Find Academic Supervisors

• Data mining and knowledge discovery
• Data engineering and data science
• Data quality
• +17 more

Prof. Ping Yu is a Professor at the University of Wollongong's School of Computing and Information Technology, where she has held leadership roles such as Director of the Centre for Digital Transformation (2013–2020). Her work focuses on digital health, health informatics, and data-driven solutions for aged care, with collaborations involving the World Health Organization (WHO), NSW Health, and over 11 aged care providers. She has pioneered projects like the WHO’s eSTEPS platform and AI-driven analytics to optimize healthcare resources. Her research integrates socio-technical perspectives to address challenges in technology adoption and healthcare system improvements. Her research interests span data engineering, data quality, ontology development, and generative AI applications in healthcare. Key areas include extracting insights from unstructured health records, improving clinical decision-making, and enhancing patient outcomes through mHealth and telemedicine innovations. She also explores the impact of green spaces on healthy aging and disparities in healthcare access across regions. Prof. Yu has secured over $4.5 million in research funding, including significant grants from the Australian Research Council. She has mentored 29 postgraduate students to completion, emphasizing interdisciplinary research and practical implementation. Her awards include the prestigious 2022 Telstra Brilliant Women in Digital Health Award and the 2008 Don Walker Award for contributions to health informatics. Her advising and grants narrative highlights her role as a mentor and her success in securing competitive funding. Her work bridges academia and industry, with projects like improving pressure injury risk management in aged care using EHRs and analyzing agitation in dementia through AI. She contributes to education policy, including co-designing academic leadership programs and enhancing clinical informatics curricula in the AI era. Prof. Yu leads multi-disciplinary teams at UOW and collaborates with global institutions, focusing on labs and initiatives like the Appendicectomy Surgical Pathway Ontology (ASPO) and the 6A framework for hypertension management via mHealth. Her research emphasizes real-world impact, from reducing hospital readmissions to optimizing surgical workflows and improving public health communication strategies during crises.

Lisa KervinView profile

Professor

• Early Childhood Education
• Digital Literacy
• Child Development
• +3 more

Professor Lisa Kervin is a leading academic in early childhood education at the University of Wollongong (UOW), serving as Director of Early Start Research and holding a Professorial appointment in the School of Education. Her research focuses on young children’s literate practices, play-based learning, and digital technology integration in education. She leads the ARC Centre of Excellence for the Digital Child and has secured significant funding, including a 2025 ARC Future Fellowship exploring intergenerational play. Kervin was honored as a Member of the Order of Australia (AM) in 2024 for contributions to early childhood digital literacy research. She has supervised over 35 research students, many now in academic and leadership roles, and currently oversees seven doctoral candidates. Her work bridges theory and practice through collaborations with educators and industry partners, emphasizing interdisciplinary approaches to child development and policy influence globally. Education: PhD in Language and Literacy from UOW (2001–2004). Professional roles include Principal Fellow of the Australian Literacy Educators’ Association and Director qualifications from the Australian Institute of Company Directors. Her research spans digital childhood ethics, play pedagogy, and literacy curriculum design, with outputs impacting government policies and international educational frameworks. Ongoing projects include the ‘DigIQ’ program promoting digital literacy and ‘Playgroups for All Ages’ fostering intergenerational engagement. Grants and collaborations involve partnerships across six universities and 33 global organizations. Her teaching innovations include the Early Childhood Elevate Mentoring Program to support educators’ academic progression. Kervin’s work addresses critical issues like screen time impacts, STEAM education, and culturally responsive pedagogies, positioning her as a key voice in 21st-century early childhood education.

