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.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۷۳۶-۷۵۰ از ۱٬۹۰۴ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Mrinal Sharma is a Lecturer in IT and Programme Coordinator for the BSc (Hons) Cyber Security and Digital Forensics at Middlesex University, Mauritius. He joined the university in September 2021 as a Graduate Teaching Assistant during his master's thesis completion and has since advanced to his current roles. His research interests focus on cybersecurity, Internet of Things (IoT), and blockchain technologies, driven by a passion to address modern security challenges through innovative solutions. Teaching: He currently teaches modules including CST 1330 Information Technology Applications CST 2120 Web Applications and Databases CST 2572 Secure Web Technologies CST 3510 Memory Analysis CST 4560 Network Security and Mechanisms Research: His work spans malware threat prediction using AI, blockchain-based healthcare systems, and IoT-driven home security solutions. Recent publications emphasize applications of CNN-SVM ensembles, smart home monitoring via Raspberry Pi, and NFC-enabled patient tracking systems. Student Supervision: He oversees undergraduate and postgraduate projects in cybersecurity and digital forensics, including modules CST 3590, CST 3990, and CST4599.
Elizabeth Stobertمشاهده پروفایل
استادیار
Elizabeth Stobert is an Assistant Professor and Human-Computer Interaction (HCI) Program Co-Director at the School of Computer Science, Carleton University. Her research focuses on usable security systems, integrating cognitive science principles to enhance security design in healthcare and education contexts. She holds a leadership role in advancing security education and authentication practices. Her work emphasizes improving user experiences in authentication systems, cybersecurity education, and addressing cultural and contextual factors in security practices. Key projects include studies on password management, digital legacy planning, and healthcare IT security gaps in emergency departments. She leads the SPIRL lab (website: https://spirl.scs.carleton.ca ), which explores human-centered security solutions. Dr. Stobert’s research has been disseminated through top-tier venues, analyzing user behavior in IoT authentication, cross-cultural security practices, and emergency department cybersecurity challenges. She advocates for interdisciplinary approaches to bridge gaps between technical security measures and human usability needs.
Srinjoy Dasمشاهده پروفایل
استادیار
Srinjoy Das is an Assistant Professor in Data Science at the School of Mathematical and Data Sciences, part of the Eberly College of Arts and Sciences at West Virginia University (WVU). He holds a Ph.D. and M.S. in Electrical Engineering and Statistics from the University of California, San Diego (2018), followed by postdoctoral research at UCSD’s Department of Mathematics until 2021. His research focuses on algorithms for predictive inference on time series, generative models, and efficient implementation of deep learning on edge computing devices. Education: Ph.D. in Electrical Engineering, UCSD (2018) M.S. in Statistics, UCSD (2018) Postdoctoral Researcher, UCSD Mathematics (2018–2021) Research Interests: Algorithms for real-time inference on generative neural networks Efficient implementation of deep learning on FPGAs and edge devices Time series analysis and nonparametric prediction Data-efficient learning in additive manufacturing and healthcare Recent Research Trends: His recent work emphasizes machine learning applications in manufacturing defect detection (e.g., melt pool characterization in 3D printing), geospatial analysis, and healthcare prediction systems. He also explores hybrid optimization strategies and bandwidth-efficient video processing techniques. Mentoring & Collaboration: Advised students on projects including FPGA-based neural network design (Xinyu Zhang), generative model evaluation (Ojash Neopane), and statistical inference for random fields (Ivy Zhang). Collaborates with industry partners like Qualcomm and Microsoft Research, focusing on edge computing and hardware optimization. Labs/Teams: His research group focuses on interdisciplinary projects at the intersection of data science, signal processing, and applied mathematics, with active collaborations in both academia and industry.
