جست‌وجوی استاد و پژوهشگر

• Wireless Communication Systems
• Signal Processing
• Network Security
• +۳ مورد دیگر

Mustafa Matalgah is a Professor of Electrical and Computer Engineering at the University of Mississippi. He holds a B.S. from Yarmouk University (1987), an M.S. from Jordan University of Science and Technology (1990), and a Ph.D. from the University of Missouri-Columbia (1996). His research focuses on wireless communication systems, signal processing, and network security with a particular emphasis on UAV networks, fading channel analysis, and cooperative diversity techniques. Professor Matalgah has published extensively in top-tier journals and conferences, contributing to advancements in aviation communication systems, encryption algorithms for IoT, and relay-based cooperative networks. His work spans theoretical analysis of channel models, practical implementations of communication protocols, and real-time data transmission systems. Education: B.S. Electrical Engineering, Yarmouk University (1987) M.S. Electrical Engineering, Jordan University of Science and Technology (1990) Ph.D. Electrical Engineering, University of Missouri-Columbia (1996) Research Interests: Professor Matalgah’s research explores cutting-edge topics in wireless communication, including UAV networks, machine learning for drone activity classification, and robust encryption methods for IoT devices. He investigates the impact of fading channels on signal performance and develops protocols to enhance reliability in cooperative relay systems. His work often bridges theoretical models (e.g., outage probability analysis) with practical implementations (e.g., real-time flight data recorders). Advancing Communication Technologies: His articles highlight contributions to aviation safety through ground-based aircraft recorders, satellite data transfer optimization, and VHF digital link design. He also addresses challenges in mobile networks, such as enhancing throughput in V2X (vehicle-to-everything) systems and improving error performance in cryptographic transmissions over noisy channels.

Constantinos Koliasمشاهده پروفایل

دانشیار

• Computer Security
• Network Security
• Cybersecurity
• +۳ مورد دیگر

Constantinos (Costas) Kolias is an Associate Professor in the Department of Computer Science at the University of Idaho, part of the College of Engineering. His expertise lies in cybersecurity, network security, and IoT security. He teaches courses such as CS 404/504 Advanced Security Incident Identification and CS 438/538 Network Security. His research focuses on cutting-edge areas like fuzzing techniques, electromagnetic signal analysis for anomaly detection, and securing industrial control systems. He is affiliated with the University of Idaho’s Idaho Falls campus and actively contributes to advancing cyber resilience through software-defined networking and machine learning applications. His work addresses challenges in detecting lateral movement, mitigating DDoS attacks, and ensuring compliance with industrial cybersecurity standards like IEC 62443-3-3. While no specific awards or grants are detailed here, his extensive publication record highlights contributions to both theoretical and applied cybersecurity research. He maintains an active presence in critical infrastructure security, embedded systems protection, and IoT device vulnerability analysis, reflecting a commitment to bridging academic research and real-world security solutions.

Omer Aliمشاهده پروفایل

مدرس

• Machine Learning
• Artificial Intelligence
• Internet of Things (IoT)
• +۴ مورد دیگر

Omer Ali is a Lecturer (Software Development) at the Department of Computing, South East Technological University (SETU) Carlow campus. His research focuses on Machine Learning, Internet of Things (IoT), and Embedded Systems, with a particular emphasis on energy optimization and sustainable technology integration. Education: PhD in Electrical Engineering (Universiti Sains Malaysia, 2006–2022) MSc in Communications Engineering (University of Manchester, 2007–2008) BSc in Computer Systems Engineering (Bahauddin Zakariya University, 2001–2005) His work explores adaptive machine learning for real-time battery state estimation, energy-efficient wireless sensor networks, and IoT middleware integration. Recent publications highlight trends in AI/IoT for sustainable smart cities and battery health monitoring in low-power electronics. Scientific Awards: 3MT Thesis Winner (2021) Ali has contributed to 23 research outputs, including a 2022 article in Sensors with 84 Scopus citations, and actively engages in peer-review activities for journals like IEEE Access. His research aligns with UN Sustainable Development Goals, particularly in education and sustainability.

