جست‌وجوی استاد و پژوهشگر

• Distributed Computing
• Applied Economics
• Policy and Administration Law
• +۲ مورد دیگر

Naranker Dulay is a Professor in the Department of Computing at Imperial College London, part of the Faculty of Engineering. He holds affiliations with the Centre for Cryptocurrency Research and Engineering, Centre for Smart Connected Futures, and the Distributed Software Engineering group. His research focuses on Distributed Computing, Applied Economics, Policy and Administration Law, Computer Software, and Information Systems. His work explores blockchain technologies, smart contracts, consensus algorithms, and distributed systems. Recent research includes optimizing post-trade processing using distributed ledgers and developing adaptive protocols for dispute resolution in smart contracts. He is also involved in cybersecurity and privacy-preserving technologies for data management. Key contributions include frameworks like Chainlog for logic-based smart contracts and FADE for self-destructing data. His articles span over a decade, emphasizing blockchain scalability, energy-efficient neural networks, and decentralized macro-programming in wireless sensor networks. Dr. Dulay collaborates across interdisciplinary domains, blending technical innovation with socio-technical challenges. His affiliations reflect a commitment to advancing smart connected futures through cutting-edge research.

Mahroo Eftekhariمشاهده پروفایل

استاد

• Building Energy Management Systems
• HVAC Systems Optimization
• Thermal Comfort Modeling
• +۵ مورد دیگر

Professor Mahroo Eftekhari is a Professor in Building Services Engineering at Loughborough University, leading the Low Energy Building Services Engineering MSc programme. Her research focuses on energy-efficient building systems, thermal comfort, HVAC optimization, and renewable integration. She has pioneered control systems for airports and buildings, including MPC-based strategies to reduce energy use while enhancing occupant well-being. Notable contributions include the development of BISPA (Building & Industrial Services Pipework Academy), a national center for BIM and pipework training. Education: Holds qualifications including CEng (Chartered Engineer), DPhil (Doctor of Philosophy), FCIBSE (Fellow of Chartered Institution of Building Services Engineers), and SFHEA (Senior Fellow of the Higher Education Academy). Her academic career is marked by collaborations with Tata Steel, Mitsubishi R&D, and Vexo, yielding applied research in sustainable building technologies. Research Interests: Indoor Air Quality, Thermal Comfort Modeling, Zero Energy Buildings, Digital Twins, and Advanced Control Systems. She has developed innovative solutions like AI-driven thermal management for Building Energy Management Systems (BEMS) and interfaces to synchronize airport operations with energy systems. Awards & Grants: Secured funding from diverse bodies for projects such as adaptive thermal comfort models, BISPA infrastructure, and energy-efficient HVAC strategies. Her work emphasizes practical applications, including reducing CO₂ emissions via airport terminal optimization and improving renewable energy use in buildings. Lab & Teams: Leads the Building Energy Research Group, managing projects in closed-loop heating systems, IEQ monitoring, and hydronic system efficiency. The Civil Engineering labs house interactive BIM rigs launched with institutional and industry support.

Nidhi Rastogiمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Data Science
• +۷ مورد دیگر

Nidhi Rastogi is an Assistant Professor at the Department of Software Engineering within the Golisano College of Computing and Information Sciences (GCCIS) at Rochester Institute of Technology (RIT). She leads the AI4Sec Research Lab, which focuses on data-driven AI solutions for cybersecurity, emphasizing interpretability and practical applications. Her research interests span Cyber Threat Intelligence, Artificial Intelligence, Graph Analytics, and Healthcare Analytics. Education: Ph.D. in Computer Science (2018), Rensselaer Polytechnic Institute M.S. in Computer Science (2008), University of Cincinnati Bachelor of Information Technology (2003), University of Delhi Research Interests: Transdisciplinary work in cybersecurity, AI, heterogeneous networks, and graph analytics. She develops systems for threat intelligence, explainable AI, and security monitoring. Notable projects include the CyNER library for cybersecurity NER, TINKER framework for open-source CTI, and personal health knowledge graphs. Awards & Mentoring: Students advised include Le Nguyen (1st place at UPSTAT23), Tanvirul Alam (IEEE SP Travel Grant), and Dipkamal Bhusal. Recent recognitions include program committee roles for ACM CCS'24 and ACSAC'24. Labs & Collaborations: The AI4Sec Lab collaborates with federal agencies, national labs, and enterprises. Current projects address autonomous vehicle security, healthcare analytics, and systemic cyberattack detection using graph-based methods.

