جستجوی استاد راهنمای دانشگاهی

• Optical Networks
• Data Center Networks
• Optical Interconnects
• +۷ مورد دیگر

Dr. Khurram Aziz is a Senior Instructor in the Faculty of Computer Science at Dalhousie University , Halifax, Canada. He is actively engaged in teaching and research, with a focus on optical networks, data center interconnects, and network performance modeling. Education: PhD in Electrical Engineering, Vienna University of Technology, Austria (2008) MSc in Electrical Engineering, National University of Singapore (2003) BSc (Hons) in Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan (1998) His research interests include optical packet and burst switched networks , optical interconnects for data centers , analytical modeling and simulation , and network routing and switching . He has contributed extensively to the design and performance evaluation of scalable optical switches and hybrid switching systems. The recent publications reflect a strong trend in data center optical networks , focusing on performance, blocking probability, signal degradation, and architectural classification. His work bridges theoretical modeling with practical simulation frameworks, such as CloudNetSim++ in OMNeT++, contributing to cloud and high-capacity network research. Dr. Aziz has no listed scientific awards in the provided text. He teaches several core computer science courses including CSCI 2141: Intro to Database Systems , CSCI 3171: Network Computing , CSCI 3132: Object Orientation and Generic Programming , and CSCI 3120: Operating Systems . There is no mention of graduate student supervision or external research grants. He has co-authored book chapters in major handbooks on data centers and switched systems. Dr. Aziz has not listed any formal lab or research team affiliations in the provided content.

David Blaauwمشاهده پروفایل

استاد

• Ultra-Low Power Circuits
• IoT and Sensor Networks
• RF Communication
• +۷ مورد دیگر

David Blaauw is the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science (EECS) at the University of Michigan. His research focuses on ultra-low-power analog/mixed-signal circuits, mm-scale sensors, neural networks, and biomedical applications. He leads the Blaauw Lab, which has pioneered innovations like the Michigan Micro Mote (M^3) and neural recording probes. His work emphasizes real-world deployability, with applications in environmental monitoring (e.g., monarch butterflies), medical devices, and robotics. Education: B.S. in Physics and Computer Science, Duke University (1986) Ph.D. in Computer Science, University of Illinois Urbana-Champaign (1991) Research Interests: Blaauw’s lab explores ultra-low-power computing, mm-scale systems, RF communication, in-memory computing, and genomics acceleration. Key projects include: Millimeter-scale computers (e.g., 0.04mm³ temperature sensors) Wireless neural interfaces for brain-machine communication Energy-efficient accelerators for edge AI and genomics Micro-robotics with sensing/actuation/computation Awards: IEEE Fellow 2016 SIA-SRC Faculty Award Motorola Innovation Award Best Paper Awards at ISSCC, ISCA, and RFIC Advising & Impact: Over 600 publications, 65 patents, and 4 startup companies spun from his lab. Current research includes genome sequencing accelerators (GenAx) and neural recording dust for brain mapping. He directs the Michigan Integrated Circuits Lab and chairs major conferences like ISSCC and DAC. Labs/Teams: Blaauw Lab (University of Michigan) Michigan Integrated Circuits Lab (MICAL)

• Coding Theory
• Network Coding
• Information Theory
• +۴ مورد دیگر

Chih-Chun Wang is a Professor at the Elmore Family School of Electrical and Computer Engineering , Purdue University, with additional leadership roles as Associate Head for Facilities, Planning, and Staff. He earned his Ph.D. in Information Sciences and Systems from Princeton University in 2005, following an M.S. (2002) and B.S. (1999) in Electrical Engineering from Princeton and National Taiwan University, respectively. Research Interests: His work spans Network coding (graph-theoretic capacity, wireless network coding, feedback mechanisms) Coding theory (LDPC codes, Reed-Solomon decoding, iterative algorithms) Information theory (multi-user detection, network information theory) Signal processing (turbo equalization, space-time codes) Control theory (optimal stopping theory) Scientific Contributions: He has published extensively on Age-of-Information (AoI) minimization, low-latency coding, and multi-hop relay optimization. His research trends include Integrating machine learning with network coding Wireless security for Beyond-5G systems Distributed storage networks with intelligent helper selection Delay-constrained communication protocols Awards: Recognized as an IEEE Fellow in 2024 for contributions to network coding and information theory. Teaching: He teaches undergraduate courses like ECE301: Signals and Systems and graduate courses such as ECE639: Error Control Coding , with a focus on iterative decoding, LDPC codes, and network information theory. Advising: Supervised 15+ Ph.D. students, including current advisees Pin-Wen Su (delay-oriented coding), Wonjun Lee (cyber-physical systems), and Giles Bischoff (low-latency systems). Former students hold prominent roles at institutions like Google, Meta, and Intel.

