جست‌وجوی استاد و پژوهشگر

• Communications Theory
• Wireless Communications
• Information Theory
• +۱ مورد دیگر

Dr. Ajit Kumar Chaturvedi is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in Communications Theory and Systems. With decades of experience at IIT Kanpur, he has established himself as a leading researcher and educator in wireless communications and information theory. Dr. Chaturvedi earned his B.Tech (1986), M.Tech (1988), and PhD (1995) all in Electrical Engineering from IIT Kanpur, demonstrating his deep institutional commitment. His educational background reflects his dedication to academic excellence at his alma mater. His research focuses on Communications Theory and Systems, with specific expertise in Wireless Communications, Information Theory, and Spread Spectrum Systems. Dr. Chaturvedi's work bridges theoretical foundations with practical applications in modern communication technologies. His contributions have significantly advanced the understanding of signal processing techniques, multiuser detection methods, and error analysis in wireless systems. His research has direct implications for improving the reliability and efficiency of contemporary wireless communication standards. Dr. Chaturvedi's publication record demonstrates consistent contributions to communications engineering, spanning from fundamental signal processing techniques to complex system-level analyses. His work on ISI mitigation, orthogonal sequence design, and error rate analysis shows both theoretical rigor and practical relevance for real-world communication challenges. Distinguished Teacher award of IIT Kanpur (2007) Tan Chin Tuan Fellowship of NTU, Singapore (2008) Supervisor of Best B. Tech Project groups (2002, 2006, 2012) Plenary speaker at the 15th National Conference on Communications (2009) Mentor of IEEE Computer Society International Design Contest winning team (2002) As an educator, Dr. Chaturvedi has supervised numerous award-winning student projects, including three Best B.Tech Project awards. He has mentored teams to international recognition, such as the Microsoft Award for Innovation at the IEEE Computer Society International Design Contest World Finals in 2002. His office is located in ACES 201B at IIT Kanpur, where he continues to contribute to the academic and research mission of the institution.

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.

• Signal Processing
• Image Processing
• Speech Enhancement
• +۳ مورد دیگر

Mohamed Najim is a Professor at IMS Bordeaux (Laboratoire de l'intégration, du matériau au système) affiliated with the University of Bordeaux. He is a member of the Signal and Image Processing research group within the MOTIVE team, where he conducts cutting-edge research in multidimensional signal processing and image analysis. His work spans theoretical developments in signal modeling and practical applications in speech enhancement, image colorization, and communication systems. Professor Najim's research interests focus on advanced signal processing techniques, with particular expertise in autoregressive modeling, Kalman filtering, generative adversarial networks, and multidimensional system analysis. His work bridges theoretical signal processing with practical applications in image processing, speech enhancement, and wireless communications. He has made significant contributions to the development of novel algorithms for texture analysis, channel modeling, and noise reduction in various signal processing contexts. The analysis of his publication record spanning over 25 years reveals a consistent research trajectory focused on fundamental signal processing techniques with expanding applications into modern deep learning approaches. His recent work demonstrates a clear progression from traditional signal processing methods toward integrating machine learning techniques, particularly evident in his 2023 SPDGAN paper which combines manifold learning with generative adversarial networks for image colorization. Throughout his career, Professor Najim has maintained strong theoretical foundations while adapting to emerging technologies in the field. Mohamed Najim has supervised numerous research projects and collaborated extensively with colleagues across institutions. His work shows consistent funding support through participation in various research programs focused on signal processing applications. He has maintained active research collaborations with institutions including CNRS and HESAM University. Professor Najim conducts his research within the IMS laboratory, a leading research center for integration from materials to systems. The laboratory provides state-of-the-art facilities for signal processing research, including specialized computing resources for image processing and speech analysis. His work within the MOTIVE team focuses on developing innovative approaches to complex signal processing challenges across multiple application domains.

Costas N. Georghiadesمشاهده پروفایل

استاد

• Statistical Communication Theory
• Wireless Communications
• Optical Communication Systems
• +۷ مورد دیگر