Jinyuan Sunمشاهده پروفایل
دانشیار
Jinyuan Sun is an Associate Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. She joined the faculty in 2010 as an Assistant Professor and has since specialized in network and system security, wireless communications, and mobile computing. Her work emphasizes securing critical infrastructure like smart grids and cyber-physical systems against adversarial attacks and ensuring privacy in data communications. Education: She holds a BSc in Computer Information Systems from Beijing Information Technology Institute (2003), an MASc in Computer Networks from Ryerson University, Canada (2005), and a PhD in Electrical and Computer Engineering from the University of Florida (2010). Before academia, she worked as a Network Test Developer at RuggedCom Inc., Canada (2005–2006). Research Interests : Her research focuses on security and privacy in wired/wireless networks, including adversarial machine learning for cyber-physical systems, secure authentication systems leveraging user behavior, and privacy-preserving mechanisms for smart grids. She explores vulnerabilities in energy markets, deep learning-based fraud detection, and resilient communication protocols. Publications: Her recent work spans topics like constrained adversarial machine learning, secure encryption schemes for smart grids, and dynamic privilege control in authentication systems. These contributions highlight her expertise in bridging theoretical cybersecurity with practical applications in critical infrastructure. Advising & Grants: She actively seeks self-motivated PhD students to advance research in network security and mobile computing. While specific grants are not listed here, her work reflects sustained engagement with funded research initiatives in cybersecurity and smart systems.
Reinhard Jung is a Full Professor of Business Engineering at the University of St. Gallen , where he also serves as Director of the IWI-HSG institute. Since 2021, he has held the role of Dean of the School of Management . Prior to this, he was a Full Professor at the University of Duisburg-Essen (2007-2009) and an Assistant Professor at the University of Bern (2002-2007). His research focuses on Digital Transformation , Blockchain Technology , Business Ecosystems , and Wearable Technology . Key areas include analyzing how technology impacts organizational processes, value creation in ecosystems, and behavioral change mechanisms driven by digital tools. His work bridges theoretical frameworks with practical applications in industries like healthcare, finance, and logistics. He advises students such as Tobias Mirsch and has contributed to over 100 publications since 2008, addressing topics ranging from social CRM to agile IT governance . His research emphasizes the intersection of technology, business strategy, and human behavior. Jung’s leadership roles include shaping the IWI-HSG as a hub for innovation in business engineering and driving strategic initiatives as Dean, focusing on interdisciplinary education and digital transformation strategies.
Bruno Rodriguesمشاهده پروفایل
استادیار
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.
David Kinahanمشاهده پروفایل
دانشیار
David Kinahan is an Associate Professor at Dublin City University's School of Mechanical and Manufacturing Engineering, specializing in microfluidics, biomedical diagnostics, and advanced manufacturing technologies. His research focuses on developing lab-on-a-disc platforms for medical diagnostics, laser-based surface engineering, and industrial applications. He completed a BEng in Aeronautical Engineering and a PhD in high-throughput droplet microfluidics at the University of Limerick. Prior to academia, he held engineering leadership roles at Stokes Bio Ltd and the Biomedical Diagnostics Institute. His research interests span microfluidic device innovation, surface texturing for antifouling/corrosion resistance, and additive manufacturing of smart materials. Recent projects include laser processing of NiTi alloys, centrifugal microfluidics for pathogen detection, and nanoscale surface engineering. Kinahan's publications demonstrate consistent focus on translating engineering solutions into practical applications, particularly in healthcare and industrial contexts. His collaborations with Fraunhofer Project Center highlight his commitment to industry-relevant research. He maintains an active Google Scholar profile documenting his contributions to microfluidics and advanced manufacturing research.
