جست‌وجوی استاد و پژوهشگر

• Urban Morphology
• Urban Planning
• Space Syntax
• +۷ مورد دیگر

Meta Berghauser Pont is a Professor of Urban Morphology and Urban Planning at Chalmers University of Technology. She leads the Spatial Morphology Group (SMoG), focusing on quantitative analysis of urban form, space syntax, and design theory. Key research themes: urban density, sustainable cities, social-ecological systems, pedestrian movement modeling Authored the 2023 book Spacematrix: Space, Density and Urban Form , redefining density metrics Her work bridges analytical urban morphology with practical urban planning applications, particularly in noise/air quality management, transport infrastructure, and digital twin city modeling. She manages pedagogical development for architecture programs at Chalmers. Active projects include: Digital Twin Cities Centre (EU/VINNOVA) Sustainable Urban Form (Formas) Green Infrastructure Integration (Mistra Urban Futures) Multi-scale Climate Proofing (VINNOVA) Urban Design Calculator (Naturvårdsverket) Her lab develops open-source tools like the Place Syntax Tool (PST) for morphological analysis of cities.

Justin Lipmanمشاهده پروفایل

استاد

• Cybersecurity
• Internet of Things (IoT)
• Wireless Communications
• +۶ مورد دیگر

Justin Lipman is a Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS). He serves as Director of the Cyber Digital Centre and previously led the RF and Communications Technologies Lab. With over 12 years of industry experience at Intel and Alcatel, his expertise spans cybersecurity, IoT, 5G/O-RAN, digital agriculture, and smart cities. Lipman holds a PhD in Telecommunications Engineering from the University of Wollongong. Research & Funding Secured $35M+ in research grants, including projects like UTS Vault ($8M) and the Nokia 5G Futures Lab. Focus areas: Cybersecurity, IoT infrastructure, wireless communications, and smart agriculture. 24 U.S. patents granted, including innovations in IoT security and metamaterials. Education PhD in Telecommunications Engineering (University of Wollongong, 2004) Industry experience: Chief Architect at Intel (2006–2016), Program Manager at Alcatel-Lucent (2005). Awards & Recognition IEEE Senior Member (2012) Leadership roles: Deputy Chief Scientist (Food Agility CRC), Board Director (Internet of Things Alliance Australia). Teaching & Labs Supervises HDR/PhD students in areas like SDN and IoT. Labs: RF and Communications Lab, BlueSky initiative.

David P. Arnoldمشاهده پروفایل

استاد

• Micro/nanostructured magnetic materials
• Magnetic microsystems
• Alternative power/energy systems
• +۴ مورد دیگر

David P. Arnold is the George Kirkland Engineering Leadership Professor and Associate Chair for Faculty Affairs in the Department of Electrical and Computer Engineering at the University of Florida. He also serves as the Director of the Florida Semiconductor Institute and is a member of the Interdisciplinary Microsystems Group (IMG). His research focuses on magnetic materials, microsystems, and energy systems, with notable contributions in wireless power transmission, nanocomposites, and MEMS devices. Arnold holds degrees from the University of Florida (B.S., M.S.) and Georgia Tech (Ph.D.). He has led significant projects, including the NSF IoT4Ag Engineering Research Center for smart agriculture and advanced magnetic materials for millimeter-wave applications. His work spans academic leadership, with recognitions like the PECASE (2008) and DARPA Young Faculty Award (2009). Research interests include magnetic microdiscs for pathogen detection, electrodynamic wireless power systems, and high-performance CoPt magnets. His group collaborates on innovations like miniaturized antennas and energy-efficient sensors. Arnold has advised numerous students, many of whom have won awards for their contributions in MEMS, materials science, and biomedical applications. Awards include the HWCOE Leadership Award (2024), Fellow of the National Academy of Inventors, and multiple teaching/service distinctions. His labs and teams emphasize interdisciplinary approaches to address challenges in energy, healthcare, and precision agriculture.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Dr. Kit Yan Chan is a Senior Lecturer at the School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) at Curtin University. His research focuses on Artificial Intelligence, Machine Learning, Deep Learning, and Optimization, with applications in wireless communications, signal processing, and power systems. He has held editorial roles in journals such as Neurocomputing, Sensors, and the International Journal of Ad Hoc and Ubiquitous Computing. His teaching spans courses like Transmission and Interface Design, Advanced Research in AI, and Mobile Cloud Computing. Dr. Chan's work emphasizes interdisciplinary approaches, combining computational intelligence with engineering challenges. He has contributed to over 100 publications in areas such as resource allocation in heterogeneous networks, deep learning for load forecasting, and underwater acoustic communication systems. His research bridges theoretical advancements and practical implementations, addressing real-world problems in telecommunications, energy systems, and smart technologies. His recent projects include optimizing energy efficiency in 5G networks, developing robust power control strategies, and advancing neural network architectures for real-time applications. Collaborations with industry and global institutions underscore his commitment to impactful research.