Ken Duffyمشاهده پروفایل

استاد

• Network Coding
• Algorithms
• Probability and Statistics
• +۳ مورد دیگر

Ken Duffy is a Professor and Chair of the Department of Mathematics at Northeastern University, with a joint appointment in the Department of Electrical and Computer Engineering. He joined Northeastern in 2023 and previously served as Interim Chair of the latter department. Previously, he was a professor at the National University of Ireland, Maynooth, where he directed the Hamilton Institute (2016–2022) and co-directed the Science Foundation Ireland Centre for Research Training in Foundations of Data Science. He earned a PhD in Mathematics from Trinity College Dublin. His research focuses on collaborative, multi-disciplinary algorithm design using probability and statistics, with applications in digital circuits, DNA, and network coding. Notable contributions include the Royal Statistical Society’s Applied Probability Section (co-founded in 2011) and numerous award-winning papers in IEEE conferences and journals. Recent work emphasizes decoding algorithms like GRAND (Guessing Random Additive Noise Decoding), applied to error correction, wireless systems, and biomedical imaging. His articles address topics like soft-output decoding, interference mitigation, and cellular lineage tracing. Awards: Best Paper Awards (IEEE ICC 2015, IEEE TNSE 2019), COMSNETS Best Demo (2022–2023), and the IEEE Ellersick Award (2024). Advising: The SFI Centre he co-directed funded over 120 PhD students. Labs/Teams: Hamilton Institute, Royal Statistical Society’s Applied Probability Section, and collaborative projects in cellular dynamics and secure communication.

Ivana Nikoloskaمشاهده پروفایل

استادیار

• Machine Learning
• Quantum Computing
• Communication Engineering
• +۷ مورد دیگر

Ivana Nikoloska is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She is affiliated with the Center for Quantum Materials and Technology Eindhoven and BIASlab (Bayesian Intelligence and Stochastic Agents Lab). Her academic career includes prior roles as a Research Associate at King’s College London and a Visiting Researcher at Aalborg University. PhD: Monash University, Australia (2023) MSc & Dipl.-Ing.: University of Ss. Cyril and Methodius, North Macedonia Research Interests span foundational and applied machine learning, quantum computing, and information/communication engineering. Her work focuses on integrating Bayesian inference, variational methods, and quantum technologies for tasks like signal processing, channel estimation, and power control optimization. Quantum Machine Learning Bayesian Simulation-Based Inference Meta-learning for Wireless Systems Hybrid Quantum-Classical Architectures Stochastic Signal Processing Quantum Sensing & Metrology Notable Trends in Publications include quantum recurrent neural networks with adaptive gating, Bayesian frameworks for quantum sensing, and meta-learning applications in communication systems. She explores variational inference for planning and robust algorithms for channel estimation under non-ideal conditions.

• Communication Theory
• Channel Coding
• Low-Density Parity-Check (LDPC) Codes
• +۳ مورد دیگر

Richard D. Wesel is an Associate Dean for Academic and Student Affairs at a College of Engineering, where he has held leadership roles such as Vice-Chair of the Electrical Engineering Department. With Ph.D. and M.S. degrees in Electrical Engineering from Stanford University and MIT respectively, his research focuses on communication theory and channel coding, particularly low-density parity-check (LDPC) codes and turbo codes for efficient data transmission over noisy channels. Education: MIT (B.S., M.S.), Stanford (Ph.D.) Leadership: Associate Dean, Former Vice-Chair of Electrical Engineering Wesel's research explores advanced techniques for broadcast and multiple-access communication systems, emphasizing applications in wireless LANs, satellite communications, and optical networks. His work integrates machine learning with traditional decoding algorithms, as seen in recent publications on neural-network-optimized LDPC decoding and parallel trellis-stage-combining methods for high-throughput systems. His articles demonstrate a focus on finite-blocklength coding, including CRC-aided list decoding for convolutional and polar codes, and voltage optimization strategies for flash memory reliability. Wesel has authored over 100 publications and led a research group that won the 2006 Design Automation Conference's top award for optical multiple access design. Scientific Awards: National Science Foundation CAREER Award Okawa Foundation Award As an educator, Wesel received the TRW Excellence in Teaching Award in 2000 and has contributed to academic governance through roles on the Faculty Executive Committee and Undergraduate Council. His work bridges theoretical communication systems with practical implementations, including FPGA-based decoders and adaptive coding for fading channels.