Sara Comaiمشاهده پروفایل
دانشیار
Sara Comai is an Associate Professor at the Politecnico di Milano , affiliated with the Department of Electronics, Information and Bioengineering . She coordinates the Assistive Technology Group (ATG) and leads the MEP (Maps for Easy Paths) project. Research Focus : Database systems, smart home technologies, indoor localization, and assistive solutions for elderly/dementia patients Recent Trends : 2025-2023 publications highlight Occupancy detection via Wi-Fi/infrared sensors Behavior classification for Alzheimer's patients Wearable/RFID-based health monitoring Human-robot collaboration in agriculture Adaptive machine learning for land use segmentation
Nam Buiمشاهده پروفایل
استادیار
Nam Bui is an Assistant Professor in the Department of Electrical Engineering at the University of Colorado Denver, where he founded and directs the Intelligent Networked Systems and Cybernetics Laboratory (InsCy Lab). His research focuses on developing intelligent cybernetic systems at the intersection of AI, machine learning, and embedded systems, with applications in mobile/wearable health monitoring and physiological sensing. His research interests span: Innovative sensing techniques for health monitoring Embedded intelligent systems leveraging AI/ML Wearable technology for physiological measurement Multidisciplinary approaches to medical cybernetics Analysis of recent publications reveals consistent themes in wearable health technology development, particularly focusing on non-invasive monitoring techniques for vital signs (blood pressure, respiration, glucose) using ear-worn and behind-ear devices. Key technical innovations include compressed sensing frameworks, closed-loop acoustic stimulation systems, and novel sensing modalities like polarization-based optical detection. Awards and Honors: Best Paper Awards at ACM MobiCom (2019, 2017) ACM SigMobile Research Highlights (2020) Communication of ACM Research Highlights (2021) Colorado OEDIT Award (2024) NASA MUREP Program Award (2024) NSF Sense Award (2024) DoD STTR Grant (2024) Teaching Innovation Award (2023) Dr. Bui actively advises graduate students including Anh-Huy Dinh and undergraduate researchers including Luis Carlos Gutierrez and Alejandro Cordova. His laboratory has secured multiple grants from NSF, NASA, DoD, and Colorado economic development programs. He directs the Intelligent Networked Systems and Cybernetics Laboratory (InsCy Lab), which focuses on practical intelligent systems for health monitoring. The lab emphasizes multidisciplinary collaboration and has developed technologies like in-ear blood pressure monitors and closed-loop sleep aid devices.
Mark Phillipsمشاهده پروفایل
مدرس ارشد
Mark Phillips serves as Design Director of Design Futures Product within Sheffield Hallam University's College of Social Sciences and Arts, bringing over 25 years of product design innovation experience across medical, consumer, and industrial sectors for clients including adidas, Gillette, and Unilever. He teaches BA (Hons) Product Design and MA Design courses while leading strategic research initiatives. His educational background includes an MDes from the Royal College of Art/Imperial College. Research focuses on human-planet centred design with projects spanning gamification for exercise, smart wearables, mobile hyperspectral imaging, sustainable composites, and health monitoring devices. Collaborations extend to clinicians, material scientists, and social researchers to develop future-facing product solutions. Publications demonstrate consistent innovation in health technology, sustainable design, and user experience, with recent work emphasizing medical applications and environmental impact reduction. Scientific recognition includes: Fellow of the RSA (Royal Society for the Encouragement of Arts, Manufactures and Commerce) Phillips has led undergraduate programs at Sheffield Hallam and served as external examiner for Nottingham Trent University's MA Product Design. Research funding from UKRI and Innovate UK supports applied projects addressing real-world challenges in healthcare and sustainability. He directs the Design Futures Product group, fostering interdisciplinary partnerships to advance product design innovation across multiple industry sectors.
Younghee Parkمشاهده پروفایل
دانشیار
- Network Security
- System Security
- Malware Detection
- +۷ مورد دیگر
Dr. Younghee Park is an Associate Professor in the Department of Computer Engineering at San José State University, part of the College of Engineering. She joined SJSU in 2013 as an Assistant Professor, advancing to her current rank in 2019. Her research focuses on network and system security, including malware detection, insider threats, botnets, smart grid security, and blockchain applications. She holds a Ph.D. in Computer Science from North Carolina State University (2010) and postdoctoral experience at the University of Illinois at Urbana-Champaign and Columbia University. Dr. Park has received prestigious awards such as the Kordestani Endowed Chair (2016-2017) and the Faculty Award for Excellence in Scholarship (2018). She founded the Silicon Valley Cybersecurity Institute (SVCSI), a non-profit dedicated to advancing cybersecurity. Her work integrates machine learning, blockchain, and SDN/NFV to address modern security challenges in IoT, mobile cloud computing, and critical infrastructure. Recent research emphasizes real-time intrusion detection systems, generative AI for malware analysis, and blockchain-based security mechanisms. She has led projects funded by the National Science Foundation (NSF) and industry partners, contributing to both academic publications and practical cybersecurity solutions.
