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Hongyu AnView profile

Assistant Professor

• Neuromorphic Computing
• Energy-efficient Neuromorphic Electronic Circuit Design
• Artificial Intelligence
• +8 more

Hongyu An is an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Technological University. He holds affiliations with the Computer Science and Biomedical Engineering departments. Dr. An leads the BrainX Lab (Neuromorphic Robotics Lab and Neuromorphic Brain-Machine Interface Lab) and collaborates with the Institute of Computing and Cybersystems (ICC). He earned his PhD, MS, and BS in Electrical Engineering from Virginia Tech, Missouri University of Science and Technology, and Shenyang University of Technology respectively. Research Interests: Dr. An focuses on neuromorphic computing and its applications in AI hardware , robotics , and medical devices . His work spans memristor-based circuits , spiking neural networks , and energy-efficient AI systems . Key projects include associative learning in neuromorphic robots , neural prosthetics for memory restoration , and power-efficient adaptive deep brain stimulation systems . Publications & Research: With over 15 significant publications since 2016, Dr. An's work demonstrates expertise in 3D neuromorphic IC design , memristor reliability , and self-learning robotic systems . His research has appeared in journals like IEEE Transactions on Computing Aided Design and Frontiers in Computational Neuroscience. Awards & Funding: Bill and LaRue Blackwell Dissertation Award NSF CRII and ERI Awards USAF VFRP Fellowship Best Paper Nomination (2017 ISQED) Students & Collaborations: Dr. An mentors PhD students Tianze Liu and Md Abu Bakr Siddique, undergraduate Lucas Haddad, and volunteers like Vinay Kumar Pillalamarri. His team collaborates with Dr. Yan Zhang on neuromorphic brain-machine interfaces . The lab operates advanced infrastructure including LabLynx wireless neural recording systems and Intel Loihi-2 neuromorphic servers .

Alan BovikView profile

Professor

• Image and Video Processing
• Digital Television
• Digital Cinema
• +5 more

Alan Bovik is a Professor at The University of Texas at Austin, holding the prestigious Cockrell Family Endowed Regents Chair in Engineering. He serves as Director of the Laboratory for Image and Video Engineering (LIVE) and maintains dual faculty appointments in the Department of Electrical and Computer Engineering and the Institute for Neuroscience. His extensive contributions have established him as a leading authority in visual information processing with global impact. Dr. Bovik's research spans multiple domains with a primary focus on image and video processing, digital television and digital cinema, computational vision, and visual perception. His work has fundamentally advanced the understanding of human visual perception, leading to practical applications in video quality assessment and image processing systems. With over 800 technical publications cited more than 75,000 times and an H-index above 100, his research has had extraordinary impact across academia and industry. He is recognized as a Highly-Cited Researcher by Clarivate Analytics, placing him among the most influential researchers globally. Analysis of Dr. Bovik's recent publications reveals a strong emphasis on video quality assessment for emerging applications like user-generated content, high-motion streaming, and adaptive video delivery. His work seamlessly integrates deep learning approaches with traditional signal processing techniques to develop perceptually accurate models. There's a clear trend toward addressing practical challenges in video streaming quality, compression artifacts, and the unique characteristics of modern video content. His research bridges theoretical foundations with real-world applications, making significant contributions to both academic understanding and industry standards. Dr. Bovik's exceptional contributions have been recognized with numerous prestigious awards: IEEE Fourier Award (2019) for seminal contributions to perception-based image and video processing Edwin H. Land Medal (2017) from The Optical Society Primetime Emmy Award for Outstanding Achievement in Engineering Development (2015) Norbert Wiener Society Award (2013) Claude Shannon / Harry Nyquist Technical Achievement Award (2005) Multiple best paper awards from IEEE, EURASIP, and Picture Coding Symposium As an educator and mentor, Dr. Bovik has guided numerous students through his leadership at LIVE. His professional service includes founding and serving as Editor-in-Chief of the IEEE Transactions on Image Processing (1996-2002) and chairing the inaugural IEEE International Conference on Image Processing in 1994. His industry impact is substantial, evidenced by his Primetime Emmy Award and frequent consultation with major institutions. Dr. Bovik is also a registered Professional Engineer in Texas, demonstrating his practical engineering expertise alongside theoretical contributions. Dr. Bovik leads the Laboratory for Image and Video Engineering (LIVE), which maintains strong affiliations with multiple research centers including the Wireless Networking and Communications Group (WNCG), Center for Perceptual Systems, Telecommunications and Signal Processing Research Center, and Institute for Computational Engineering and Sciences. These interdisciplinary connections enable research that bridges engineering, neuroscience, and computer science to advance our understanding of visual perception and processing.