M.Z. NaserView profile

Assistant Professor

• Machine Learning
• Structural Engineering
• Fire Engineering
• +5 more

Dr. M.Z. Naser is an Assistant Professor in the Glenn Department of Civil Engineering at Clemson University. His research focuses on causal and explainable machine learning methodologies applied to structural engineering, materials science, and fire safety. He holds a PhD from Michigan State University and an M.S. from the American University of Sharjah. Naser teaches courses such as Machine Learning for Civil Engineers and Structural Fire Engineering, emphasizing interdisciplinary innovation. His work bridges data-driven analysis with domain-specific knowledge to address challenges in resilient infrastructure design, including fire-resistant materials, structural retrofits, and AI-driven decision-making. Education: PhD, Michigan State University; M.S., American University of Sharjah Research Themes: Explainable AI, Fire Engineering, Structural Materials, Causal Inference Key Projects: Developing SPINEX framework, wildfire classification models, and cognitive infrastructure systems Recent publications analyze over 1000 fire tests to uncover spalling mechanisms, explore synthetic fire tests via GANs, and benchmark automated ML platforms. His work on causal diagrams for civil engineers and firefighter algorithms highlights contributions to both theory and practical applications. Naser also advocates for integrating AI into engineering education, emphasizing ethical and transparent model deployment.

• Social Physics
• Graph Convolutional Neural Networks
• Large Language Models (LLMs)
• +4 more

Dr. Alexander Mantzaris is an Associate Professor in the Department of Statistics & Data Science at the University of Central Florida, College of Sciences. His research bridges physics and sociology through Social Physics frameworks, focusing on statistical mechanics and thermodynamic analogies to model social phenomena. Current research explores criticality points in social systems Developing computational tools for NLP and big data Former work on Graph Convolutional Networks in social analysis Specializes in entropy-based modeling of polarization and segregation His publications emphasize interdisciplinary approaches combining network science, computational modeling, and sociological dynamics. Recent articles address thermodynamic formulations of political cycles, energy states in Schelling models, and memory-efficient data processing algorithms. Dr. Mantzaris teaches graduate courses in big data analytics and statistical learning theory. He maintains active research in computational social science with applications to political dynamics, media influence, and complex systems analysis.

Paul Van OorschotView profile

Professor

• Computer Security
• Authentication
• Internet Security
• +7 more

Paul Van Oorschot is a Professor at the School of Computer Science, Carleton University. He has held the Canada Research Chair in Authentication and Computer Security from 2002 to 2023. His expertise spans authentication, applied cryptography, and network security. He co-authored the seminal Handbook of Applied Cryptography and led the NSERC Internetworked Systems Security Network (2008–2013). His research focuses on enhancing security in systems, software, and web authentication, including methods to augment passwords with geolocation and device recognition. He holds a Ph.D. from the University of Waterloo and was awarded the J.W. Graham Medal (2000) and Fellowship in the Royal Society of Canada (2011). Education: Ph.D. in Computer Science from the University of Waterloo (1988) His research interests include authentication systems, public-key infrastructure, smartphone security, and usability challenges in security design. He has contributed to frameworks like OWL for password-based key exchange and SLV for server location verification. His work addresses both technical and human factors in securing modern computing environments. Key contributions include analysis of TLS interception, memory safety in programming languages, and evaluating IoT security best practices. He has published extensively on topics ranging from side-channel attacks to cryptographic protocol vulnerabilities. Awards: J.W. Graham Medal in Computing and Innovation (2000), Fellow of the Royal Society of Canada (2011) His academic leadership includes roles in shaping cybersecurity education and policy, emphasizing the need for rigorous scientific approaches in security research. His research group, the Carleton Computer Security Lab (CCSL), drives interdisciplinary projects in software security and system administration tools.

• Artificial Intelligence in Education
• Digital Transformation in Education
• Educational Technologies
• +3 more

Sabine Seufert is a Full Professor of Management of Educational Innovations at the University of St. Gallen (HSG), where she has held leadership roles including Director of the Institute of Educational Management and Educational Technologies (since 2021) and Director of the Institute of Business Education and Educational Management (2009–2020). She holds a PhD in Information Management (1996) and a Habilitation in Business Education (2006) from the University of St. Gallen, specializing in educational innovation and technology integration. Her research focuses on digital transformation in education, AI applications in learning environments, and competence development in vocational training. She has pioneered initiatives like the Swiss Centre for Innovations in Learning (scil) and contributed to frameworks for hybrid intelligence in education. Her work bridges academic research and practical implementation, emphasizing ethical AI use and teacher preparedness for technological change. Key affiliations include the European Foundation for Management Development (EFMD), the editorial board of the International Journal of Learning Technology , and advisory roles for journals like Empirical Research in Vocational Education and Training . Her recent publications explore AI literacy, social robots in classrooms, and the impact of generative AI on teaching and learning. Her career spans over 25 years, including guest professorships at the University of Southern Queensland and Stanford University, leadership in educational institutions, and policy advisory roles. She is actively involved in shaping future-ready education systems through digital innovation and human-AI collaboration strategies.

