Find Academic Supervisors

• Surface Science
• Positron Spectroscopy
• Radiation Detection
• +5 more

Dr. Varghese Anto Chirayath is a Research Assistant Professor in the Department of Physics at the University of Texas at Arlington (UTA). He leads research in surface and materials science using positron annihilation spectroscopy, radiation detection, and quantum sensor development. His work includes building advanced positron beam systems and designing detectors for high-energy, medical, and nuclear physics applications. Education: PhD in Physics, Homi Bhabha National Institute (2013) M.S. in Physics, Mahatma Gandhi University (2005) B.S. in Physics, Mahatma Gandhi University (2002) Research Interests: Dr. Chirayath focuses on positron-based surface analysis (e.g., defect characterization, electronic structure probing), quantum sensors, and detector innovation for radiation measurement. His recent work includes RF carpets for ion manipulation, cryogenic photodetectors, and machine learning-enhanced spectroscopy. Article Trends (2023–2025): Recent publications emphasize positron-annihilation-driven surface studies, FLASH radiotherapy platforms, and quantum pixel detector (Q-Pix) development. Themes include precision radiation detection, 2D material analysis, and AI-driven spectroscopic optimization. Grants & Awards: No awards explicitly listed, but his research reflects sustained institutional support for positron beam and detector projects. Labs/Teams: Leads UTA’s positron beam and quantum sensor research groups, collaborating on multi-disciplinary projects in physics and engineering.

Ming LiView profile

Associate Professor

• Networking
• Mobile Systems
• Cybersecurity
• +5 more

Ming Li is an Associate Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington. Her research focuses on networking, mobile systems (e.g., VR/XR), and cybersecurity, with an emphasis on applied AI, sensing, and computing. She holds a PhD from Mississippi State University and has held prior faculty positions at the University of Nevada Reno. Her work has been funded by NSF, DoT, and NIH, and she has received prestigious awards including NSF CRII and CAREER grants, as well as the N2Women Rising Star in Networking and Communications honor (2023). Education: PhD in Electrical and Computer Engineering, Mississippi State University, 2014 M.E. in Electrical Engineering, Beijing University of Posts and Telecommunications, 2010 B.E. in Electrical Engineering, Sun Yat-sen University, 2007 Research Interests: Dr. Li’s work spans IoT security, mobile computing, privacy-preserving computing, and human-centric systems. Her recent projects include developing VR-based authentication methods, detecting GPS trackers via EMR, and creating tools for cyclist safety using acoustic sensing. She has published over 35 papers in top venues like ACM CCS, INFOCOM, and IEEE journals. Recent Publications Trends: Her recent work emphasizes hardware security (e.g., EMR-based attacks), VR/XR system improvements, and smart city applications. Key areas include user authentication via novel sensing modalities, adversarial attack detection, and privacy-preserving techniques in IoT and crowdsourcing systems. Awards & Recognition: NSF CAREER Award (2020) N2Women Rising Star (2023) 40 Under 40 by Arlington City (2023) Best Paper Awards at IEEE Globecom’15 and DASC’17 Advising & Grants: Dr. Li has advised numerous graduate students, many of whom have gone on to academic and industry positions. Her grants include an NSF-funded project on privacy-aware VR QoE assessment and a DoT grant for cyclist safety. She also serves on editorial boards (e.g., IEEE Transactions on Vehicular Technology) and TPC roles for conferences like INFOCOM, NDSS, and CCS. Labs & Teams: Her research group, MobiSec Lab, focuses on mobile and network security, with active projects in wearable computing, edge AI, and smart infrastructure. Collaborations include work with the National Institute of Standards and Technology (NIST) on privacy metrics and with transportation agencies on vulnerable road user safety.

Ting-Yen ShihView profile

Associate Professor

• Antenna Design
• RF Circuits
• Electromagnetics
• +2 more

Dr. Ting-Yen Shih is Associate Professor in the Electrical and Computer Engineering Department at University of Idaho's College of Engineering. His research specializes in RF/microwave systems with focus areas in: Electrically-small antennas Ultra-wideband array design Machine learning for RF systems Non-reciprocal microwave devices High-power microwave applications He teaches courses including Electromagnetic Theory, Antennas and RF Circuits for 5G, and Advanced Topics in Electromagnetics. Research utilizes simulation tools including Altair FEKO and Keysight ADS for antenna optimization and microwave circuit design.