Julio Giordano is a Professor of Dairy Cattle Biology and Management in the Department of Animal Science at Cornell University. He serves as Director of the Dairy Cattle Biology and Management Laboratory, Director of the Cornell Agricultural Systems Testbed (CAST) for the Farm of the Future, and Associate Director of the Cornell Institute for Digital Agriculture (CIDA). His research focuses on integrating technology, data analytics, and biological principles to enhance dairy cattle reproduction, health, and farm profitability. Key projects include developing automated reproductive management systems, precision technologies for health monitoring, and data-driven decision tools for dairy farms. Giordano holds a DVM from Universidad Católica de Córdoba (Argentina), an MS from the University of Tennessee, and a Ph.D. from the University of Wisconsin-Madison. His work emphasizes translating research into practical solutions, such as the CAST initiative advancing climate-smart agriculture through sensor networks and IoT frameworks. He teaches courses on reproductive physiology, herd management, and digital agriculture. His articles explore topics like automated estrus detection, genomic integration in reproductive strategies, and the economic impacts of precision technologies. Giordano collaborates with industry partners to bridge academic research and on-farm implementation, aiming to modernize dairy production systems through innovation.
Professor Liyong Tong is a Professor in the School of Aerospace, Mechanical and Mechatronic Engineering at the University of Sydney. He holds BSc and MEngSc degrees from Dalian University of Technology and a PhD from Beihang University. A Fellow of Engineers Australia (FIEAust) and Member of AIAA, his research focuses on advanced composite materials and computational optimization methods. Research Focus: Multiscale topology optimization of composite structures and metamaterials Additive manufacturing of functional composites and smart structures Machine learning applications in structural optimization Analysis and design of advanced composite materials and structures His recent publications demonstrate integration of machine learning with structural optimization, novel approaches for metamaterial design, and experimental validation of 3D-printed structures. Research trends show emphasis on computational efficiency in optimization algorithms and multifunctional material systems. Current Projects: Microcrack suppression in thermoplastic composites for cryogenic hydrogen storage (NSW Space Research Network) Mitigating micro-vibration in satellite devices using multiscale shear damping Development of novel algorithms for topology optimization of laminated composites
Luca Arditoمشاهده پروفایل
دانشیار
Luca Ardito is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino. His research focuses on software engineering methodologies, mobile computing, and gamification strategies in education and testing. His work integrates technical domains such as Android development, GUI testing automation, energy efficiency in software systems, and IoT security. Ardito is a core member of the SoftEng research group, contributing to projects like SIFIS-home for privacy-preserving smart home systems. Research Interests: Advanced GUI testing techniques for Android and web applications Application of gamification in software education and quality assurance Energy-aware software development and green computing practices Certification frameworks for IoT device firmware and cybersecurity His recent work emphasizes empirical studies on gamification in UML modeling education, Kotlin adoption in Android ecosystems, and innovative approaches to firmware certification. Ardito has pioneered tools like Umlegend for gamified UML learning and Bipmin for BPMN education. Grants & Collaborations: Leading multidisciplinary projects combining computer science with agriculture (e.g., UAV-based hazelnut tree characterization) Active in industry partnerships for mobile testing frameworks (e.g., TOGGLE library) Labs & Teams: Core contributor to Politecnico's SoftEng Research Group , collaborating on projects like SIFIS-home (FP7/ERC-funded).
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