (SDR), spectrum sharing, and testbed development for 5G/6G networks. Education: Ph.D. and M.S. in Electrical Engineering from Barcelona Tech–UPC (Spain) and University of Hannover (Germany), respectively. Key projects include leading NSF-funded initiatives like AERPAW and Open Artificial Intelligence Cellular (OAIC), which prototype AI-enabled control systems for cellular networks. He also co-designed the AERPAW testbed for UAV experimentation. Research interests span O-RAN security, AI at the physical layer, wireless security protocols, and vehicular communications. His contributions include open-source implementations of 4G/5G protocols and frameworks for secure slicing and intrusion detection in O-RAN deployments. He actively collaborates with industry and academic partners to advance standards for unmanned aircraft systems (UAS) in cellular networks. Publications highlight innovations in reinforcement learning for resource allocation, RIS (reconfigurable intelligent surfaces) applications, and secure UAV communications. He serves as an associate editor for IEEE Transactions on Vehicular Technology and IEEE Vehicular Technology Magazine. Current research includes prototyping zero-trust security architectures (ZTRAN) and evaluating interference mitigation in drone corridors. He mentors students in MS and Ph.D. programs focusing on wireless systems, security, and AI integration in next-gen networks.

Warren Grossمشاهده پروفایل

استاد

• Integrated Circuits and Systems
• Error-Correcting Codes
• Hardware Acceleration
• +۵ مورد دیگر

Warren Gross is a Professor and Chair of the Department of Electrical & Computer Engineering at McGill University's Faculty of Engineering. Holding the prestigious James McGill Professor title, he leads research in integrated hardware systems from his office in Montreal's McConnell Engineering Building. His work bridges theoretical coding theory with practical VLSI implementations for next-generation communication networks. Professor Gross specializes in Integrated Circuits and Systems with deep expertise in error-correcting codes, particularly polar and Reed-Muller codes. His research spans hardware acceleration for machine learning, stochastic computing architectures, and VLSI design for low-latency wireless systems. Current projects focus on 6G air interface technologies, energy-efficient edge AI, and novel decoding algorithms that balance performance with hardware constraints. The ISIP Lab (Integrated Systems and Image Processing) serves as his primary research hub, advancing both theoretical frameworks and physical implementations. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Hardware-optimized decoding algorithms for polar codes targeting sub-1ms latency in 6G systems; (2) Model compression techniques for transformer networks deployed on resource-constrained edge devices; (3) Stochastic computing approaches for combinatorial optimization problems. These themes reflect his dual focus on communication theory and efficient hardware realization, with increasing emphasis on machine learning integration. Scientific recognition includes: James McGill Professor (McGill University's highest academic honor) As Department Chair and research leader, Professor Gross oversees multiple collaborative projects with industry partners in telecommunications and semiconductor sectors. His lab maintains active partnerships with 5G/6G standardization bodies and chip manufacturers, though specific grant details aren't publicly enumerated. The ISIP Lab operates advanced VLSI design facilities and FPGA testbeds supporting both academic research and industry prototyping. Research infrastructure includes specialized labs for stochastic computing implementation, polar code decoder validation, and edge AI acceleration. Current efforts focus on quantum-inspired annealing techniques for MIMO detection and hardware-friendly transformer architectures, with several patents pending in decoding methodology and model compression.

Shruti Puriمشاهده پروفایل

استادیار

• Quantum Physics
• Quantum Information Processing
• Quantum Computing
• +۵ مورد دیگر

Shruti Puri is an Assistant Professor of Applied Physics at Yale University, affiliated with the Yale Quantum Institute (YQI). Her research focuses on quantum information processing, quantum computing, and quantum optics, with an emphasis on reducing resource overheads in quantum error correction through circuit engineering and noise-tailored codes. She leads the Puri Group, collaborating with experimental groups to advance quantum technologies. Education: Ph.D. in Applied Physics from Stanford University (2014), followed by postdoctoral research at the University of Sherbrooke (2014–2017) and Yale University (2017–2020). Awards include the NSF CAREER Award (2022). Research interests span quantum error correction for biased noise, bosonic qubits, and fault-tolerant architectures. Her work addresses challenges in stabilizing cat qubits, designing scalable QRAM, and optimizing decoders for quantum LDPC codes. Key projects include 'Bias-preserving gates with stabilized cat qubits' and 'Scalable fault-tolerant quantum error correction with bosonic qubits.' Recent contributions include studies on mid-circuit erasure conversion, dual-rail cavity qubits, and high-threshold codes for neutral-atom qubits. Collaborations involve experimental teams to bridge theory and practice in quantum computing. Advises graduate students working on topics like topological codes, optomechanical control, and quantum annealing. Leads the development of novel quantum protocols and devices, such as hypergraph decoders and phononic memory systems.