Vibhutesh Kumar SinghView profile

Lecturer

• Signal Processing
• Wireless Communication
• Embedded Systems
• +3 more

Dr. Vibhutesh Kumar Singh is an Assistant Lecturer in Electronic Engineering at South East Technological University (SETU) since January 2024. Previously, he worked as a Product Development Engineer at Intel Corporation and held academic positions during his PhD studies at University College Dublin (UCD). He holds a BTech from Vellore Institute of Technology (2014), an MTech from IIIT-Delhi (2016), and a PhD in Electrical and Electronic Engineering from UCD (2021). His research focuses on signal processing, wireless communication, embedded systems, and applied machine learning in resource-constrained environments. He has developed methodologies for channel estimation in FBMC-OQAM and OTFS systems, IoT-based monitoring solutions, and neural network deployment on low-RAM devices. Education: PhD in Electrical and Electronic Engineering, University College Dublin (2016–2021) MTech in Electronics and Communications Engineering, IIIT-Delhi (2014–2016) BTech in Electronics and Communication Engineering, Vellore Institute of Technology (2010–2014) Research Interests: Dr. Singh specializes in optimizing communication systems through advanced signal processing techniques. His work includes developing machine learning frameworks for embedded systems, designing efficient channel estimation algorithms, and creating IoT solutions for healthcare and infrastructure monitoring. He is particularly interested in TinyML applications for low-power, edge computing devices. Awards: Best Paper Award (Runner-Up), 2022 IEEE ComSoc Student Travel Grant, 2020 Intel MPE Division Recognition Awards (2023) Teaching & Professional Activities: Dr. Singh currently teaches courses on control systems, programming, and robotics at SETU. He has organized IEEE conferences and serves on the IEEE Professional Body. His work aligns with UN SDGs for sustainable innovation and education. Labs & Teams: He contributes to research teams focused on wireless communication testbeds and embedded system development at SETU and UCD.

• Machine Learning
• MPPT Algorithms
• Harmonic Detection
• +5 more

Assoc. Prof. Marko Dimitrijević is affiliated with the University of Niš, Faculty of Electronic Engineering, where he holds the position of Associate Professor since 2021. He leads the Laboratory for Electronic Design Automation (LEDA) and the Laboratory for Electronics. His academic journey includes a PhD in 2012 on 'Electronic System for Polyphase Loads Analysis Based on FPGA' and postgraduate studies from 2005. He has conducted research exchanges at Technische Universität Ilmenau (Germany), IHP Microelectronics (Germany), the University of Southampton (UK), and Universidad Politécnica de Madrid (Spain). Prof. Dimitrijević teaches courses such as 'Introduction to Electronics' and 'System on a Chip' across undergraduate, master’s, and doctoral programs. His research focuses on MPPT algorithms, harmonic detection, FPGA applications, and smart grid technologies. He has supervised two master’s theses and contributed to numerous academic publications. His work bridges theoretical advancements with practical applications in renewable energy systems and power electronics. Education: Bachelor's in Electronics and Telecommunications (2002, Faculty of Electronics, Niš) Master's in Electronics (2005, Faculty of Electronics, Niš) PhD in Electronics (2012, Faculty of Electronics, Niš) Professional Roles: Assistant Professor (2016–2021) Associate Professor (since 2021) Head of LEDA and Electronics Lab Research Highlights: Development of FPGA-based systems for polyphase load analysis MPPT controller optimization for standalone PV systems Nonlinear load characterization using machine learning Labs & Teams: LEDA focuses on electronic design automation and power electronics, while the Electronics Lab supports undergraduate teaching and experimental research.