• Cybersecurity
• Malware Detection
• Machine Learning
• +۷ مورد دیگر

Hayretdin Bahsi is an Assistant Professor at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University . His research focuses on cybersecurity, with expertise in malware detection, IoT security, and machine learning applications in defense mechanisms. He collaborates internationally on maritime cybersecurity, healthcare systems, and critical infrastructure protection. Research Interests include Android malware analysis, botnet detection, explainable AI in intrusion detection, and threat modeling for AI-driven systems. His work addresses challenges like concept drift in malware detection and privacy-preserving techniques for IoT networks. Publications span 66 scholarly works since 2009, emphasizing cybersecurity trends in AI, IoT, and healthcare. Recent contributions explore large language model (LLM) applications in vulnerability detection and cyber threat modeling for healthcare systems. Collaborations include projects on maritime cyber-insurance, cyber incident management in low-income countries, and datasets like MedBIoT for IoT botnet analysis. His work bridges theory and practice, addressing real-world cybersecurity challenges.

Edward Harcourtمشاهده پروفایل

استاد

• Ethics
• Moral Philosophy
• Practical Ethics
• +۳ مورد دیگر

Edward Harcourt is a Professor of Philosophy at the University of Oxford and a Fellow by Special Election at Keble College. He holds dual appointments in the Department of Philosophy and the Department of Psychiatry. His research focuses on ethics, moral psychology, and the intersections of philosophy with psychoanalysis and psychiatry. He earned his BPhil and DPhil from Oxford after an undergraduate degree in Philosophy and History at Trinity College, Cambridge. Key roles include leading the Wellcome ISSF project on mental health and the AHRC International Research Network on attachment theory and virtue. He directs the Oxford Summer Schools in Philosophy and Psychiatry and serves as Academic Director of the Royal Institute of Philosophy. His work bridges ethical theory, developmental psychology, and clinical practice, addressing topics like secure attachment, moral emotions, and the ethical dimensions of psychoanalysis. Publications span edited collections like Attachment and Character (2021) and articles in journals such as Journal of Medical Ethics and European Journal of Philosophy . His research emphasizes how human virtues and moral psychology intersect with psychological health and societal structures.

Greg Bamberمشاهده پروفایل

استاد

• Artificial Intelligence (AI)
• Data Futures
• Future of Work
• +۹ مورد دیگر

Greg Bamber is a Distinguished Professor in the Department of Management at Monash Business School, Monash University. He specializes in Employment Relations, Human Resource Management (HRM), and Industrial Relations with a focus on AI, the future of work, and organizational change. He holds adjunct roles at Newcastle University and Nottingham Business School, UK, and leads research initiatives in the Monash AI Institute and the International Consortium for Research in Employment & Work. Education: PhD in Human Resources & Industrial Relations (Heriot-Watt University), BSc (Manchester University). His career includes leadership roles at Durham University (UK), Griffith University (Australia), and Queens University (Australia). Research interests span AI's impact on HR, workplace dispute resolution, and global comparative labor studies. Notable works include the seminal textbook International & Comparative Employment Relations (7 editions) and studies on airline HR strategies. He has secured grants from the Australian Research Council (ARC), UK Economic & Social Research Council, and others. Awards include the British Academy of Management Cooper Medal and Lifetime Achievement Award from the Labor & Employment Relations Association. He advises international organizations, including the ILO, and serves on editorial boards of leading journals like Personnel Review and Journal of Management Studies .