Tuğçe BilenView profile

Assistant Professor

• Artificial Intelligence
• Computer and Communication Networks
• Digital Twin
• +4 more

Tuğçe Bilen is an Assistant Professor at Istanbul Technical University's Department of Artificial Intelligence and Data Engineering, within the School of Computer and Informatics. Her research focuses on Artificial Intelligence and Computer and Communication Networks, particularly Digital Twin technologies, 6G wireless systems, and smart IoT applications. PhD in Computer Engineering (2017-2022), Istanbul Technical University Master's in Computer Engineering (2016-2017), Istanbul Technical University Licence in Computer Engineering (2010-2015), Istanbul Technical University Her research explores Digital Twin middleware for smart farms, energy-aware task scheduling in 6G edge networks, aeronautical ad-hoc network optimization, and cloud-based protocol enhancements. Recent work addresses metaverse-driven supply chain optimization and secure routing for aircraft networks. Key publication trends show strong focus on: Digital Twin integration across domains 6G wireless network architectures Adaptive routing algorithms Energy-efficient IoT systems Security in airborne communication Machine Learning for network management Scientific recognition includes: Serhat Özyar Young Scientist of the Year Honorary Award (2023) Doctoral Thesis Award from Istanbul Technical University (2023) TÜBA Doctoral Science Awards-Teknofest (2023) She serves as Principal Investigator for the Unsupervised Learning-Based Management of Ad Hoc Airborne Network Topology project (2024-2026) and holds a patent for Parametric Parsing Based Routing System in Content Delivery Networks (2021). As IEEE member since 2015, she contributes to telecommunications standards.

Manuel Jesus Espinosa GaviraView profile

Researcher

• Power Quality Analysis
• Wireless Sensor Networks
• Smart Grid Technologies
• +3 more

Manuel Jesus Espinosa Gavira is a researcher at the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cádiz, Spain. He is affiliated with the TIC168 Computational Instrumentation and Industrial Electronics research group under the Information and Communication Technologies PAIDI area. Research Focus: His work centers on power quality analysis, wireless sensor networks, and smart grid technologies. Key contributions include developing instrumentation systems for voltage supply characterization, cloud-induced photovoltaic transient analysis, and synchronized sensor networks for industrial applications. His PhD thesis (2023) explored sensor networks for short-term solar prediction in microgrids and smart cities. Publications Trends: Recent work focuses on higher-order statistics (HOS) for power quality monitoring, photovoltaic plant optimization using weather forecasts, and frequency domain analysis for grid stability. These publications reflect expertise in computational instrumentation, renewable energy integration, and real-time monitoring systems.

Marchegiani Maria LetiziaView profile

Assistant Professor

• Signal Processing
• Machine Learning
• Robotics
• +9 more

Maria Letizia Marchegiani is an Assistant Professor at the University of Parma , affiliated with the Department of Engineering and Architecture . Previously, she held academic positions at Aalborg University (2019) and Oxford Robotics Institute (2014-2018). Education: PhD in Computer Science and Engineering from Sapienza - University of Rome , MSc/BEng in Computer Engineering Her research interests span signal processing , machine learning , and their applications to robotics , autonomous systems , intelligent transportation , and intelligent healthcare . She explores intersections between auditory perception , cognitive modeling , and energy-efficient wearable systems . Recent publications demonstrate expertise in acoustic event localization , ML-SDWSN architectures , thermal camera integration for vehicles, and privacy-preserving wearable systems . Her work addresses challenges in network reliability , urban soundscapes , and human-robot collaboration .

• Internet of Things (IoT)
• Machine Learning
• Smart Agriculture
• +9 more

Laura Belli is a Researcher at the Department of Engineering and Architecture , University of Parma, with a focus on interdisciplinary projects bridging IoT, Machine Learning, and Smart Systems . Her work spans smart agriculture, vehicular networks, and urban mobility. Research Interests: Internet of Things (IoT) in agriculture and transportation Machine Learning for predictive modeling and data analysis Edge Computing and network optimization Blockchain applications in data integrity Driver health and stress monitoring Recent Publications highlight her contributions to privacy-preserving vehicular systems , smart farming datasets , and adaptive IoT protocols . She collaborates on projects like OPEVA and DistriMuse , emphasizing data-driven innovation.