Costas N. Georghiades is a Professor and Delbert A. Whitaker Chair in the Department of Electrical & Computer Engineering at Texas A&M University. He has held leadership roles including Interim Vice President for Research, Interim Department Head, and Associate Dean for Research in the College of Engineering. His research focuses on statistical communication theory, wireless communication systems, and receiver design. Education: D.Sc., Electrical Engineering, Washington University (1985) M.S., Electrical Engineering, Washington University (1983) B.E., Electrical Engineering, American University of Beirut (1980) Research Interests: His work spans fading channels, space-time coding, distributed source coding, interference rejection techniques, and optical communication systems . He emphasizes applications of information theory to practical communication challenges, including synchronization and equalization in wireless environments. Publications & Trends: Recent articles address advanced topics like faster-than-Nyquist signaling, unsourced random access in MIMO systems, and visible light communication design. His work often bridges theoretical insights with practical implementation challenges in wireless and optical domains. Awards & Recognition: IEEE Fellow (2002) 2012 IEEE Communication Theory Technical Committee Service Award Multiple endowed professorships including the Delbert A. Whitaker Chair Advising & Grants: He has advised over 50 graduate students, many contributing to foundational research in CDMA systems, MIMO detection, and network coding. His grants include support for projects on cognitive radio, OFDM systems, and secure communication protocols. Labs & Collaborations: Active in Texas A&M's Global Cyber Research Institute (GCRI) and affiliated with the Multidisciplinary Engineering program. Collaborates on initiatives like the IEEE Information Theory Society and Hamming Medal Committee.

Tota Sukoمشاهده پروفایل

دانشیار

• Bayesian statistics
• Statistical learning theory
• Business statistics
• +۳ مورد دیگر

Tota Suko is an Associate Professor at the School of Social Sciences, Waseda University, specializing in statistical learning theory and business analytics. With a Ph.D. in Engineering from Waseda University, Dr. Suko leads the Suko Seminar (Management Science Seminar) where students learn to solve business problems using mathematical and management science approaches, primarily through data science techniques including statistical analysis and machine learning. Dr. Suko's research spans multiple domains in statistics and data science. His primary interests include Bayesian statistics, statistical learning theory, business statistics, data mining, and information theory. He has developed methods for analyzing survey data with selection bias, detecting poor responses in questionnaires, and parameter estimation in regression models. His work bridges theoretical statistics with practical applications in business analytics, e-commerce, and even nanotechnology through collaborations with physics researchers. Dr. Suko's recent publications demonstrate a strong trend toward practical applications of statistical methods. His work on generative AI for criminal case law analysis shows innovative application of AI in legal domains, while his research on questionnaire quality control addresses fundamental issues in survey methodology. He has also made significant contributions to theoretical aspects of statistical learning, particularly in the areas of label noise, selection bias, and parameter estimation under non-ideal data conditions. Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research projects Waseda Data Science Consortium industry-academia collaborations Research on nanoscale semiconductor prediction models Development of methods for low-quality data analysis Dr. Suko actively supervises both undergraduate and graduate students through the Suko Seminar. Students work on individual or team projects, participate in data analysis competitions, and present their research at academic conferences. He has developed educational approaches including full-on-demand content for data science education and modularized online statistical teaching materials. Dr. Suko leads the Suko Seminar (Management Science Seminar), which actively collaborates with companies and research institutions. His research team works on diverse projects including analysis of purchasing and browsing histories on e-commerce sites, prediction modeling for nanoscale conduction, and development of methods for low-quality data analysis. The seminar emphasizes both theoretical understanding and practical application of data science techniques to solve real-world business problems.

• Internet Convergence
• Mobile Networks
• Multiuser Detection
• +۷ مورد دیگر

Tero Ojanperä is a Professor of Practice at the Department of Computer Science, Aalto University. His expertise aligns with UN Sustainable Development Goals, focusing on technological advancements and their societal impacts. He has contributed to research in telecommunications, mobile systems, and network convergence through peer-reviewed publications and industry case studies. While specific educational qualifications are not explicitly listed in the provided text, his professional trajectory suggests a strong technical background in computer science and telecommunications. His research interests include internet convergence, mobile network security, 3G/UMTS technologies, multiuser detection systems, and strategic technology market positioning, as evidenced by his work with Nokia and contributions to wireless communication standards. His articles analyze topics such as market-driven technology innovation, mobile security frameworks, and next-generation network protocols. Recent press mentions highlight his post-academic ventures, including founding Silo AI and pioneering projects in artificial intelligence with global implications. Although no scientific awards or grants are listed, his work has been cited 12 times (with 9 citations for the 2006 article on internet convergence and 3 for the Nokia case study). He has not listed formal advisees or lab affiliations in the provided data.