Kaidi Yangمشاهده پروفایل

استادیار

• Intelligent Transportation Systems
• Traffic Flow Theory and Control
• Multimodal Transportation Systems
• +۵ مورد دیگر

Kaidi Yang is an Assistant Professor at the National University of Singapore (NUS) in the Department of Civil and Environmental Engineering, specializing in Intelligent Transportation Systems and related fields. He holds a PhD from ETH Zurich (2019), an M.Sc. in Control Science and Engineering from Tsinghua University (2014), and dual bachelor’s degrees in Automation and Mathematics from Tsinghua University (2011). His research focuses on advancing traffic control, connected/automated vehicles, shared mobility systems, and data privacy in transportation. He has contributed to developing algorithms for efficient traffic signal control, platooning coordination, and privacy-preserving data sharing in transportation networks. Education: Ph.D., Civil and Environmental Engineering (Transportation), ETH Zurich, 2019 M.Sc., Control Science and Engineering, Tsinghua University, 2014 B.Sc./B.Eng., Dual Degrees in Pure/Applied Mathematics and Automation, Tsinghua University, 2011 Yang has received prestigious awards including the Swiss National Science Foundation’s Postdoc Mobility Fellowship (2021–2022) and the IEEE ITS Conference Best Student Paper Award (2020). He serves as an Associate Editor for the IEEE Conference on Intelligent Transportation Systems (2024). His work bridges theoretical advancements in operations research, robotics, and machine learning with practical applications in urban mobility systems. Recent efforts emphasize integrating privacy-preserving techniques into traffic management and optimizing mixed-autonomy platoon control.

Kaiqun Fuمشاهده پروفایل

استادیار

• Spatial Data Mining
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Dr. Kaiqun Fu is an Assistant Professor in the McComish Department of Electrical Engineering and Computer Science at South Dakota State University (SDSU). He holds a Ph.D. and M.S. in Computer Science from Virginia Tech (2021 and 2016). His research focuses on spatial data mining, spatiotemporal event analysis, graph neural networks, and urban computing applications such as traffic impact prediction and social media-driven insights. He also explores physics-informed machine learning for power systems and interdisciplinary topics like 'deaths of despair' in rural areas. Education: Ph.D. in Computer Science, Virginia Tech, 2021 M.S. in Computer Science, Virginia Tech, 2016 Research Interests: His work emphasizes machine learning and deep learning applications in spatial-temporal domains, including: Graph neural networks for traffic incident prediction Social media analysis for urban challenges Physics-informed models for power grid stability Citation forecasting in scientific publications Grants & Projects: NSF CRII ($174,734): Spatiotemporal impacts of traffic events via graph neural networks (2024–2026) NSF EAGER ($300,000): Socio-economic impacts of emerging technologies (2024–2026) SDSU RSCA ($10,118): Graph transformer-based location learning (2023–2024) Professional Involvement: He chairs ACM SIGSPATIAL's SRC committee, serves on SDSU's Computer Science curriculum committees, and is an IEEE member. He co-edits Frontiers in Big Data and advises on interdisciplinary projects like climate-impacted grid security (NSF RII Track-2, $750,000). Labs/Teams: Collaborates with interdisciplinary groups focusing on smart cities, data-driven infrastructure resilience, and GeoAI applications.

Misa Faezipourمشاهده پروفایل

دانشیار

• System Dynamics Modeling
• Healthcare Systems Engineering
• Complex Systems Modeling
• +۳ مورد دیگر

Dr. Misa Faezipour is an Associate Professor in the Department of Engineering Technology at Middle Tennessee State University (MTSU) and director of the Systems Engineering Lab (SEL). She holds a Ph.D. and M.Sc. in Industrial Engineering and Engineering Management from the University of Texas at Arlington and a B.Sc. in Software Engineering from Islamic Azad University North Tehran Branch. Her research focuses on system dynamics modeling, healthcare systems engineering, complex systems, and sustainability optimization. Dr. Faezipour has advised numerous graduate students in M.S. and Ph.D. programs, focusing on topics such as healthcare disparities, AI robustness, and policy impact analysis. She teaches courses including Engineering Economy, Operations Management, and Engineering Management Systems. Her work spans collaborations with institutions like NASA, the Systems Engineering Research Center, and healthcare organizations. Her recent publications emphasize AI-driven healthcare solutions, system dynamics applications in policy analysis, and optimizing healthcare delivery through data-driven models. She actively contributes to professional organizations such as INCOSE, IEEE, and the System Dynamics Society. Dr. Faezipour’s lab, SEL, develops innovative tools for healthcare informatics, including diagnostic recommenders and policy simulation frameworks. Her research bridges systems engineering with healthcare challenges, addressing issues like racial health inequities and pandemic response strategies.