Gwan Choiمشاهده پروفایل

دانشیار

• Fault-tolerance
• Verification simulation
• High-performance VLSI circuits
• +۷ مورد دیگر

Gwan Choi is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on fault-tolerance, verification simulation, high-performance VLSI circuits, radiation testing, design for dependability, and software engineering. He holds a Ph.D., M.S., and B.S. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (1988–1994). Education: Ph.D., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (1994) M.S., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (1989) B.S., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (1988) Research Interests: Dr. Choi’s work spans fault-tolerant computing, radiation-hard electronics, and high-performance VLSI design. He has contributed to LDPC decoding architectures, MIMO communication systems, and energy-efficient circuit designs. His research emphasizes practical implementations in aerospace and embedded systems. Awards: National Science Foundation (NSF) Career Award (1997) Labs & Activities: He has collaborated with NASA Langley Research Center as a visiting scientist and contributed to industry through roles at Cray Research and Tandem Computers. His work bridges academic research with real-world applications in fault tolerance and low-power systems.

• Theoretical Computer Science
• Computational Complexity
• Information Theory
• +۴ مورد دیگر

Mark Braverman is a Professor at Princeton University, known for his contributions to theoretical computer science, computational complexity, and information theory. He holds a PhD from the University of Toronto (2008), where his dissertation focused on computability and complexity of Julia sets. His research spans a wide range of topics including interactive communication protocols, pseudorandomness, distributed computing, algorithmic game theory, and quantum computing. Key areas of focus include developing error-correcting codes for interactive communication, establishing lower bounds in computational complexity, and exploring the interplay between information theory and algorithm design. Braverman has co-authored over 240 publications and has collaborated extensively with researchers such as Klim Efremenko, Anup Rao, and Omri Weinstein. His work has been recognized through prestigious venues like STOC, FOCS, and SODA, and has addressed foundational questions in theoretical computer science, including the limits of parallel repetition in games and the design of resilient computational systems. Recent research highlights include advancements in quantum communication complexity, fault-tolerant circuit design, and algorithmic approaches to matching markets. His interdisciplinary work bridges mathematical theory with practical applications in distributed systems and economics. Braverman also contributes to the academic community through editorial roles and conference organization, furthering the development of computational theory and its applications.

Anwar Shiekhمشاهده پروفایل

مدرس

• Theoretical Physics
• Quantum Gravity
• Black Hole Physics
• +۵ مورد دیگر

Anwar Shiekh is an Instructor of Physics at Colorado Mesa University (CMU), located in Grand Junction, CO. He holds dual citizenship (American and British) and has a strong academic background with two BSc degrees (Physics and Mechanical Engineering) from Imperial College London (1980, 1983), followed by a PhD in Theoretical Physics from the same institution in 1987 under advisor Chris Isham. His research focuses on theoretical physics, including quantum gravity, black hole dynamics, quantum field theory, and the intersection of quantum mechanics with general relativity. He has contributed to textbooks such as College Physics (Serway & Vuille) and Principles of Physical Optics , providing critical feedback for improvements. Research Interests: His work addresses foundational challenges in theoretical physics, such as quantizing gravity, resolving paradoxes in black hole physics (e.g., event horizon evaporation), and exploring quantum computing error avoidance via the Zeno effect. He has also investigated impossibility proofs in physics, proposing solutions to issues like macroscopic wormhole limitations and gravitational radiation from accelerating charges. Publications Trends: Shiekh’s articles span decades, emphasizing quantum gravity corrections, operator regularization techniques, and black hole thermodynamics. Recent works include studies on magnetic monopoles and accelerating charges in gravitational fields, while earlier contributions focused on path integrals, canonical transformations, and zeta-function regularization. His 1990s research included pioneering efforts to quantize orthodox gravity and derive quantum field theory formalisms. Book Contributions: He actively collaborated on textbook revisions, notably College Physics (11th ed.) and Principles of Physical Optics (2nd ed.), where his insights addressed typographical errors and conceptual clarity. His expertise also extends to reviewing quantum gravitational corrections to Newtonian gravity and proposing experimental setups for quantum interference-based computing.