Yang ChengView profile

Associate Professor

• Supply Chain Management
• Manufacturing Strategy
• Manufacturing Network
• +5 more

Yang Cheng is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. He holds a PhD in Mechanical Engineering from the same institution (2011), focusing on manufacturing strategy and network dynamics. His research spans supply chain management, sustainability, and global operations, with a focus on integrating technology and environmental policies into manufacturing systems. He leads or participates in high-impact projects like MAASive (2024–2026) and the Sino-Danish Center Research Project (2011–present), addressing resilience in value networks and global operations innovation. Research Interests: Supply Chain Management & Integration Sustainability & Green Technologies Manufacturing Strategy & Networks Technology Policy & Digitalization Global Operations & Cross-Border Collaboration Recent Work Trends: Prof. Cheng's 2025 articles emphasize blockchain in sustainable supply chains, green technology investments under carbon policies, and digitalization's ethical implications. His 2024 research explores smart factories, EU battery regulations, and robotization in manufacturing. These studies blend quantitative models with case-based analysis to address real-world challenges. Awards: 2024 Emerald Literati Awards – Outstanding Reviewer Advising & Grants: As PI for multiple Global Operations Management PhD programs (2019–2025), he guides research on digital transformation and university-industry collaboration. His projects receive funding from Danish and international grants, focusing on innovation and resilience in manufacturing networks. Labs/Teams: Collaborates with the Center for Industrial Production at Aalborg University and engages in international partnerships through the Sino-Danish Center. Active editorial roles include Production Planning & Control and Journal of Manufacturing Technology Management .

Kirk R. PruhsView profile

Professor

• Algorithmic problems related to green computing
• Fair allocation
• Resource management
• +3 more

Professor Kirk R. Pruhs is a full Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds editorial roles at journals such as the Journal of Scheduling and ACM Transactions on Algorithms. His research focuses on algorithmic problems in green computing, scheduling, online optimization, and resource management. Pruhs has advised numerous PhD students and has a strong publication record in top venues like SODA, STOC, and FOCS. His work often addresses energy-efficient algorithms and computational resource management. Notable contributions include studies on stochastic scheduling, energy-efficient routing, and competitive analysis of online algorithms. Education: BS in Mathematics and Computer Science from Iowa State University (1984), PhD in Computer Science from University of Wisconsin-Madison (1989). Research Interests: Algorithmic challenges in green computing, fair allocation mechanisms, scheduling under uncertainty, and online optimization techniques. He explores how computational methods can improve energy efficiency and resource allocation in distributed systems. Recent articles focus on robust scheduling strategies, stochastic systems, and algorithmic approaches to network design and resource optimization. His work bridges theoretical computer science with practical applications in sustainable computing. Students: Includes Jonathan Beaver (2006), Mohamed Aly (2008), Christine Chung (2009), Daniel Cole (2013), Neal Barcelo (2015), Michael Nugent (2015), and Alireza Samadian Zakaria (2021). Labs/Teams: Engaged in algorithm design and analysis within the Department of Computer Science, contributing to initiatives in computational sustainability and high-performance computing.

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +4 more

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University’s Faculty of Science. His research focuses on applying software engineering principles to video game development, with particular emphasis on software testing, artificial intelligence for software engineering (AI4SE), deep reinforcement learning, and empirical software engineering. Education includes a PhD in Computer Science and Software Engineering from Concordia University (2022), supervised by Professors Yann-Gaël Guéhéneuc and Fabio Petrillo. Prior to his current role, he held postdoctoral positions at Université de Montréal and École de Technologie Supérieure in Montréal, Canada. Research interests span game engine architecture analysis, automated testing methodologies for games, and bridging gaps between academic theory and industry practices in software engineering. His work often involves empirical studies on software quality, framework impacts, and event-driven systems. Publications reflect a focus on game development challenges, including studies on API compatibility, subsystem coupling visualization, and AI-driven game balance assessment. He actively contributes to the understanding of software processes in the video game industry through surveys and dataset curation initiatives like PlayMyData.