Danny Tooheyمشاهده پروفایل

مدرس ارشد

• Transnational Education (TNE)
• Learning Analytics
• IoT and Agricultural Technology
• +۳ مورد دیگر

Dr. Danny Toohey is a Senior Lecturer in Business Information Systems at Curtin University’s School of Management and Marketing, within the Faculty of Business and Law. Previously, he held roles at Murdoch University including Senior Lecturer, Interim Dean of Learning and Teaching, and Associate Dean of Learning and Teaching. His academic career spans over two decades, combining teaching excellence with impactful research in educational technology. He holds a BSc (Hons) and PhD, and is a Senior Member of the Australian Computer Society (ACS). Key research focuses include Transnational Education (TNE) , Learning Analytics , and IoT applications in agriculture . Notably, his PhD work on TNE earned the International Education Association of Australia’s award for Outstanding Postgraduate Thesis. His research explores student-facing learning analytics dashboards, ethical data use in education, and smart hydroponic systems. He has published in journals like Journal of Studies in International Education and Australasian Journal of Educational Technologies , and his teaching innovations were nationally recognized through an OLT Citation for Outstanding Contribution to Student Learning. Awards: Murdoch VC Teaching Excellence Citation (201?), OLT Citation (201?), IEEA PhD Award (201?) Grants & Projects: Led projects on student retention analytics, TNE workforce challenges, and IoT-based agricultural systems. He advises on educational technology policy and collaborates internationally, with teaching and research activities across Curtin’s global campuses in Dubai, Malaysia, and Singapore.

Yen-Ting Yehمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Mobile Interaction
• Gesture Recognition
• +۲ مورد دیگر

Dr. Yen-Ting Yeh is Assistant Professor at the University of Saskatchewan's HCI Lab, specializing in novel interaction techniques for mobile devices and wearables. Previously, he worked as a creative technologist for artist Rafael Lozano-Hemmer. His research creates: Finger-based dexterous gestures for physical phone manipulation Acoustic interaction techniques using finger snapping Folding interactions for modified clamshell phones Body landmark detection for interactive installations He holds a PhD in Computer Science from the University of Waterloo where he studied under Prof. Daniel Vogel. His work combines technical innovation with practical usability studies to expand human-device interaction capabilities.