Elaine Chenمشاهده پروفایل

استاد

• Startup Entrepreneurship
• Corporate Innovation and Entrepreneurship
• Mission-Driven Ventures
• +۳ مورد دیگر

Elaine Chen is the Cummings Family Professor of the Practice in Entrepreneurship and Director of the Derby Entrepreneurship Center at Tufts University's School of Engineering. She holds a BS and MS in Mechanical Engineering from MIT. Her expertise spans entrepreneurship education, corporate innovation, and mission-driven ventures. She oversees the Entrepreneurship Minor program and co-curricular initiatives like accelerators and internships, fostering diverse student engagement. Previously, she served as Senior Lecturer at MIT's Martin Trust Center, developing scalable entrepreneurship programs. She is a board member at the Center for Open Science and Cybernetix Ventures. Notable awards include the MIT Monosson Prize for mentoring and recognition as an Invention Ambassador by AAAS and the Lemelson Foundation. Education: Master of Science, Mechanical Engineering, MIT, 1993 Bachelor of Science, Mechanical Engineering, MIT, 1991 Research Interests: Elaine focuses on advancing entrepreneurship education through equitable access, corporate innovation strategies, and supporting startups and non-profits. Her work emphasizes mentorship, digital infrastructure, and global entrepreneurship, particularly in Asia-Pacific regions. Awards: MIT Monosson Prize for Entrepreneurship Mentoring Invention Ambassador, AAAS and Lemelson Foundation Advising & Grants: She advises students through experiential courses like Entrepreneurial Internship and Field Study. Her consulting firm, ConceptSpring, assists corporations in innovation across healthcare, FinTech, and government sectors. She holds 22 patents and has led product development at companies like Rethink Robotics and Zeo. Labs & Teams: Leads the Derby Entrepreneurship Center, fostering cross-disciplinary innovation and student ventures through workshops, accelerators, and grants.

Alice Wangمشاهده پروفایل

استادیار

• Low-Power Electronics
• Energy Harvesting
• Circuit Design
• +۳ مورد دیگر

Alice Wang is an Assistant Professor of Instruction in the Department of Computer Science at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. Her research focuses on low-power electronics, energy harvesting systems, and advanced circuit design for mobile and embedded applications. She has contributed to innovations in ultra-low-power (ULP) SoCs, wireless sensor networks, and energy-efficient processor architectures. Key research interests include optimizing energy consumption in 3D-ICs, developing self-powered systems using multimodal energy harvesting, and improving thermal and power management in integrated circuits. Her work spans topics such as low-voltage circuit design, wake-up receiver architectures, and adaptive voltage scaling techniques for mobile processors. Her publications highlight advancements in low-power radio design, thermal-aware system architectures, and hardware-software co-optimization strategies. Recent work emphasizes industrial IoT applications, machine health monitoring systems, and energy-efficient embedded computing solutions. No academic awards or grants are explicitly mentioned in the provided texts. She has advised no students listed in the current data. Her research often intersects with industry challenges in battery-operated devices and scalable microsensor networks.

Phillip De Leonمشاهده پروفایل

استاد

• Digital Signal Processing (DSP)
• Machine Learning
• Speech Processing
• +۳ مورد دیگر

Phillip De Leon is an accomplished academic and administrator serving as Associate Vice Chancellor for Research and Chief Research Officer at the University of Colorado Denver. He is also a Professor in the Department of Electrical Engineering within the College of Engineering, Design and Computing. His career includes prior roles as a Professor at New Mexico State University, where he held distinguished professorships for teaching excellence and research leadership. Dr. De Leon leads CU Denver’s strategic research initiatives, emphasizing interdisciplinary collaboration and innovation across diverse academic programs. His research focuses on Digital Signal Processing (DSP), with specializations in machine learning, speech processing (including speaker recognition and speech enhancement), time-frequency analysis, and embedded systems. His work has been supported by agencies such as the Air Force Research Laboratory, Army Research Laboratory, NSF, NASA, and Sandia National Laboratories. He has authored numerous publications in DSP, addressing topics like spoofing detection, spectral analysis, and biomedical signal applications. Education: PhD in Electrical Engineering (prior academic details not specified) Dr. De Leon’s research trends reflect a strong emphasis on security applications of signal processing, such as anti-spoofing for voice authentication systems, and practical implementations of advanced DSP techniques. His recent work explores instantaneous frequency analysis, embedded system optimizations, and machine learning for healthcare monitoring (e.g., falls risk prediction in elderly populations). His professional service includes roles such as Associate Dean of Research and Chief Science Officer, demonstrating leadership in both academic governance and scientific innovation. He maintains active collaborations with industry and government agencies to advance applied research outcomes.