Zhangyu GuanView profile

Associate Professor

• Wireless Networking
• Network Security
• Communication Systems
• +4 more

Zhangyu Guan is an Associate Professor in the Department of Computer Science & Engineering at the University of Minnesota - Twin Cities, with a courtesy appointment at the Department of Electrical Engineering, University at Buffalo - SUNY. Previously, he served as an Associate Professor at SUNY Buffalo (2015-2025) and an Associate Research Scientist at Northeastern University (2015-2018). His research focuses on next-generation wireless networking , including zero-touch computing , space-air-ground integrated networking , and AI-enabled ultra-broadband networks . He leads the Wireless Intelligent Networking and Security (WINGS) Lab , which develops UAV platforms, digital twin technologies, and shared wireless testbeds. Ph.D., Communication and Information Systems, Shandong University, China (2010) His research explores Wireless Sensing, Communications and Networking for Advanced Air Mobility , Experimentation and Softwarization for Future Wireless Networks , and Printable Circuits for RFID . Recent work emphasizes digital twin frameworks to bridge simulation-to-real gaps and democratizing access to heterogeneous wireless testbeds through grassroots initiatives like UnionLabs (NSF CIRC grant, 2025). Key scientific contributions include domain adaptation for UAV networks, resilient communication protocols , and spectrum sharing frameworks for UAV swarms. He has received the Senior Teacher of the Year Award (2025) and led numerous NSF-funded projects. His lab has produced graduates now at institutions like Google, AMD, Synopsys, and academic positions including Eastern New Mexico University. He serves on organizing committees for IEEE INFOCOM and editorial boards for IEEE Transactions on Wireless Communications and Computer Networks (Elsevier).

Pavlos LazaridisView profile

Professor

• Wireless Communication Systems
• Antenna Design
• 5G/6G Networks
• +5 more

Pavlos Lazaridis is a Professor in Electronic and Electrical Engineering at the University of Huddersfield's School of Computing and Engineering. His research focuses on antenna arrays , beamforming , 5G/6G wireless systems , and machine learning applications in telecommunications. He leads EU Horizon 2020 projects ITN-MOTOR5G and RISE-RECOMBINE. Research expertise includes RF engineering , digital broadcasting , and ultra high definition TV Active publication areas: electromagnetic compatibility, partial discharges, and evolutionary algorithms With over 2,697 citations (Google Scholar h-index 26), his work intersects telecommunications and artificial intelligence . Current projects address B5G/6G ecosystem challenges , including non-terrestrial network security and 3D beamforming optimization .

Leo LiuView profile

Senior Lecturer

• Business Analytics
• Information Systems
• Digital Transformation
• +2 more

Dr. Leo Liu is Senior Lecturer in Business Analytics at Manchester Metropolitan University, where he previously served as Programme Leader for the MSc Business Analytics. His research focuses on Information Systems, Business Analytics, and Digital Transformation. Research spans Business Analytics education frameworks, healthcare system interoperability, and technology applications in dentistry and wireless networks. Recent work includes meta-analyses of clinical treatments and antenna design optimization. Liu holds doctoral research experience from the University of Reading and industry background as an IT consultant. Current investigations examine digital transformation pathways for businesses using interdisciplinary approaches.

Sanjib SurView profile

Associate Professor

• Wireless systems
• Millimeter-wave networks
• Internet of Things
• +2 more

Sanjib Sur is an Associate Professor in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research focuses on wireless systems for healthcare, mobility sensing, and IoT connectivity. Research interests span: Millimeter-wave communication networks Contactless health monitoring technologies Intelligent transportation systems Edge computing for sensor networks His recent publications demonstrate strong focus on non-contact sensing for healthcare (sleep analysis, stroke rehabilitation) and smart infrastructure (traffic monitoring, outdoor networking). Technical approaches consistently integrate millimeter-wave systems with deep learning for robust environmental operation.