Bryan A. BrownView profile

Professor

• Science Education
• Diversity and Identity
• Urban Education
• +3 more

Bryan A. Brown is the Kamalachari Professor of Science Education and Senior Associate Vice Provost at Stanford University’s Graduate School of Education. His work focuses on science education in urban contexts, emphasizing discourse, identity, and equity. He holds administrative roles including College Director of Freshman Sophomore College and oversees the Stanford Provostial Fellows Program. Education: BS in Biology (Hampton University, 1996), MA and PhD in Science Education (UC Santa Barbara, 1999–2002). Research Interests: Student identity, classroom discourse, urban STEM equity, college access, and culturally relevant pedagogy. Advisees: Supervises doctoral students including Kendra Sobomehin, Brandi Cannon, and Derric Heck. Dr. Brown’s recent work explores virtual reality (VR) applications for culturally relevant science education and the impact of language ideologies on cognition. He teaches courses like Curriculum and Instruction in Science and Science, Engineering and Technology Education Seminar . His research highlights how race, language, and culture shape learning opportunities, particularly for urban students. He advocates for technology-based solutions to address educational disparities and has contributed to projects like VR-based ocean acidification education and culturally responsive STEM curricula. Key Themes: Bridging cultural relevance and technology, dismantling language barriers in science, and advancing equity through pedagogical innovation.

Li LiuView profile

Professor

• archaeology of early China (Neolithic and Bronze Age)
• ritual practice in ancient China
• cultural interaction between China and the Old World
• +4 more

Li Liu is the Sir Robert Ho Tung Professor in the Department of East Asian Languages and Cultures at Stanford University. She joined the Stanford faculty in 2010, following 14 years at La Trobe University in Melbourne, Australia, where she taught archaeology and was elected a Fellow of the Academy of Humanities in Australia. Her research focuses on early China's archaeology, encompassing the Neolithic and Bronze Ages, ritual practices, cultural interactions with the Old World, domestication processes, state formation, and urban development. She holds a B.A. in Archaeology from Northwestern University (Xi'an), an M.A. in Anthropology from Temple University (Philadelphia), and a Ph.D. in Anthropology from Harvard University (1994). Dr. Liu's educational background includes degrees from prestigious institutions across multiple countries, reflecting her global academic engagement. Her work bridges archaeological methods with interdisciplinary approaches to understand societal complexity and environmental adaptation in ancient China. Notably, her contributions to understanding cultural exchanges between China and neighboring regions have been influential in East Asian Studies. Her research interests emphasize material culture analysis, settlement patterns, and the socio-political dynamics underlying early state formations. This includes investigations into ritual landscapes, agricultural practices, and urbanization processes in ancient China. Her studies often involve collaborative projects that integrate archaeological data with historical and anthropological perspectives. Dr. Liu has been recognized for her scholarly contributions, including her Fellowship in the Australian Academy of Humanities. Though her primary role is in archaeology, her Google Scholar publications reflect interdisciplinary collaborations in medical research, audio engineering, and environmental science, suggesting diverse academic engagements. In advising, she mentors students in archaeological and anthropological studies, though specific advisee names are not listed here. Her grants and funding history, while not detailed in the text, would likely support her archaeological fieldwork and interdisciplinary projects. She has contributed to the Stanford Center for East Asian Studies and affiliated programs, fostering cross-cultural research initiatives.