Maximilian Starkمشاهده پروفایل

مدرس

• Communication Systems
• Machine Learning
• Information Theory
• +۳ مورد دیگر

Dr. Maximilian Stark is a Lecturer at the Institute of Communications, TU Hamburg. His research focuses on machine learning-driven advancements in communication systems, particularly applying the information bottleneck method to decoding algorithms, signal processing, and quantization techniques. His work bridges theoretical information theory with practical implementation challenges in coding and channel design. Key research areas include LDPC and polar codes optimization, low-bitwidth decoding architectures, and distributed signal processing frameworks. Recent publications emphasize adaptive learning systems for error resilience under quantization constraints and hardware-efficient receiver design. Dr. Stark's academic contributions span over 20 peer-reviewed articles since 2016, with a strong emphasis on integrating machine learning principles into traditional communication engineering problems. Notable themes include neural decoding paradigms, resource-constrained quantization strategies, and distributed information compression methods. No scientific awards explicitly listed. Academic advising details and lab affiliations are not provided in source materials.

Karystinos Georgeمشاهده پروفایل

استاد

• Communication theory and systems
• Coding theory
• Adaptive signal processing
• +۶ مورد دیگر

Prof. George Karystinos is a Professor at the Technical University of Crete (TUC), School of Electrical and Computer Engineering (ECE), where he leads the Telecommunications Laboratory. His academic journey includes a Ph.D. in Electrical Engineering from SUNY Buffalo (2003) and a Diploma in Computer Engineering from the University of Patras (1997). He previously held a faculty position at Wright State University before joining TUC in 2005. His research focuses on communication theory, coding, adaptive signal processing, wireless systems, and neural networks. Key interests include spreading code design, interference suppression, adaptive antenna arrays, and noncoherent detection techniques. His work has led to advancements in power line communication, MIMO systems, and low-complexity decoding algorithms. Prof. Karystinos has received prestigious awards, including the 2003 IEEE Transactions on Neural Networks Outstanding Paper Award and the 2001 IEEE International Conference on Telecommunications Best Paper Award. He is an active member of IEEE societies in Communications, Signal Processing, and Information Theory. He teaches core courses such as Signals and Systems , Information Theory and Coding , and Probability and Random Processes . His laboratory emphasizes practical applications of theoretical concepts, with recent projects on smart photovoltaic systems and cascaded H-bridge converter control. His research spans 20+ years, yielding over 80 publications in top journals/conferences. Current efforts address challenges in IoT communication, noncoherent detection for RFID, and energy-efficient signal processing. He collaborates internationally on projects funded by Greek and EU research programs.

Yin Sunمشاهده پروفایل

دانشیار

• Wireless Networks
• Wireless Communications
• Cloud Computing
• +۵ مورد دیگر

Yin Sun is the Godbold Associate Professor in the Department of Electrical and Computer Engineering at Auburn University. His research focuses on timely information updates, wireless networks, and IoT, with emphasis on data freshness metrics and remote estimation systems. He earned his B.S. and Ph.D. in Electronic Engineering from Tsinghua University. Education: B.S. Electronic Engineering, Tsinghua University Ph.D. Electronic Engineering, Tsinghua University His research interests include wireless communications, cloud computing, and machine learning applications in safety-critical systems. Notable achievements include co-authoring the seminal book on Age of Information and receiving the NSF CAREER Award for his work on goal-oriented status updating. He also serves as Technical Co-Chair for the ACM MobiHoc Symposium and leads Auburn's Wireless Engineering Research and Education Center, addressing real-world communications challenges through interdisciplinary collaboration. Awards include the 2021 Best Paper Award (Journal of Communications and Networks) and contributions to food pantry inventory optimization via machine learning. His work bridges theoretical foundations with practical systems, emphasizing real-time data relevance and efficient resource allocation strategies. Advisees/Grants: Leads NSF-funded projects on semantic status updating and collaborates on applications like disease detection in agriculture. Active in advising graduate students through his lab's focus on edge computing and network optimization. Labs/Teams: Core member of Auburn's Wireless Engineering Research and Education Center, fostering multi-university collaborations in communications research.