• Food Science
• Nutrition
• Functional Foods
• +۷ مورد دیگر

Alberta N.A. Aryee, PhD is an Associate Professor in the Department of Human Ecology (Food Science & Biotechnology) at Delaware State University (DSU). She holds a PhD from McGill University and completed postdoctoral research at Agriculture and Agri-Food Canada. Her research focuses on the impact of natural products and bioactive compounds on nutrition, health, and metabolic diseases, with particular emphasis on food processing effects, functional food development, and biofortification strategies. Education: Postdoctoral Research: Agriculture and Agri-Food Canada PhD: McGill University (Dissertation: Enzyme Immobilization and Biodiesel Production) MSc: McGill University (Thesis: Lipase Purification) BSc (Hons): Kwame Nkrumah University of Science and Technology Research Interests: Food science, functional ingredients, nutraceuticals, fermentation science, lipid technology, and sustainable food systems. She explores how processing impacts food matrices, bioavailability of nutrients, and the application of nanotechnology and machine learning in food analysis. Recent Research Trends: Her work spans encapsulation of bioactives, plant-based food innovation, and leveraging AI for nutrient prediction. Studies include optimizing hempseed processing, analyzing fermented cassava chemistry, and designing smart food packaging. Awards: 2020 DSU Faculty Excellence in Research 2018 Hornet Award (Early College High School) Mini Grant for hands-on food science education Advising & Grants: Mentors students in food chemistry and product development. Collaborates on grants focused on value-added food products from agricultural byproducts. Leads experiential learning programs integrating global food challenges. Labs & Teams: Based in DSU’s Baker Annex, her lab focuses on lipid science and functional food formulation. Collaborates with industry partners on sustainable food technologies and nanodelivery systems.

Rita Borgoمشاهده پروفایل

استاد

• Data Visualization
• Computer Science
• Human-Computer Interaction
• +۴ مورد دیگر

Dr Rita Borgo is a Professor in Data Visualization and Head of the Human Centred Computing Group at King's College London's Department of Informatics. She holds a leadership role within the Faculty of Natural, Mathematical & Engineering Sciences and is affiliated with the Centre for Urban Science and Progress (CUSP) London. Her research focuses on interdisciplinary visualization challenges, including human-computer interaction, AI trust calibration, and epidemiological modeling. Education details are not explicitly stated in the provided text. Her work spans over 58 publications, emphasizing visualization techniques for large datasets, trust in AI systems, and urban science applications. Key projects include RAMPVIS (visual analytics for pandemic response) and Trusted Autonomous Systems Hub (AI ethics and human-machine partnerships). Research interests include data visualization, human factors, generative AI, and policy simulation. Recent articles explore trust calibration in AI, time-series visualization, and ethical clinical decision support systems. She has led grants totaling £multi-million, including EPSRC-funded initiatives. Collaborations with organizations like ContactEngine Limited highlight her industry engagement. Labs/Teams: Leads the Human Centred Computing Group and contributes to CUSP's urban data initiatives. Supervised student work includes a notable BSc thesis by Munkhtulga Battogtokh. Current projects address visualization in nuclear policy, social media mental health correlations, and trustworthy autonomous systems.