Matthias BeckerView profile

Professor

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +6 more

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

Ahmed AhmedView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Machine Learning
• +5 more

Ahmed Ahmed, an associate professor in the Department of Computer Science at Prairie View A&M University (PVAMU) , shapes tech leaders through innovative teaching and research. His work spans IoT, AI, and ML applications across agriculture, infrastructure monitoring, and healthcare. Key research areas include: IoT and AI for sustainable agricultural practices LoRa-based location tracking in constrained environments Secure blockchain-federated learning systems Geofencing for community safety With over 50 peer-reviewed publications and a $300k NSF grant (2023), Ahmed develops hands-on learning tools like a Special Interest Group for IoT and live programming demonstrations. His global journey—from Cairo University to a PhD at the University of Saskatchewan—fuels his commitment to empowering underrepresented students. Scientific awards include the PVAMU Faculty Service Award . He advises students like Kritika Singh (2022 graduate) and advocates for continuous refinement of teaching as a craft.

• Terahertz Science
• Biomedical Engineering
• Medical Imaging
• +3 more

Zachary Taylor is an Associate Professor at Aalto University's School of Electrical Engineering, specializing in terahertz science and biomedical engineering. His research focuses on advanced imaging and spectroscopy techniques for medical diagnostics. Specialized in terahertz and microwave-optical systems Recipient of Aalto University Doctoral Thesis Award Active in IEEE Transactions and IRMMW-THz conferences His work spans innovative technologies like Gaussian beam analysis for corneal sensing, quasioptical calibration methods, and frequency diversity applications in holography. Recent publications highlight his contributions to radiation oncology predictive modeling and millimeter-wave measurement systems. Key research domains include: Terahertz biomedical imaging Microwave-optical component integration Computational electromagnetic modeling MRI-guided radiotherapy prediction Reflective optical system design Precision calibration techniques Scientific Recognition: Aalto University School of Electrical Engineering Doctoral Thesis Award Prof. Taylor leads the Zachary Taylor Group, advising multidisciplinary researchers across terahertz science, medical physics, and computational modeling. His team's recent work demonstrates cross-domain applications from corneal diagnostics to cancer treatment prediction.

Pierre DuhamelView profile

Researcher

• Digital Signal Processing
• Communication Systems
• Image Compression
• +6 more

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.

Susan K. CohenView profile

Associate Professor

• Innovation
• Organizational Theory
• Entrepreneurship
• +6 more

Susan K. Cohen serves as Associate Professor of Organizations and Entrepreneurship at the University of Pittsburgh's Katz Graduate School of Business, where her research investigates how firms achieve innovation success through organizational capabilities, social networks, alliance structures, and ecosystem strategies. Her work integrates resource-based theory, social network analysis, and complex contagion frameworks to advance knowledge in innovation commercialization. Her academic credentials include a PhD in Strategic Management from the University of Minnesota (1998) and a BS in Management Information Systems from Clarkson University (1986). Professor Cohen's research spans innovation dynamics, entrepreneurial ecosystems, knowledge management, and strategic alliance formation. She examines firm-specific language in life science business model transformation and analyzes how regional entrepreneurial ecosystems influence new venture resource acquisition strategies. Her current work emphasizes practical applications for improving innovation outcomes in complex technological environments. Analysis of her recent publications reveals consistent focus on innovation barriers and enablers across industries including biotechnology, machine tools, and wireless communications. Her work demonstrates evolving emphasis on ecosystem-level factors and cross-sector collaboration, with increasing attention to assistive technology translation and regional economic development. Scientific recognition includes: Distinguished Reviewer Award, Academy of Management Discoveries (2018) She has secured over $4.5 million in research funding through grants from NSF, NIDILRR, PPG Foundation, and University of Pittsburgh initiatives. Key projects include IMPACT Grant on community development ($4.5M), Pitt Seed Grants for entrepreneurial ecosystem diversity ($48,972), pharmaceutical R&D productivity studies ($7,000), and global innovation conferences sponsored by Bayer/Alcoa/PPG. Her editorial leadership includes Associate Editorship at Academy of Management Discoveries and TIM Division Program Chair-Elect role at the Academy of Management. Professor Cohen directs experiential learning initiatives including Commercializing New Technologies and Leading Organizations to Innovate courses, while co-organizing industry-academic partnerships like the Global Collaboration for Technological Innovation conference series.