Ke XiaView profile

Academic

• Glycobiology
• Protein Chemistry
• Mass Spectrometry
• +7 more

Ke Xia is a Research Assistant Professor and Director of the Proteomics Core at Rensselaer Polytechnic Institute (RPI), where he has held roles in the Linhardt Research Labs and the Center for Biotechnology and Interdisciplinary Studies since 2001. His research focuses on protein and glycan chemistry, with a strong emphasis on mass spectrometry-based proteomics, glycomics, and the development of bioengineered glycans for medical applications. Xia has over 50 peer-reviewed publications, including work in Nature journals and PNAS , and has contributed to advancements in antiviral agents, stem cell differentiation, and protein aggregation studies. Education : Ph.D. in Biochemistry, Rensselaer Polytechnic Institute, USA (2009) M.Sc. in Chemistry, Peking University, China (2004) B.Eng. in Materials Science & Engineering, Donghua University, China (2001) Research Interests : Xia’s work spans glycobiology (e.g., heparin synthesis and viral-glycan interactions), protein stability (e.g., SDS-resistant protein aggregates), and biomedical applications (e.g., heparin analogs for anticoagulation and antiviral therapies). He employs advanced techniques like CRISPR screening, bioinformatics, and machine learning to study glycan roles in disease and development. Awards : W. H. Bauer Doctoral Prize in Chemistry (2009) Winner of Rensselaer’s Change the World Challenge (2009 & 2010) DANKONG Scholarship (2003) Advising & Labs : Xia has advised over 40 students and researchers, emphasizing interdisciplinary training in glycomics and proteomics. His lab focuses on translating glycan research into clinical tools, such as novel antiviral agents and engineered heparins. Collaborations include projects on stem cell differentiation, cardiovascular protein aggregates, and biomaterials for tissue engineering.

Georgios MakrisView profile

Professor

• Hardware Security and Trustworthiness
• Machine Learning Applications in Integrated Circuit Design
• Analog and RF Circuit Testing
• +3 more

Professor Georgios Makris is a faculty member in the Department of Electrical and Computer Engineering at the Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas. He leads the Trusted and RELiable Architectures (TRELA) Research Laboratory, the Safety, Security and Healthcare Thrust of the Texas Analog Center of Excellence (TxACE), and the UT Dallas site of the NSF CHEST I/UCRC. Previously, he was a faculty member at Yale University for over a decade. Education : Dipl. Eng. (1995) from University of Patras, M.S. (1998) and Ph.D. (2001) from UC San Diego. Research Interests His research spans hardware security, machine learning applications in IC design, analog/RF circuit testing, counterfeit IC detection, and statistical analysis. Current work includes statistical side-channel fingerprinting, hardware Trojans in wireless cryptographic ICs, on-die learning architectures, and security in synthetic biology. Recent article trends focus on hardware security (8/15), machine learning applications (7/15), and analog/RF test/reliability (6/15), with subfields including side-channel analysis, statistical modeling, and emerging technologies. Scientific Awards Elevated to IEEE Fellow (2025) Sheffield Distinguished Teaching Award (2006) Best Paper Awards: DATE’13, VTS’15, DCAS’22 Best Hardware Demonstration Awards: HOST’16, HOST’18 Erik Jonsson School Faculty Research Award (2020) His research has been supported by NSF, ARO, AFRL, DARPA, and industry partners. He has advised Ph.D. students whose work received the David Daniel Thesis Award (2021).

Mark GolkowskiView profile

Professor

• Electromagnetic waves in ionosphere/magnetosphere
• Plasma discharges for medical applications
• HAARP facility experiments
• +3 more

Mark Golkowski serves as Chair and Professor of Electrical Engineering at the University of Colorado Denver's College of Engineering, Design, and Computing. His research focuses on electromagnetics, plasma physics, and ionospheric/magnetospheric interactions. He leads experiments at the HAARP facility in Alaska, investigating ionospheric probing and magnetosphere dynamics, as well as developing plasma-based medical sterilization technologies and thermo-acoustic imaging systems. His academic accolades include the 2019 CU Denver Excellence in Research Award, 2016 Outstanding Teaching Award, and NSF CAREER Award (2013). Golkowski has pioneered active experiments with VLF/ELF waves, plasma discharges for biomedical applications, and novel imaging techniques combining thermal and acoustic modalities. Key Research Areas: Ionospheric remote sensing Medical plasma applications Whistler mode wave dynamics HAARP experimental campaigns Awards: 2019 Excellence in Research Award 2013 NSF CAREER Award 2008 IAGA Young Scientist Award His work bridges theoretical plasma physics with applied engineering solutions, including medical disinfection systems and space weather research. Current projects include solar eclipse ionospheric studies and magnetospheric wave propagation modeling.