• Machine Learning
• Internet of Things
• Biomedical Signal Processing
• +۲ مورد دیگر

Md Abu Sayeed is an Assistant Professor in Electrical and Computer Engineering at Stevens Institute of Technology. His research develops IoT-enabled medical devices for epilepsy and sleep apnea management, emphasizing energy efficiency and real-time processing. Research Focus: Machine learning applications in biomedical edge devices, low-power sensor systems, and IoT healthcare solutions. Current projects include seizure detection wearables and AI-driven drug delivery systems. Students Advised: Harshil Patel Bathini Shravan Kumar Sunil Virendra Gupta Yash Rajendra Ambetkar Pranay Saha (past) Awards: IEEE MetroCon Best Poster Award (2018) Tolouse Graduate School Dean’s Award (2016)

Shervin Erfaniمشاهده پروفایل

استاد

• Computer & Network Security
• Data Networking
• Communication Network Management
• +۳ مورد دیگر

Dr. Shervin Erfani is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor, Faculty of Engineering. His research focuses on computer and network security, data networking, communication network management, and multidimensional digital filter realization. He holds a position in 3048 CEI and can be reached at erfani@uwindsor.ca. His research interests span a wide range of topics, including IoT security, signal processing in linear time-varying systems, and fractional calculus applications. Recent work emphasizes bifrequency analysis, iterated Laplace transforms, and fractional differential equations. His contributions bridge theoretical advancements with practical implementations in security frameworks and network protocols. Publications highlight trends in secure communication architectures, such as Bitcoin security models and IoT applications, alongside foundational work in signal processing and circuit theory. Collaborations address challenges in network management, spectrum sensing, and system stability.

Alioune Ngomمشاهده پروفایل

استاد

• Bioinformatics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Dr. Alioune Ngom is a Professor and Graduate Program Chair at the School of Computer Science, University of Windsor. He holds a Ph.D. in Computer Science from the University of Ottawa with additional graduate degrees in the field. Dr. Ngom founded Genesis Genomics Inc. and maintains affiliations with this organization. His research spans multiple interdisciplinary domains with primary focus areas including: Bioinformatics and computational biology (DNA microarray analysis, mitochondrial genomics) Machine learning applications (clustering, classification, neural networks) Network optimization (wireless mobile networks, scheduling) Computational methods in biomedicine (protein structure prediction, drug discovery) Recent publications demonstrate strong focus on AI integration in life sciences, particularly graph neural networks for drug discovery and multi-modal learning frameworks. Publication trends show increasing emphasis on transformer architectures, trustworthy AI systems, and clinical applications of deep learning. Dr. Ngom mentors graduate students as evidenced by his role as Graduate Program Chair.

Halil Yetginمشاهده پروفایل

مدرس

• Wireless Networks Optimization
• Multi-Objective Optimization
• AI for Wireless Networks
• +۷ مورد دیگر