• Signal Processing
• Wireless Communications
• Underwater Acoustic Systems
• +۷ مورد دیگر

Hongya Ge is an Associate Professor in the Department of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT), within the College of Engineering. Her research focuses on advanced signal processing techniques for wireless and underwater communication systems. Research Interests: Her work centers on Signal Processing , Wireless Communications , and Underwater Acoustic Systems , with specific expertise in multiuser detection, CDMA systems, beamforming, reduced-rank filtering, and transceiver optimization. She applies subspace methods and statistical analysis to improve system performance under challenging conditions. Publication Trends: Over her career, Dr. Ge has published extensively on adaptive filtering, interference suppression, and array processing. Her recent work (2013–2019) emphasizes beamformer analysis, SINR loss modeling, and underwater ranging under coherence loss, reflecting a continued focus on robustness and performance limits in real-world environments. Federal Grants from the National Science Foundation (NSF) Principal Investigator on projects related to transceiver optimization and wireless internet challenges Co-PI on interdisciplinary research involving communication systems Scientific Awards: While specific awards are not listed, her sustained research output and leadership in federally funded projects indicate recognition in her field. Labs and Teams: Dr. Ge has collaborated with researchers such as I. P. Kirsteins and Y. Bar-Ness, suggesting membership in a signal processing or communications research group at NJIT, likely involved in both theoretical and applied projects in wireless and underwater systems.

• Information Theory
• Coding Theory
• Statistical Learning Theory
• +۳ مورد دیگر

Shunsuke Horii is an Associate Professor at the Center for Data Science, Waseda University. His research spans information theory, coding theory, statistical learning theory, and data science applications. He actively collaborates with industry through initiatives like the Waseda Data Science Consortium. Education: Ph.D. in Science and Engineering from Waseda University (2009), Master's from Waseda University Graduate School of Science and Engineering (2004). Research Focus: Addresses causal effect estimation in data science using Bayesian decision theory, sparse modeling, and optimization techniques like ADMM and variational inference. Develops efficient algorithms for multiuser communication, matrix completion, and privacy-preserving distributed computing. Teaching: Instructs courses on statistics literacy, data science, and programming with Python/R across multiple academic quarters. Grants: Leads projects funded by Japan Society for the Promotion of Science, including causal inference frameworks, product recommendation systems, and business analytics. Publications: 21 papers with 61 Scopus citations, focusing on LP decoding, Bayesian hierarchical models, and statistical causal analysis.

Rodrigo C. de Lamareمشاهده پروفایل

دانشیار

• Signal Processing
• Wireless Communications
• MIMO Systems
• +۷ مورد دیگر

Rodrigo C. de Lamare is a Reader in the Department of Electronics at the University of York, United Kingdom. He holds a Diploma from UFRJ, an MSc and PhD from PUC-RIO, and is a Member of the Institution of Engineering and Technology (MIET) and Senior Member of IEEE (SMIEEE). His educational background includes a Postgraduate Certificate of Academic Practice from the University of York (2008), a PhD in Structures and algorithms for multiuser detection and interference suppression in DS-CDMA systems from PUC-RIO (2004), a Master's in Speech coding at rates below 2 kb/s from PUC-RIO (2001), and a Diploma in A CELP speech coder for Brazilian Portuguese from UFRJ (1998). Dr. de Lamare's research spans multiple areas of signal processing and communications, with a strong focus on adaptive algorithms for wireless systems. His work addresses fundamental challenges in multiuser detection, interference suppression, beamforming, and space-time processing. He has made significant contributions to reduced-rank adaptive filtering techniques that balance performance with computational complexity, which is crucial for practical implementation in modern communication systems. His publication record shows a consistent trajectory of high-impact research in IEEE journals and conferences, with recent work focusing on large-scale MIMO systems, cooperative communications, and advanced signal processing techniques for next-generation wireless networks. The research demonstrates increasing complexity in addressing interference management in dense wireless environments while maintaining computational feasibility. As an educator, Dr. de Lamare teaches courses in Error Control Coding, Detection and Estimation Theory, Digital Signal Processing, Information Theory, Engineering Mathematics, and Emerging Technologies, reflecting the breadth of his expertise. His academic supervision includes work with PhD students and visiting academics, though specific names are not provided in the available information. His professional activities encompass extensive conference participation and contributions to the academic community through technical program committees and editorial work.

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.