• Cybersecurity
• Wireless Communications
• Health AI
• +6 more

Dr. Ying Wang serves as an Associate Professor in the Department of Systems and Enterprises at Stevens Institute of Technology's Charles V. Schaefer, Jr. School of Engineering and Science since August 2021. Her interdisciplinary background bridges wireless communications, health informatics, software engineering, and data mining with extensive industry experience. Her research spans cybersecurity , wireless communications , and health AI , focusing on AI-driven 5G/NextG platforms, quantum-enhanced UAV security, and telehealth systems. Key projects include quantum-optimized beamforming for UAV swarms, formal verification of 5G protocols, and edge-centered medical decision support systems leveraging IoMT. Recent publications (2024-2025) reveal a strong trend toward quantum-secure communications and hybrid AI-quantum frameworks for vulnerability detection, with 60% of articles integrating quantum techniques for cybersecurity applications. Her work consistently bridges theoretical advances with real-world validation through over-the-air testing and industry partnerships. Awards: Tom Ode Richardson Faculty Fellowship (2024) Dr. Wang actively mentors undergraduate senior design teams, with multiple groups winning Best Project awards for UAV security systems and 5G digital twins. She leads the MACC Lab, which develops deployable solutions for defense and healthcare applications, including real-time anomaly detection frameworks and edge-based radiology diagnosis systems.

• Radio Spectrum Management
• Mobile Computing
• Cyber-Physical Systems and IoT
• +4 more

Min Song is Professor, Department Chair of Electrical and Computer Engineering, and Founding Director of the Center for Innovative Computing and Networked Systems (iCNS) at Stevens Institute of Technology's Charles V. Schaefer, Jr. School of Engineering and Science. He holds a PhD in Computer Science and Engineering from the University of Toledo (2001). With over 35 years of cross-sector experience—including leadership roles at Michigan Tech and as an NSF Program Director—his research spans radio spectrum management, mobile computing, cyber-physical systems/IoT, wireless networks, machine learning, and network security, supported by $5M+ grants from NSF, Air Force, and NSA. Research Focus: Dr. Song pioneers adaptive wireless systems, emphasizing security and efficiency. His work integrates ML with spectrum sharing, UAV-assisted communications, and privacy-preserving techniques for IoT. Recent projects explore RIS-aided NOMA networks, federated learning privacy, and AI-driven RF slicing, advancing 5G/6G infrastructure resilience. Awards & Leadership: Recognized as IEEE Fellow (2018) and NSF CAREER awardee (2007), he received the Air Force Research Fellowship (2024) and Stevens Excellence Award (2021). He chaired flagship conferences (IEEE INFOCOM 2023, GLOBECOM) and serves on editorial boards for IEEE Transactions on Wireless Communications and Computer Networks . Grants & Labs: Active grants include NSF-funded cybersecurity for AIoT (CNS-2431547) and Air Force STTR projects on FPGA-assisted image processing. He directs iCNS, fostering innovation in networked systems through industry-academia partnerships.

Jason SawyerView profile

Associate Professor

• Animal Husbandry
• Meat Science
• Food Technology
• +4 more

Jason Sawyer is an Associate Professor in the Department of Animal Sciences at Auburn University's College of Agriculture. His research focuses on meat science, packaging innovations, livestock nutrition, and agricultural digital engagement. He investigates technologies like vacuum packaging for meat quality preservation, evaluates alternative feed ingredients for livestock, and explores social media strategies to bridge agricultural communication gaps with non-agricultural audiences. His work spans food industry analytics, poultry and pork processing, and extension education through podcasting and Instagram outreach. Research Interests: Meat quality and packaging solutions for freshness retention Plant-based supplements in animal diets Impact of technology (RF waves, machine learning) on food safety and quality Social media's role in agricultural education and youth engagement Recent articles highlight innovations in meat processing, challenges in poultry myopathies, and the efficacy of digital tools like Instagram and podcasts. His studies often integrate empirical data with industry applications, aiming to enhance both production efficiency and consumer trust.