Casey ReasView profile

Professor

• Generative Art
• Digital Media
• Computer Graphics
• +4 more

Casey Reas is a Professor in the Department of Design Media Arts at the University of California, Los Angeles (UCLA), where he also co-directs UCLA Social Software. He holds a Master's in Media Arts and Sciences from MIT and a Bachelor's from the University of Cincinnati's College of Design. A pioneering figure in generative art and digital media, Reas co-founded the open-source programming language Processing, revolutionizing computational creativity for artists and designers. His work spans software installations, prints, and collaborative projects exhibited globally at institutions like the Centre Pompidou and the Whitney Museum. His research explores intersections of technology, art, and pedagogy, reflected in books such as Compressed Cinema and Making Pictures with Generative Adversarial Networks . Reas' practice emphasizes algorithmic processes and machine learning, exemplified in series like Untitled Film Stills and Compressed Cinema . He actively contributes to initiatives like UCLA’s Game Lab and the Conditional Studio, fostering interdisciplinary innovation. His work balances technical rigor with aesthetic exploration, bridging art, science, and technology.

Yu HuangView profile

Assistant Professor

• Software Engineering
• Human-Centered AI
• Human Factors in Programming
• +5 more

Yu Huang is an Assistant Professor of Computer Science at Vanderbilt University with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her research focuses on human-centered AI for software engineering, combining human cognition with machine intelligence to enhance software development processes. Educated at the University of Michigan (PhD, 2021), University of Virginia (MS, 2015), and Harbin Institute of Technology (BS, 2011), her work spans software engineering, human factors, AI, and medical imaging. Key projects include the MIND Lab, studying programmer expertise and cognitive processes, and the HumanAISE workshop on Human-Centered AI for Software Engineering. Huang has received significant recognition, including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards. Her research is supported by NSF, GitHub, and Vanderbilt initiatives. She advises numerous graduate and undergraduate students, emphasizing diversity and innovation in programming education.

Ed ChienView profile

Assistant Professor

• Computer Science
• Graphics
• Computational Engineering
• +3 more

Ed Chien is an Assistant Professor at Boston University's Department of Computer Science within the College of Arts & Sciences. He specializes in applying differential geometry and topology to graphics, computational engineering, and machine learning. Previously, he was a postdoctoral researcher at MIT's CSAIL and Bar-Ilan University. His work focuses on mathematically rigorous solutions to problems in geometric data processing and optimal transport. Education PhD in Mathematics, Rutgers University (2015) A.B. in Mathematics & Physics, Dartmouth College (2009) Research Highlights Dr. Chien's research includes fundamental studies on hexahedral mesh topology for Finite Element Modeling, optimal transport applications in machine learning, and singularity-free geometric algorithms. His work bridges theoretical mathematics with computational tools for engineering and graphics. Publications span top venues like NeurIPS, Eurographics, and SIGGRAPH, reflecting contributions to geometry processing and machine learning intersections. Program committee roles include Eurographics SGP (2019) and AAAI (2020). Awards & Recognition No specific awards listed, but notable service includes program committee memberships and peer-reviewed contributions to leading conferences. Grants & Advising Active in mentoring through academic positions but no explicit grant details provided. Research focuses on advancing geometric algorithms and optimal transport methodologies.

Margaret GroseView profile

Associate Professor

• Ecological Design
• Urban Ecology
• Sustainable Landscapes
• +4 more

Associate Professor Margaret Grose is an academic at the University of Melbourne's Melbourne School of Design, specialising in Landscape Architecture. She holds an Associate Professorship and teaches ecological design principles in the Masters of Landscape Architecture and Bachelor of Environments programs. Her work bridges design and ecological science, with a focus on urban ecosystems, water management, and cultural landscapes. Education: Grose began in Agricultural Science (soils/water processes), completed a PhD in ecophysiology of Australian plants, followed by postdoctoral research at Oxford University and the University of Cambridge’s Mathematical Biology group. She later trained in Landscape Architecture and practiced as an environmental scientist in urban design projects. Research interests include integrating ecological science into design, the role of historical ecological knowledge in contemporary design, and urban water systems. Her recent Universitas 21 Fellowship explores teaching ecology to built environment students globally. Publications span topics like urban forestry in China, dryland river parks, and impacts of artificial light on ecosystems. She has received the 2011 Faculty Teaching Award for Excellence in the Masters program. Supervision focuses on river design, urban waterways, ecological planting resilience, and design of public spaces in Mediterranean climates. She collaborates on interdisciplinary projects combining ecology, urban planning, and cultural heritage.