Pierre Duhamelمشاهده پروفایل

پژوهشگر

• Digital Signal Processing
• Communication Systems
• Image Compression
• +۶ مورد دیگر

Pierre Duhamel is a researcher affiliated with the Signals and Systems Laboratory, focusing on digital signal processing, communication systems, and multimedia security. His work spans theoretical and applied research in network coding, image compression, and channel coding. Primary affiliation: Signals and Systems Laboratory Research roles: Academic researcher, inventor (patents in image coding) Research interests: Duhamel's work addresses challenges in signal processing (e.g., wavelet transforms, L∞ norm compression), communication systems (e.g., robust decoding, WiMAX MAC protocols), and multimedia security (asymmetric watermarking, screen content coding). He explores optimization techniques for wireless networks and error resilience in multimedia transmission. Recent publications (2024–2025) reflect trends in image and signal processing , network optimization , and communication security , with applications to hyperspectral imaging, turbo coding, and cooperative wireless systems.

Alex Alvaradoمشاهده پروفایل

استاد

• Optical Communications
• Wireless Communications
• Information Theory
• +۳ مورد دیگر

Alex Alvarado is a Full Professor in the Signal Processing Systems department at Eindhoven University of Technology (TU/e), leading the Information and Communication Theory Lab (ICT Lab). He is also affiliated with TU/e's Center for Wireless Technology in Eindhoven. His academic career includes roles as a Senior Research Associate at University College London (2014–2016), Marie Curie Intra-European Fellow (2012–2014), and Newton International Fellow (2011–2012) at the University of Cambridge. Alvarado is a Senior Member of the IEEE and has held editorial and committee positions in major conferences like OFC and ECOC. Alvarado holds an Electronics Engineer degree (2003) and MSc (2005) from Universidad Técnica Federico Santa María, Chile, followed by a Licentiate of Engineering (2008) and PhD (2011) from Chalmers University of Technology, Sweden. His research focuses on high-speed secure data transmission in optical and wireless systems, emphasizing energy-efficient algorithms and theoretical limits of telecommunication systems. Key areas include communication theory, information theory, optical fiber systems, and nonlinear interference mitigation. His recent articles explore advanced modulation formats, machine learning applications for channel estimation and decoding, and innovations in free-space optics and MIMO systems. This work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and responsible consumption through energy-efficient communication solutions. Scientific Awards: ERC Starting Grant (2018) NWO VIDI Grant (2016) 2015 Journal of Lightwave Technology Best Paper Award 2015 IEEE Exemplary Reviewer Award 2018 and 2023 Asia Communications and Photonics Conference Best Paper Awards 2019 Optoelectronics and Communications Conference Best Paper Award Alvarado's advising contributions include supervising 12 research works. His grants include NWO VIDI and ERC Starting funding. He leads projects like NESTOR (Next-gen optical networks) and LaiQa (Quantum Key Distribution). His lab, the ICT Lab, drives theoretical and applied research in communication systems.