Dr. Halil Yetgin is a Lecturer in Computing Science at the Department of Computer Science, Middlesex University, within the Faculty of Science and Technology. His expertise spans wireless networks optimization, AI-driven solutions, and IoT automation. He holds a PhD in Wireless Communications from the University of Southampton and has held academic roles in Turkey and Slovenia. Teaching Roles: Module Leader for CST2133 (Data Science and Machine Learning) and CST3133 (Advanced Topics in Data Science/AI) Programme Leader for BSc Computer Science (Systems Engineering) Research Focus: Lifetime optimization of wireless networks Multi-objective optimization using evolutionary algorithms (e.g., NSGA-II) AI applications in IoT, vehicular networks, and UAV systems Zero-touch IoT provisioning and anomaly detection Publications & Collaborations: Over 20 peer-reviewed articles in journals like IEEE Transactions and conferences (ENASE, WCNC) Contributions to EU-funded projects and IEEE technical committees Editorial roles in several journals Advising: Supervised multiple MSc and PhD students in AI-driven wireless systems and optimization. Labs/Teams: Active in the Next Generation Wireless Research Group and collaborations with Jožef Stefan Institute.

• computer architecture
• VLSI design
• computer graphics
• +۱ مورد دیگر

Dr. Paul Gillard is a retired Professor in the Department of Computer Science at Memorial University of Newfoundland. His research focuses on computer architecture, VLSI design, computer graphics, and wireless protocols. He is affiliated with the Centre for Digital Hardware Applications Research. Education: B.Sc. in Computer Science, Memorial University M.Sc. in Computer Science, Memorial University Ph.D. in Computer Science, Memorial University Teaching: He instructs courses including CS3724 (Computer Organization), CS3725 (Computer Architecture), CS4723 (Introduction to Microprocessors), CS4725/EE8863 (VLSI Design), and CS4751 (Computer Graphics). His course materials emphasize practical lab work, programming (C and assembly), and project-based learning. Research & Projects: Dr. Gillard leads the Centre for Digital Hardware Applications Research, focusing on digital hardware and embedded systems. His courses involve hands-on projects with microprocessors, sensors, and circuit design. Awards: No scientific awards explicitly mentioned. Labs & Teams: He oversees laboratory modules in microprocessor interfacing, embedded systems, and analog/digital electronics. Course labs include work with AVR microcontrollers, SPI protocols, and sensor integration.

Bayaner Arigongمشاهده پروفایل

استادیار

• RF/Microwave Passive Circuit Design
• Beamforming Phased Array Antenna
• RF Power Amplifier Design
• +۶ مورد دیگر

Dr. Bayaner Arigong is an Assistant Professor in the Department of Electrical & Computer Engineering at Florida A&M University - Florida State University. He holds a Ph.D. in Computer Science and Engineering from the University of North Texas (2015), and M.Sc. and B.Sc. degrees in Electrical Engineering from China University of Geosciences, Wuhan (2008 and 2005). Prior to academia, he worked as an RF System Design Engineer at Infineon Technologies (2014–2017). Education: Ph.D., Computer Science and Engineering, University of North Texas, 2015 M.Sc., Electrical Engineering, China University of Geosciences, Wuhan, China, 2008 B.Sc., Electrical Engineering, China University of Geosciences, Wuhan, China, 2005 Research Interests: Beamforming Phased Array Antenna Integrated Passive Device Design Electromagnetic Cloaking & Metamaterials His recent work focuses on frequency-agile RF analog co-processors , 3D-printed reconfigurable components , and deep learning-enhanced monopulse receivers . Over 60 publications span topics like tunable Nolen matrices, VO₂-based smart materials, and IoT spectrum coexistence frameworks. He leads a research group actively recruiting students in RF systems, high-frequency circuits, and electromagnetic theory. Lab/Team: Active research group focused on RF circuit innovation and applied electromagnetic systems.

Xavier Aragones Cerveraمشاهده پروفایل

دانشیار

• Integrated Circuits Design
• RF Systems
• Substrate Noise Analysis
• +۷ مورد دیگر