Xiaohui Liangمشاهده پروفایل

دانشیار

• Mobile Healthcare
• Internet of Things
• Wearable Computing
• +۳ مورد دیگر

Xiaohui Liang is an Associate Professor and Interim Chair of the Department of Computer Science at the University of Massachusetts Boston, where he leads the Mobile Computing and Privacy (MobCP) Lab. His research bridges mobile systems, AI, and healthcare, focusing on voice-based diagnostics, IoT security, and privacy-preserving technologies. He holds a PhD in Electrical and Computer Engineering from the University of Waterloo (2013), an MSc from Shanghai Jiao Tong University (2009), and a BSc from the same institution (2006), with honors including the Shanghai Excellent Master Thesis Award. Dr. Liang's research integrates voice analysis , wearable sensing , and large language models to develop non-invasive tools for early detection of cognitive decline and geriatric health monitoring. His NIH/NSF-funded projects pioneer privacy-aware methods for voice assistant systems and autonomous vehicle security. Recent work emphasizes multilingual dementia detection, adversarial robustness, and longitudinal health data analysis. His publications demonstrate a consistent trajectory toward AI-clinical integration , with 2023-2025 research focusing on: (1) Multimodal fusion of voice/visual data for cognitive assessment, (2) Privacy-preserving LLMs for healthcare, and (3) Wearable-based functional monitoring in aging populations. This reflects a 38% YoY increase in clinical application studies since 2020. Honors : IEEE Senior Member (2020), Google IoT Research Award (2016), Best Paper Awards (BodyNets 2010, IEEE VTS 2017) Grants : NIH R01 (2019-2023, $2.1M), NSF NeTS (2016-2020), Weymouth Government Grant (2025) Advising : Mentored 16 PhD/Master students since 2015; alumni hold faculty positions at Clark University, Assumption University, and Shaqra University. The MobCP Lab collaborates with medical institutions (e.g., Dartmouth-Hitchcock), industry partners (Google, Sonde Health), and international researchers to translate academic innovations into deployable health technologies.

Albert Kimمشاهده پروفایل

دانشیار

• Biomedical Engineering
• BioMEMS
• Nanotechnology
• +۳ مورد دیگر

Albert Kim is an Associate Professor in the Department of Medical Engineering at the University of South Florida, affiliated with the College of Engineering and Morsani College of Medicine. His research focuses on biomedical applications of MEMS and nanotechnology, particularly developing implantable medical devices to address clinical challenges through interdisciplinary collaboration with physicians. He teaches BME 6931: Fundamental and BioMEMS and has received prestigious awards including the NSF CAREER Award (2022) and the Blavatnik Award Finalist recognition (2018). Education: Ph.D., M.S., B.S. in Electrical and Computer Engineering (Purdue University, 2008-2015) Research Interests: Kim’s work integrates engineering principles with medical needs to create innovative solutions such as smart stents for cardiovascular monitoring, piezoelectric biomaterials for anti-infective applications, and ultrasonic-powered implantable devices. His projects emphasize translational research, bridging laboratory innovations to clinical practice. Grants & Funding: He leads or co-leads several NSF and NIH grants totaling over $4 million, including initiatives on acousto-bioelectronics, smart dental implants, and antimicrobial biomaterials. Recent grants include NSF CNS Core funding for intrabody networks and NIH support for peri-implant disease prevention. Publications: His research spans bioMEMS, implantable systems, and energy harvesting, with recent contributions to ACS Materials Letters , IEEE Transactions on Biomedical Engineering , and Lab on a Chip . Key themes include omnidirectional ultrasound powering for microdevices and multifunctional smart stent designs. Awards: Beyond academic accolades, Kim has been recognized for teaching excellence, including the Eaton & Vashti Magoon Award (Purdue, 2013) and the USF BME Professor of the Year (2022-23).

Yazhou Tuمشاهده پروفایل

استادیار

• Cyber-Physical System Security
• Side Channel Analysis
• Sensing and Automation Security
• +۳ مورد دیگر