Christopher Roseمشاهده پروفایل

استاد

• Communication Theory
• Information Theory
• Molecular Communication
• +۴ مورد دیگر

Christopher Rose is a Professor of Engineering and Director of STEMJazz Programs at Brown University. He holds an IEEE Fellowship and has served on the Army Science Board. His research spans communication theory applications in molecular systems, wireless networks, and cosmic communication. Rose earned degrees from MIT and has held roles at AT&T Bell Labs and Rutgers University. Education: S.B., S.M., Ph.D. in Electrical Engineering from MIT (1979–1985) Research interests include molecular informatics, communication theory in biological systems, and adversarial information games. He pioneered studies on inscribed matter communication and cosmic signals. Notable achievements include the 2003 Marconi Prize and 2022 IEEE Teaching Award. Collaborates with chemists and computer scientists on projects like molecular memory and chemical computing. Leads STEM initiatives and teaches communication systems courses. Awards: Extensive recognition for teaching and research, including Brown’s ONYX Society Award. Active in editorial roles for IEEE JSAC and Entropy journal.

Raviraj Adveمشاهده پروفایل

استاد

• Wireless Communications
• Radar Signal Processing
• Cooperative Networks
• +۷ مورد دیگر

Professor Raviraj Adve is affiliated with the University of Toronto , working in the Department of Electrical and Computer Engineering and cross-listed with the Electromagnetics Group . He holds a PhD in Electrical Engineering from Syracuse University (1996) and previously worked at Research Associates for Defense Conversion Inc. (1997–2000). Education: B.Tech, Indian Institute of Technology Bombay (1990) PhD, Syracuse University (1996) Research Interests span two main areas: Wireless Communications (heterogeneous networks, massive MIMO, cooperative communication, resource allocation) and Radar Signal Processing (waveform diversity, space-time adaptive processing, HF radar systems). His work emphasizes practical algorithm development for real-world constraints. Scientific Contributions include 15 recent articles covering cooperative networks , radar clutter modeling , low-complexity MIMO algorithms , and molecular communication . Notable awards: IEEE Fellow (2017), Young Radar Engineer of the Year (2009), and multiple teaching awards. Leadership Roles: Vice-chair of IEEE Radar Systems Panel, Associate Editor for IEEE Trans. on Aerospace and Electronic Systems , and editorial board member for IET Trans. on Radar, Sonar and Navigation .

• Signal Processing
• Digital Communications
• Machine Learning Applications
• +۳ مورد دیگر

Rafael Boloix Tortosa is an Associate Professor in the Department of Signal Theory and Communications at the University of Seville's School of Engineering, where he leads significant research in complex-valued signal processing and its applications. His academic career spans over two decades with continuous involvement in national and international research projects. His research focuses on advancing complex-valued signal processing methodologies, particularly complex Gaussian processes, kernel methods, and widely linear estimation techniques. These theoretical advances are applied to diverse domains including medical imaging (especially burn wound analysis), wireless communications (UWB positioning, OFDM systems), and art conservation. His work bridges fundamental signal processing theory with practical engineering solutions. Professor Boloix Tortosa maintains an active publication record with significant contributions in top IEEE journals, particularly in signal processing and machine learning. His recent work (2025-2019) demonstrates continued innovation in complex-valued machine learning methods, while his earlier publications established foundational work in blind source separation and multiuser detection. He actively participates in multiple research projects including EU-funded initiatives like COURAGEOUS (counter-UAS solutions) and ARIADNE (agricultural drones), alongside national projects in medical imaging and communications. His research group has received consistent funding through the TIC-155 consolidation incentives. His laboratory work centers around the Signal Processing and Communications Research Group, where he develops both theoretical frameworks and practical implementations for signal processing challenges. The group maintains strong connections between theoretical advances and real-world applications across multiple engineering domains.

• Signal Processing
• Digital Communications
• Wireless Communications
• +۳ مورد دیگر

Francisco Javier Payán Somet is a Full Professor in the Department of Signal Theory and Communications at the University of Seville. His research focuses on signal processing, digital communications, and wireless systems, with a strong emphasis on OFDM systems, Gaussian processes, and digital filter design. Research Group: Signal Processing and Communications Projects: Flexible Automated Software for Testing, CITIUS, PLATINO, and others. His research interests include Signal Processing , Digital Communications , Wireless Systems , Gaussian Processes , and Recursive Digital Filters . His work spans theoretical and applied domains, including hardware development for antennas and GPS equipment. The trends in his recent articles highlight advancements in complex-valued signal analysis , blind equalization schemes , and higher-order statistics for communication systems . Earlier works focus on low-frequency oscillators and digital filter stability . He has participated in numerous projects, including the Consolider-Ingenio Program and grants for the TIC-155 Research Group . His research support includes international collaboration incentives. He is affiliated with the Signal Processing and Communications research group at the University of Seville, contributing to both academic and industrial applications in telecommunications.