Xavier Aragones Cervera is an Associate Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Department of Electronic Engineering (Departament d'Enginyeria Electrònica) within the School of Telecommunications Engineering of Barcelona (Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona). His research focuses on high-performance integrated circuits and systems design, particularly addressing substrate noise, RF circuit design, and aging effects in CMOS technologies. He leads the HIPICS (High Performance Integrated Circuits and Systems Design Group) and contributes to the EFRICS (Efficient and Robust Integrated Circuits and Systems) research group. Education: M.S. in Telecommunication Engineering from UPC (1993), Ph.D. in Electronic Engineering from UPC (1997). His work spans over 130 publications, including peer-reviewed articles, conference presentations, and patents. Key research areas include substrate noise analysis, RFIC design, mixed-signal systems, and reliability engineering. He has advised students such as Marc Manel Molina and Juan Felipe Osorio. Collaborations include projects funded by national and European programs, focusing on microelectronics, IoT, and next-generation semiconductor technologies. Publications highlight experimental studies on substrate noise in VCOs/PLLs, aging compensation in amplifiers, and low-power IoT designs. He has contributed to major initiatives like the Cherenkov Telescope Array and RISC-V processor development in advanced FDSOI technology. His work emphasizes bridging theoretical models with practical circuit implementations, addressing emerging challenges in nanoscale CMOS and BEYOND-CMOS technologies.

Jihoon Ryooمشاهده پروفایل

دانشیار

• Wireless Networking
• Mobile Computing
• Internet of Things
• +۷ مورد دیگر

Jihoon Ryoo is an Associate Professor in the Department of Computer Science at SUNY Korea, where he has been employed since 2017. He directs the AI2S Lab and co-founded the startup IDCITI. He holds a Ph.D. from Stony Brook University (2017) and M.S./B.S. degrees from Korea University. Research Interests: Dr. Ryoo's work focuses on practical implementations in wireless networking and mobile systems, including backscatter communication, IoT connectivity, saliency-based video streaming, and GNSS-independent localization. His projects span uGPS (metro localization), SALI360 (360° video optimization), and autonomous anti-drone systems, often leveraging deep learning and RF analytics. Awards & Grants: Incheon City Mayor Award (Entrepreneur, 2024 & S/W Hackathon, 2020) Prime Minister Awards (ICT Colloquium & Applied Data Competition, 2020) IITP Excellence Research Award (2019) Grants: National XR-Lab initiatives (MSIT), Incheon-RISE program (2025–2030), NRF streaming platform research, and multiple Incheon Techno Park projects. Teaching & Service: Courses include Computer Networks, Computer Vision, Algorithms, and Wireless Networks. Service includes TPC roles (MobiSys, ICCCN), Director of SUNY Korea's ICT CCP Program (2018–2020), and XR-Lab Director (2021–2023).

• Embedded Sensors
• Sensor Networks
• Distributed Systems
• +۳ مورد دیگر

Bruno Rodrigues is an Assistant Professor of Computer Science (Embedded Sensing Systems) at the University of St. Gallen (HSG). His research focuses on embedded sensors, sensor networks, distributed systems, and network security, with additional expertise in software-defined networks and distributed ledgers. He holds a PhD from the University of Zurich (2020), a Master's from the Polytechnic School of the University of São Paulo (2016), and a Bachelor's from the University of Santa Catarina, Brazil (2013). Prof. Rodrigues' professional career includes roles as a Senior Researcher (2020–2024) and Junior Researcher (2016–2020) at the University of Zurich, where he contributed to projects like the EU-funded CONCORDIA H2020 and collaborations with Swiss innovation agencies (KTI/Innosuisse). His work spans DDoS mitigation, blockchain applications in voting systems, and energy-efficient cloud networks. Notable projects include the 'Passive Wireless Intelligence Tracking System (PasWITS)' and 'Energy-Efficiency to Clouds (E2C)' with Ericsson Research. His research portfolio includes over 50 publications on topics such as secure IoT frameworks (SHIFT, WeTrace), blockchain-based voting systems (ProvotuMN, Æternum), and cybersecurity tools like SecGrid for traffic analysis. He has pioneered solutions for privacy-preserving mobile tracking (LaFlector), real-time medical device inventory systems (PMD-Track), and decentralized financial inclusion tools (AfriBit). Prof. Rodrigues' work bridges theoretical computer science with practical applications, emphasizing sustainability, security, and innovation in distributed systems. He has led interdisciplinary projects at the intersection of blockchain technology, sensor networks, and ethical AI, with a focus on real-world implementation challenges.