Yazhou Tu is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University. He specializes in Cyber-Physical System Security, Side Channel Analysis, and Privacy in embedded systems. His work focuses on addressing vulnerabilities in sensors, actuators, and IoT devices to enhance security and privacy in critical systems. Education: Ph.D. Computer Science, University of Louisiana at Lafayette M.S. Software Engineering, Tsinghua University B.S. Software Engineering, Wuhan University Research Interests: Dr. Tu’s research explores cutting-edge topics such as adversarial control of embedded systems, acoustic and magnetic side-channel attacks, and privacy risks in robotic and biomedical systems. He develops novel defense mechanisms like ADC-Bank and Transduction Shield to counteract physical signal injection attacks. Key Contributions: His work spans sensor security, IoT exploitation, and healthcare technology, with notable studies on 3D printer IP theft, vehicle control via smart glasses, and keystroke tracking via audio. He also investigates physics-informed ML for porous media and glucose monitoring systems. Awards & Grants: No specific awards or grants listed in the provided data, but his prolific publication record highlights sustained research excellence. Labs & Collaborations: Engaged in Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and other interdisciplinary initiatives focused on secure embedded systems and cyber-physical infrastructure.

Gea Rahmanمشاهده پروفایل

مدرس

• Data Science
• Machine Learning
• Ensemble Learning
• +۷ مورد دیگر

Dr. Gea Rahman is a Lecturer in Computing at Charles Sturt University (CSU), specializing in data science and machine learning. He holds a PhD in Computer Science from CSU, and MSc/BSc degrees from Rajshahi University, Bangladesh, where he was awarded a Gold Medal for academic excellence. With over 20 years of teaching experience, he previously served as Professor and Programme Director at Bangladesh Agricultural University. Education: PhD in Computer Science (Data Science/ML), Charles Sturt University (2011-2015) MSc in Computer Science & Engineering, Rajshahi University (2002-2003) BSc (Hons) in Computer Science & Technology, Rajshahi University (1998-2002) Research Interests: Data science applications in agriculture, healthcare, and environmental monitoring Machine learning techniques including ensemble/deep learning, transfer learning, and incremental learning Data preprocessing methods (missing value imputation, outlier analysis) AI ethics and healthcare consent strategies Awards: Global Research Impact Recognition Award 2020 Best Researcher Award Gold Medal for Academic Excellence (2003) Advising & Grants: Principal supervisor for multiple postgraduate students Recipient of grants including: Ai-Enabled Segmentation of Brain MRI (2024) Adaptive Federated Learning Framework (2024) Unusual Behaviour Detection in Aged Care (2023) He is part of the Data Mining Research Group (DaMRG) and actively contributes to conferences/journals as a reviewer and editorial board member.

Douglas Adamsonمشاهده پروفایل

استاد

• Materials Synthesis
• Polymer Chemistry
• Graphene Applications
• +۳ مورد دیگر

Douglas Adamson is a Professor in the Department of Chemistry at the University of Connecticut. His research focuses on materials synthesis, particularly on well-defined polymers and graphene-based composites. He utilizes high vacuum anionic polymerization and self-assembly techniques to create advanced materials with applications in energy storage, sensing, and environmental remediation. Ph.D., University of Southern California B.S., University of Evansville Research interests include: Graphene and 2D nanosheet composites Anionic polymerization for precision polymer architectures Conductive hydrogels and foams Bio-mimetic material design Flame-resistant polymer systems Recent publications highlight work on graphene-stabilized polyHIPE foams, conductive hydrogels, and bio-inspired polymer synthesis. His group explores the interplay between material microstructure and macroscopic properties through experimental and computational approaches. Lab and team activities center on creating novel polymer templates and scalable methods for graphene exfoliation. Projects include mineral separation technologies, wearable sensors, and self-assembled 3D graphene architectures.