Dan Raphaeliمشاهده پروفایل

پژوهشگر

• Trellis Coded Modulation
• Decoding Algorithms
• Turbo Codes
• +۸ مورد دیگر

Dr. Dan Raphaeli is a faculty member at the School of Electrical Engineering within the Iby and Aladar Fleischman Faculty of Engineering at Tel Aviv University. His research focuses on advanced communication systems and signal processing techniques. Trellis Coded Modulation Decoding algorithms and Turbo codes Maximum likelihood equalization analysis Noncoherent detection methods for coded modulation Carrier tracking in mobile communications Multipath fading mitigation Spread spectrum systems and Multiuser CDMA OFDM receiver design Contact: daniraf@tauex.tau.ac.il

H. Vincent Poorمشاهده پروفایل

استاد

• Signal detection & estimation
• Statistical signal processing
• Wireless networking
• +۴ مورد دیگر

H. Vincent Poor is a distinguished academic currently serving as the Dean of Princeton University's School of Engineering and Applied Science and the Michael Henry Strater University Professor of Electrical Engineering. He also holds a Visiting Professor position at Imperial College London's Electrical & Electronic Engineering department. B.E.E. and M.S. in Electrical Engineering from Auburn University M.A. and Ph.D. in EECS from Princeton University His research spans signal processing, information theory, and wireless systems, with a focus on robust techniques, stochastic analysis, and quantum communication. His work has driven advancements in MMSE detection, finite-blocklength coding, and quickest detection theory. He has advised 37 doctoral and 57 postdoctoral researchers, many of whom hold prominent roles globally. His recent publications highlight innovations in communication theory, quantum channels, and detection algorithms. These include foundational work on MMSE multiuser detection, iterative processing in wireless systems, and theoretical frameworks for quickest detection applications. 2011 IEEE Eric E. Sumner Award 2005 IEEE James H. Mulligan, Jr., Education Medal 2002 NSF Director's Award for Distinguished Teaching Scholars Multiple honorary doctorates and fellowships As principal investigator on over 50 research grants, Poor has led groundbreaking projects in signal processing and wireless networking. His visiting roles at institutions like Stanford, Harvard, and Imperial College further underscore his global academic influence.

Øyvind Ytrehusمشاهده پروفایل

استاد

• Coding Theory
• Error-Correcting Codes
• Information Theory
• +۷ مورد دیگر

Øyvind Ytrehus is a Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Bergen (UiB), Norway. He is actively engaged in research and academic supervision, with a focus on coding theory and its applications in communication systems. Research Interests: His primary research areas include Coding Theory , Error-Correcting Codes , Information Theory , Network Coding , Cryptography , and RFID Communication . His work bridges theoretical foundations with practical implementations in wireless and networked systems. The recent publications (2024–2008) reflect a consistent trajectory in coding for communication security, RFID systems, and iterative decoding. Key trends include the use of formally unimodular lattices for secrecy gain, LDPC and turbo codes for erasure channels, and network coding for multicast and delay optimization. His work frequently intersects with physical-layer security and energy-efficient communication. Scientific Contributions: Co-edited special issues on coding theory and applications. Authored foundational work on convolutional codes, stopping sets, and generalized Hamming weights. Contributed to RFID and inductively coupled channel modeling. Advising and Grants: He has supervised several PhD candidates, including Bjørn Møller Greve, Christian W. Otterstad, and Mohsen Toorani. While specific grants are not listed, his extensive publication record and editorial roles suggest active grant involvement in coding and communication research. Labs and Teams: While no specific lab name is mentioned, his collaborations with researchers at Simula UiB, University of Valladolid, and Lancaster University indicate participation in interdisciplinary research networks focused on coding and communication systems.

• Information Theory
• Machine Learning
• Cyber Security
• +۳ مورد دیگر

Fredrik Jönsson is a Senior Lecturer at the Department of Computer Science , Kristianstad University , within the Faculty of Natural Science . His work bridges information theory , machine learning , and cryptography , focusing on applications like cryptanalysis using machine learning and privacy-preserving machine learning . He earned a PhD in Information Theory (2002) and an MSc in Computer Science and Engineering (1997), both from Lund University . His research spans coding theory , stream cipher cryptanalysis , and machine learning for cybersecurity . Research Trends : Recent publications highlight quasi-cyclic codes , finite field GF(17) applications , and CPLEX-based code optimization . Older work includes fast correlation attacks , convolutional codes , and linear code analysis , reflecting his foundational contributions to cryptographic security . Collaborative Projects : Active in projects like Inventering av förutsättningar inför en eventuell ansökan om tillstånd att utfärda examen på forskarnivå , aiming to enhance doctoral degree offerings at Kristianstad University. Teaching : Delivers courses in computer security and supervises bachelor theses in cybersecurity, with a broader background in computer science education .