Yingying Chenمشاهده پروفایل

استاد

• Smart Healthcare
• Internet of Things (IoT)
• Cyber Security
• +۷ مورد دیگر

Yingying (Jennifer) Chen is a Distinguished Professor and Department Chair in the Department of Electrical and Computer Engineering at Rutgers University, affiliated with the Wireless Information Network Laboratory (WINLAB) and the DAISY Lab. She holds a PhD in Computer Science from Rutgers University (2007). Her research focuses on Smart Healthcare, IoT, Cyber Security, Machine Learning, and AR/VR Security, with over 300 publications and multiple patents. Key roles include Associate Director of WINLAB, Fellow of ACM, IEEE, and AAIA, and recipient of the NSF CAREER Award (2010), Henry Morton Teaching Award (2017), and ACM Distinguished Scientist distinction. Awards also include the 2024 ACM Fellow and NAI Fellow (2022). Her work emphasizes interdisciplinary applications, such as AR/VR privacy attacks, adversarial machine learning defenses, and edge computing. Notable grants include NSF projects on AI on edge devices, NextG-enabled manufacturing, and healthcare system design. She advises Ph.D. students and collaborates with industry on testbeds like the Community-based Edge Sensing Testbed (NSF CCRI). Current research explores AI-driven sensing, privacy in immersive technologies, and robust multi-model analytics. Publications span top venues like ACM MobiCom, IEEE INFOCOM, and IEEE S&P. Labs include DAISY Lab (data analysis & security) and collaborations with WINLAB for wireless innovation. She serves on editorial boards of IEEE/ACM Transactions and organizes conferences like ACM MobiCom and IEEE ICDCS.

Lu Suمشاهده پروفایل

دانشیار

• Internet of Things
• Cyber-physical Systems
• Wireless and Mobile Sensing
• +۷ مورد دیگر

Lu Su is an Associate Professor at the School of Electrical and Computer Engineering , Purdue University , with prior appointments at SUNY Buffalo . His research spans Internet of Things , cyber-physical systems , mmWave sensing , and crowd-sourced data validation , focusing on quality-of-information aware distributed sensing and security in autonomous systems . Ph.D. in Computer Science (2013) and M.S. in Statistics (2012) from University of Illinois at Urbana-Champaign M.E. and B.E. from Harbin Institute of Technology Research Interests: IoT , cyber-physical systems , crowd sensing , security and privacy , and machine learning for sensor networks. His work addresses quality-aware information integration , adversarial attacks in autonomous vehicles , and privacy-preserving crowd-sourced systems . Recent publications focus on mmWave-based sensing (e.g., 3D pose reconstruction), federated learning (driver monitoring), and data poisoning attacks in crowd-sourced systems. His research also extends to traffic optimization and human activity recognition using wireless networks. Professional Roles: Workshop Chair (INFOCOM 2023, 2022) TPC Vice Chair (INFOCOM 2021) Program Committee Member for top conferences Editorial Board, ACM Transactions on Sensor Networks Teaching: Courses on Embedded Systems , Internet of Things , and Network Concepts at both undergraduate and graduate levels.

Muhammad Shujaat Mubarikمشاهده پروفایل

دانشیار

• Supply Chain Management
• Sustainability
• Operations Management
• +۶ مورد دیگر

Muhammad Shujaat Mubarik is an Associate Professor and Head of Research (Marketing & Operations Department) at Heriot-Watt University's Edinburgh Business School. His expertise spans logistics, supply chain management, operations management, and sustainability. He focuses on integrating digital technologies like blockchain and digital twins into supply chain frameworks, emphasizing intellectual capital's role in resilience and sustainability. His research methods include Structural Equation Modeling, Multi-Criteria Decision Making (AHP, ANP), and hybrid modeling. He holds leadership roles, including prior positions as Dean of the College of Business Management (IoBM) and Dean of the Faculty of Business Administration & Social Sciences (Mohammad Ali Jinnah University). He has secured grants from UKRI-EPSRC, NSERC, and HEC Pakistan, leading projects on supply chain resilience, logistics decarbonization, and SME internationalization strategies. His research collaborations span institutions like the University of Cambridge, Stanford University, and Copenhagen Business School. He teaches postgraduate courses in supply chain strategies, systems analysis, and green logistics. He actively engages in academic governance and industry partnerships, contributing to policy bridging. His work aligns with UN SDGs related to sustainable consumption, climate action, and responsible consumption. He has published over 100 papers, including 45 in high-impact journals, authored five books, and received the 2023 Best Researcher Award at the institute level. His funded projects address challenges like blockchain in oil and gas sectors and circular economy adoption barriers.

Yuntian Dengمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.