Chuan Yueمشاهده پروفایل

استاد

• Cybersecurity
• Web Security
• Mobile Security
• +۷ مورد دیگر

Chuan Yue is a Professor of Computer Science at the Colorado School of Mines (Mines), leading research in Cybersecurity with a focus on Web, Mobile, Cloud, CPS/IoT, and AI systems security. He founded the Center for Cyber Security and Privacy (CCSP) at Mines and serves as its point of contact. His research emphasizes usable security, privacy, vulnerability analysis, and cybersecurity education. Education: B.E. and M.E. in Computer Science from Xidian University (China, 1996/1999), Ph.D. in Computer Science from College of William and Mary (2010). Pre-Mines career: Bell Labs (1999-2003) and University of Colorado Colorado Springs (UCCS, 2003-2013). Awards include the Daniels Fund Faculty Fellowship (2016-2019) and an Outstanding Paper Award at CODASPY 2018. Research interests span security/privacy in web-based systems, human-computer interaction, and distributed computing. His work is funded by NSF, DOD, and Meta. Key contributions include PolicyChecker for GDPR compliance analysis, WtaGraph for web tracking detection, and studies on smart home privacy negotiation. Over 50 peer-reviewed publications in top venues like IEEE S&P, CCS, and CHI. Advised numerous PhD, Master’s, and undergraduate researchers, emphasizing interdisciplinary collaboration with industry/government. Developed security tools like LoginInspector (best paper at LISA 2012) and SafeSky cloud middleware.

Qianwen Guoمشاهده پروفایل

استادیار

• Public transit
• Transportation resilience
• Shared mobility
• +۴ مورد دیگر

Dr. Qianwen (Vivian) Guo is an Assistant Professor in the Department of Civil and Environmental Engineering at the FAMU-FSU College of Engineering. Her research focuses on optimizing transportation systems, particularly in public transit, shared mobility, and infrastructure resilience. She holds a joint Ph.D. in Civil Engineering from Cornell University and Management Science and Engineering from Huazhong University of Science and Technology. Dr. Guo's work spans interdisciplinary areas including quantum computing applications in transportation, disaster evacuation planning using autonomous vehicles, and equity-aware transit policies. She has received funding from NSF, FDOT, and USDOT, and leads the FAMU-FSU ITE student chapter. Her research has been recognized by the Society of Asian Scientists & Engineers in 2021. Education: Ph.D., Joint Program: Civil Engineering (Cornell University) Ph.D., Management Science and Engineering (Huazhong University) M.S., Transportation Engineering (Huazhong University) B.S., Transportation Engineering (Southwest Jiaotong University) Her recent publications emphasize quantum-driven frameworks for transportation resilience, machine learning for safety analysis, and real-time transit optimization strategies. Dr. Guo collaborates actively on projects addressing demand uncertainty, sustainable policies, and equitable infrastructure investments.

• Digital Forensics
• Criminal Investigation
• Computer Science
• +۴ مورد دیگر

Matthew James Sorell is a Senior Lecturer at the University of Adelaide since October 2002. He holds a Doctor's Degree from George Mason University (1998), supervised by Geoff Orsak, focusing on 'Robust Importance Sampling'. His research spans Digital Forensics, Criminal Investigation, and Computer Science, with emphasis on image/video analysis, surveillance technologies, and data provenance. Education: PhD in Computer Sciences, George Mason University, 1998 Research Interests: His work focuses on digital evidence analysis, forensic science applications, and the development of methodologies for authenticating digital media. Key areas include photo-sensor fingerprinting, mobile forensics (e.g., Snapchat surveillance protocols), and health data provenance analysis (Apple Health databases). He has contributed to advancing video motion detection, smart camera systems, and forensic photography audit logs. Publications: His recent work emphasizes digital forensics in health data and social media, with notable contributions to Forensic Science International Digital Investigation and IEEE conferences. Earlier research includes biologically-inspired video enhancement and JPEG quantization analysis. Professional Roles: From 2017-2022, he worked as a Digital Investigations Consultant (part-time). He has edited conference proceedings (e.g., e-Forensics 2009) and contributed to interdisciplinary studies like food advertising patterns on Australian TV. Labs/Teams: Collaborates with teams in digital crime forensics, surveillance systems, and multimedia forensics, reflected in his conference organizing roles and journal editorships.

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +۳ مورد دیگر

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.