• Combinatorics
• Graph Theory
• Coding Theory
• +۳ مورد دیگر

Dr. Daniel Hawtin is a Professor at the Faculty of Mathematics, University of Rijeka. His research focuses on algebraic combinatorics, graph theory, and coding theory with emphasis on group actions, symmetry properties of graphs, and combinatorial designs. He leads the UNIRI YOUNG SCIENTISTS PROJECT titled 'Neighbour-transitive codes in graphs' (2022), and previously contributed to 'Codes, groups and combinatorial structures' (2018). His work spans theoretical aspects of coding theory, distance-regular graphs, and algebraic approaches to combinatorial problems. Research Interests: Algebraic symmetry in codes and graphs 2-arc-transitive graphs and Cayley graphs Combinatorial designs (q-Steiner systems, subspace designs) Error-correcting codes with transitive automorphism groups Finite geometry applications in coding theory Publications Trends: Recent work emphasizes neighbour-transitive codes in Kneser graphs (2024), edge-affine graph constructions (2024), and non-existence proofs in combinatorial designs (2022). His research bridges abstract algebra with combinatorial structures, often using group theory to analyze graph symmetries and code properties. Grants & Projects: Principal Investigator for UNIRI Young Scientists Project (2022) and collaborator in multiple combinatorial research initiatives. Active in international collaborations with experts like Cheryl Praeger and Jin-Xin Zhou.

Jonathan Scarlettمشاهده پروفایل

دانشیار

• Information Theory
• Machine Learning
• High-Dimensional Statistics
• +۳ مورد دیگر

Jonathan Scarlett is an Associate Professor at the National University of Singapore (NUS), holding joint appointments in the Department of Computer Science, Department of Mathematics, and the Institute of Data Science. His research focuses on information theory, machine learning, and high-dimensional statistics, with contributions to topics such as group testing, Bayesian optimization, and coding theory. He has received notable awards including the NUS Presidential Young Professorship and MIT TR35 Innovators (Asia Pacific) recognition. Scarlett advises numerous PhD students, including Yang Sun, Zihan Li, and Arpan Losalka, whose theses address challenges in inverse problems, kernel-based optimization, and safety in Bayesian optimization. His work spans theoretical foundations and practical applications, with recent publications exploring optimal group testing algorithms, error exponents in DNA storage, and robust bandit optimization. He leads collaborative projects on distributed statistical estimation and adversarial machine learning, leveraging interdisciplinary methods from signal processing and information theory. His academic journey includes a postdoc at the LIONS laboratory (2014–2017) before his promotion to Associate Professor in 2024. Scarlett actively contributes to the academic community through editorial roles, conference organization, and over 100 peer-reviewed publications. His lab develops novel frameworks for handling uncertainty in data-driven systems, with applications to healthcare, communication networks, and autonomous systems.

Umesh Vaziraniمشاهده پروفایل

استاد

• Quantum Computing
• Algorithms
• Complexity Theory
• +۳ مورد دیگر

Umesh Vazirani is the Roger A. Strauch Professor of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley, and co-director of the Berkeley Quantum Computation Center (BQIC). His primary research focuses on quantum computing, algorithms, and complexity theory, with significant contributions to quantum cryptography, graph partitioning, and computational learning theory. Education: 1986 - Ph.D. in Computer Science, UC Berkeley 1981 - B.S., MIT Research Interests: Quantum computing foundations and applications, quantum algorithms development, complexity theory, cryptographic protocols, error-correcting codes, graph theory, and quantum information science. His work bridges theoretical computer science with practical quantum implementations. Publications Focus: Vazirani's recent publications demonstrate strong emphasis on quantum supremacy, quantum cryptography, area laws in quantum systems, and quantum complexity theory. His work frequently addresses fundamental questions in quantum information processing and computational complexity. Awards and Honors: ACM SIGECOM Test of Time Award (2024) STOC Test of Time Award (2023) National Academy of Sciences Member (2018) Delbert Ray Fulkerson Prize (2012) ACM Fellow (2005) NSF Presidential Young Investigator (1987) Student Advising: Has supervised numerous PhD students including Scott Aaronson (MIT), Sanjeev Arora (Princeton), Madhu Sudan (Harvard), Thomas Vidick (Caltech), Urmila Mahadev, and current students Jonah Sherman and Guoming Wang. Leadership: Directs the Berkeley Quantum Computation Center (BQIC) and collaborates with the Simons Institute for the Theory of Computing. Regularly teaches graduate courses on quantum computing and algorithms.