Nikos GiatrakosView profile

Assistant Professor

• Big Data Management
• Internet of Things (IoT)
• Distributed Systems
• +3 more

Nikos Giatrakos is an Assistant Professor at the School of Electronic & Computer Engineering, Technical University of Crete, and a core member of the Software Technology and Network Applications Lab (SoftNet) . His work bridges Big Data systems, IoT, and advanced analytics, with a focus on real-time processing and scalable architectures. Previously, he served as a postdoctoral researcher at the same laboratory. Education PhD in Computer Science, University of Piraeus (2012) Postgraduate Diploma in Information Systems, Athens University of Economics and Business (2008) BSc in Computer Science, University of Piraeus (2006) Research Focus : Nikos specializes in software architectures for Big Data streaming, including Distributed Big Data Processing , Federated Machine Learning , Cloud-to-Edge Data Management , and Approximate Query Processing . His work has also advanced Complex Event Processing and Outlier Detection in decentralized environments. Scientific Contributions : His research has led to the DAG* workflow optimizer for IoT, the SuBiTO framework for real-time neural learning, and the INFORE approach for cross-platform analytics. He received the Best System Demonstration Award at ACM CIKM 2020 for INforE. Academic Leadership : Nikos teaches Object-Oriented Programming, Data Science, and Distributed Systems. He has supervised numerous European and national grants as Principal Investigator and served on program committees for top-tier conferences like SIGMOD, VLDB, and DEBS.

• Signal Processing
• Wireless Communications
• Information Theory
• +5 more

Luis Castedo Ribas is a Professor at the Faculty of Informatics , University of A Coruña (UDC) , Spain, since 2001. Previously held research positions at the University of Southern California (USC) and École supérieure d'électricité (SUPELEC). PhD in Telecommunications Engineering (1993), Technical University of Madrid Department of Computer Engineering Research Group: Electronic and Communications Technology Group Research Interests: Specializing in Signal Processing and Information Theory for Wireless Communications Engineering , with focus on MIMO Communication Systems , 5G Radio Interfaces , Joint Source-Channel Coding , and High-Speed Wireless Communications . His work bridges theoretical advancements with practical prototyping of digital communication systems. Recent Article Trends: Publications span Massive MIMO , Beamforming , AI/ML for Wireless , and Quantum-Inspired Coding , reflecting his leadership in evolving telecom standards (5G→6G). Collaborative work with institutions like IEEE and European consortia. Scientific Awards: Best Student Paper (2007, 2013, 2017) General Co-Chair, IEEE Sensor Array Workshop (2014) General Co-Chair, European Signal Processing Conference (2019) Grants & Collaborations: Principal Investigator in over 50 projects funded by Spanish Ministry of Science, EU programs, and companies like Atos Origin. Key roles in national and international research consortia.

• Multi-objective optimisation
• Evolutionary computation
• Explainable artificial intelligence
• +4 more

Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.

• 5G/6G Systems
• Next-Generation Wi-Fi
• Wireless Internet of Things
• +4 more

Evgeny Khorov is a Full Professor and Deputy Chair at Moscow Institute of Physics and Technology (MIPT) and Head of the Wireless Networks Lab at the Institute for Information Transmission Problems of the Russian Academy of Sciences (IITP RAS) and the Telecommunication Systems Lab at Higher School of Economics (HSE). His research focuses on 5G/6G systems , next-generation Wi-Fi , Wireless IoT , and QoS-aware optimization. Ph.D. (2012) and D.Sc. (2022) in Telecommunications from IITP RAS and MIPT Visiting Research Fellow at King's College London (2015) His work includes mathematical modeling of networking protocols, Wi-Fi standardization (IEEE 802.11), and contributions to Wi-Fi 6 (802.11ax) and Wi-Fi 7 (802.11be) . He supervises students and has co-authored over 200 papers. Recent articles highlight advancements in Wi-Fi 7/8 , URLLC , 5G multi-connectivity , and machine learning for traffic classification . Scientific Awards: Best Demo Award, ACM Mobihoc (2022) Best Paper Awards: IEEE ISWCS (2012), Elsevier Computer Communications (2018), IEEE PIMRC (2019) Moscow & Russian Government Prizes for Young Scientists (2013, 2016) Scopus Award Russia (2018) Best Cooperation Project Leader (multiple times) He serves as Editor-in-Chief of Problems of Information Transmission (since 2024) and chairs major IEEE conferences (Globecom 2018 Workshop, BlackSeaCom 2019).