Masoud Salehiمشاهده پروفایل

دانشیار

• Error Correcting Codes
• Information Theory
• Digital Communications
• +۵ مورد دیگر

Dr. Masoud Salehi is an Associate Professor and Associate Chair for Graduate Studies in the Department of Electrical and Computer Engineering at Northeastern University, USA. He holds a BS (Summa Cum Laude) from Tehran University and MS/PhD from Stanford University. Previously, he worked at Isfahan University of Technology and Tehran University. His research focuses on error-correcting codes, information theory, digital communications, and physical-layer security. He has authored influential textbooks including Communication Systems Engineering (Prentice-Hall) and Contemporary Communication Systems Using MATLAB . Education: BS (Tehran U.), MS/PhD (Stanford U.). Visiting Professor at Eindhoven University of Technology (1988-1989). Research Interests : Network information theory, source-channel matching, data compression, turbo coding, coding for fading channels, digital watermarking. Recent work emphasizes physical-layer security in multi-user wireless networks and jamming mitigation strategies. Grants & Industry : Supported by NSF, GTE, NUWC, CenSSIS, Analog Devices. Consulted for Teleco Oilfield Services and AT&T. Awards : 2024 Outstanding Faculty Service Award. Editorial Board member of International Journal of Electronics and Communications . Key Contributions : Developed precoding techniques for MIMO systems, game-theoretic jamming mitigation, and LDPC decoding algorithms. Active in the Institute of Information Assurance (IIA) and Communications, Control & Signal Processing research group at Northeastern.

• Wireless Communications
• Telecommunications
• Algorithms Design
• +۳ مورد دیگر

Professor Robert G. Maunder is affiliated with the University of Southampton and leads research in wireless communications, algorithms design, and hardware implementation. He has been with the School of Electronics and Computer Science since 2000, advancing from Lecturer to Professor in 2017. BEng (First Class) in Electronic Engineering (2003) PhD in Telecommunications (2007) His research focuses on joint source/channel coding and optimizing wireless communication systems through algorithm-hardware co-design. Recent work includes 5G non-terrestrial networks, OTFS modulation, and quantum code decoding. Key collaborators include Prof. Lajos Hanzo and Prof. Sir Bashir Al-Hashimi. Selected awards: IEEE Senior Member (2012), Chartered Engineer (IET, 2013), Fellow of the IET (2017). He supervises PhD student Arumjeni Mitayani and founded AccelerComm Ltd to commercialize soft-IP solutions.

Sergei Savitskyمشاهده پروفایل

استاد

• Reconfigurable Computing
• Digital Signal Processing
• Hardware Architectures
• +۳ مورد دیگر

Sergei Savitsky is a Professor at Wedel University of Applied Sciences, where he serves as Head of the Bachelor of Computer Science program and Senate Chairman. He has been a university lecturer at the institution since October 2008, following professional experience at NXP Semiconductors (2006-2008) and Philips Research Europe (2001-2006). His educational background includes: Doctorate in Engineering (Dr.-Ing.) from Technical University of Dresden (2002) with distinction "summa cum laude" Habilitation (Dr.-Ing. habil.) from Technical University of Dresden (2024) with teaching authorization in "Technical Computer Science" Diplom-Informatiker (equivalent to MSc) in Computer Science from Technical University of Dresden (1998) Savitsky's research focuses on reconfigurable computing systems , with particular expertise in FPGA design, hardware acceleration, and error correction coding. His work bridges theoretical computer science with practical hardware implementation, resulting in numerous patents and publications in top venues. He has made significant contributions to the development of adaptive hardware architectures for forward error correction, which are critical for modern communication and storage systems. His recent publications demonstrate a strong trajectory in optimizing hardware design processes, with particular focus on applying machine learning techniques like self-organizing maps and gradient descent algorithms to improve FPGA placement efficiency. His research spans both theoretical foundations and practical applications, with patents filed in collaboration with industry partners like NXP Semiconductors and ST-Ericsson. Among his recognitions is the Best Paper Award at CENICS 2019 for his work on accelerating FPGA placement algorithms. As an educator, Savitsky teaches courses related to digital system design, including "Computer-aided design of digital systems," where he emphasizes algorithmic aspects of Electronic Design Automation beyond basic digital technology concepts.