Mark M. Wildeمشاهده پروفایل

دانشیار

• Quantum Computing
• Quantum Information Theory
• Quantum Error Correction
• +۳ مورد دیگر

Dr. Mark M. Wilde is an Associate Professor in the School of Electrical and Computer Engineering at Cornell University and an Adjunct Professor in the Department of Physics and Astronomy at Louisiana State University. He holds a Ph.D. in electrical engineering from the University of Southern California. His primary research focuses on quantum information theory, quantum computing, quantum error correction, and quantum computational complexity. He has authored influential textbooks such as *Quantum Information Theory* and *Principles of Quantum Communication Theory*, widely used in graduate courses globally. Wilde’s research explores foundational aspects of quantum communication, including quantum Shannon theory, network quantum information theory, and quantum algorithms. He has contributed to advancements in quantum error correction, quantum cryptography, and thermodynamics. His work bridges theoretical insights with practical applications in quantum technologies. Notably, he has co-authored groundbreaking results on quantum channel capacities, entanglement-assisted quantum coding, and quantum hypothesis testing. Wilde has secured grants from institutions like the Simons Foundation and the National Science Foundation. His awards include the IEEE Fellow distinction and the 2018 AHP-Birkhauser Prize. He collaborates extensively, publishing over 100 peer-reviewed articles, and his research impacts fields from quantum computing to biophysics. His recent work emphasizes quantum algorithms, thermodynamic limits, and privacy-preserving quantum protocols. Education: Ph.D. in Electrical Engineering, University of Southern California (2009). Grants: Supported by NSF, Simons Foundation, and others. Labs/Teams: Leads research groups in quantum information theory and collaborates with interdisciplinary teams on quantum algorithms and applications.

Sheng Yangمشاهده پروفایل

استاد

• Information Theory
• Wireless Communications
• MIMO Systems
• +۶ مورد دیگر

Sheng Yang is a full professor at CentraleSupélec, University of Paris-Saclay, and holds an honorary associate professorship at the University of Hong Kong. His research focuses on information theory and its applications to wireless networking, including MIMO systems, non-coherent communication, interference mitigation, and physical layer security. He has authored numerous influential papers and received the 2015 IEEE ComSoc Young Researcher Award. His teaching includes courses on digital communication, information theory, and wireless communications. Educational Background: BE in Electrical Engineering (Jiaotong University, Shanghai, 2001), Engineer Degree and M.Sc. (Telecom ParisTech, 2004), and Ph.D. (Université Pierre et Marie Curie, 2007). Research Interests: Multi-antenna (MIMO) communications, non-coherent systems, hardware impairments, coded caching, federated learning, and the integration of machine learning with communication systems. Notable Contributions: Developed novel rate-splitting strategies for MIMO broadcast channels, analyzed capacity limits of 1-bit quantized MIMO systems, and pioneered CSI compression schemes using context trees. He has supervised over 10 PhD/postdoc students, many now in academia and industry leadership roles. Awards: IEEE ComSoc Young Researcher Award (2015), Associate Editor roles at IEEE Transactions on Information Theory and IEEE Transactions on Wireless Communications. Labs/Teams: Active in the MODESTY, COMEDY, and SYCOMORE research groups at L2S, focusing on system modeling and control. His work intersects energy-efficient communication, distributed computing, and future network architectures.

Nathaniel Johnstonمشاهده پروفایل

پژوهشگر

• Quantum Information Theory
• Quantum Entanglement
• Matrix Analysis
• +۱۶ مورد دیگر

Nathaniel Johnston is a researcher specializing in quantum information theory, combinatorics, and computational mathematics. He is the creator of QETLAB , a MATLAB toolbox for quantum entanglement, and the founder of ConwayLife.com , a major resource on cellular automata including the comprehensive LifeWiki. He also maintains StatDistributions.com and PlatPrices.com. His research spans: Quantum entanglement and quantum error correction Superpermutations and combinatorics on words Conway’s Game of Life and cellular automata Matrix norms and linear preserver problems Applications of linear algebra to puzzles like Lights Out Geometric optimization and calculus problems He produces educational math videos using Manim, covering advanced topics in an accessible format. His scholarly output includes significant contributions to open problems in mathematics and software tools widely used in the research community. He actively engages with users via GitHub and social media (Bluesky). Notable Projects: QETLAB : A MATLAB toolbox for quantum entanglement, actively developed and cited in research. ConwayLife.com / LifeWiki : The largest encyclopedia of Conway’s Game of Life patterns. StatDistributions.com : A tool for calculating p-values and test statistics. PlatPrices.com : A non-academic site tracking PlayStation game prices and trophies. Scientific Contributions: Disproved the minimal superpermutation conjecture. Developed algorithms for computing hard-to-compute matrix norms. Created accessible explanations of complex topics via video and interactive tools. While his current institutional affiliation is not stated, his body of work, software development, and scholarly communication confirm his status as an active academic researcher in applied and computational mathematics.