جست‌وجوی استاد و پژوهشگر

Han Huمشاهده پروفایل

استادیار

• Phase-change heat transfer
• Two-phase flow
• Acoustic sensing
• +۳ مورد دیگر

Dr. Han Hu serves as Assistant Professor in the Department of Mechanical Engineering at the University of Arkansas College of Engineering, holding the Twenty-First Century Professorship since 2025. He leads the NED3 research laboratory with active collaborations including Purdue University's Cooling Technologies Research Center and NASA Glenn Research Center. Education: Ph.D. in Mechanical Engineering, Drexel University (2016) B.S. in Theoretical and Applied Mechanics, University of Science and Technology of China (2011) His research integrates phase-change heat transfer with AI-driven methodologies, focusing on thermal management solutions for power electronics through multimodal sensing systems. Current projects include pumped two-phase cooling for microchannel heat sinks and machine learning applications for bubble dynamics analysis in pool/flow boiling scenarios, supported by NSF and NASA grants. Scientific Recognition: Twenty-First Century Professorship in Engineering (2025) University of Arkansas Outstanding Mentor (2022-2024) Multiple ASEE conference awards for student mentorship (2022-2024) Faculty Gold Medal and Mechanical Engineering Service Award (2023) Dr. Hu mentors seven Ph.D. students and numerous undergraduates, with his NED3 lab securing $2.5M in recent funding including NSF grants for immersion-cooled electric motors and NASA EPSCoR research on boiling heat transfer. His team collaborates with UA-PTC's Aerospace Center of Excellence and ZIN Technologies on practical thermal management applications. The NED3 laboratory operates advanced facilities for synchronized optical, acoustic, and thermal measurements, featuring high-speed thermal imaging systems and custom-built flow boiling test rigs validated through partnerships with power electronics industry leaders.

Carla P. Gomesمشاهده پروفایل

استاد

• Artificial Intelligence
• Constraint Reasoning
• Optimization
• +۳ مورد دیگر

Carla P. Gomes is a Professor of Computer Science at Cornell University with joint appointments in the Department of Computer Science and the Dyson School of Applied Economics and Management. She holds a PhD in computer science from the University of Edinburgh and an M.Sc. in applied mathematics from the University of Lisbon. Her research focuses on artificial intelligence, constraint reasoning, optimization, and computational sustainability. As Director of the Institute for Computational Sustainability (ICS) and co-director of the Cornell University AI for Science Institute, she leads efforts to integrate AI with sustainability challenges. Her research themes include the integration of constraint reasoning, machine learning, and operations research to solve large-scale problems. She pioneered the field of Computational Sustainability, addressing environmental, economic, and societal challenges through AI. Gomes directed two NSF Expeditions in Computing awards and established CompSustNet, a large-scale sustainability research network. Key awards include the 2021 ACM–AAAI Allen Newell Award, AAAI Feigenbaum Prize, and fellowships from AAAI, ACM, and AAAS. Her work spans over 200 publications, with contributions to AI, sustainability, and materials discovery. She advises numerous PhD students and oversees postdocs in AI, sustainability, and interdisciplinary projects. Gomes' lab focuses on AI for scientific discovery, including autonomous materials synthesis and crystal-structure phase mapping. She collaborates with institutions like JCAP and the Materials Project, advancing AI-driven solutions for energy and environmental challenges. Current projects include Schmidt AI in Science postdoc initiatives and AI-driven materials discovery platforms like DRNets and SARA.

Ugur Cetintemelمشاهده پروفایل

استاد

• Data Management Systems
• Database Systems
• Distributed Systems
• +۵ مورد دیگر

Ugur Cetintemel is the Khosrowshahi University Professor of Computer Science at Brown University, where he has been since completing his PhD at the University of Maryland in 2001. His research focuses on data management systems, database systems, distributed systems, and stream processing, with recent work integrating AI techniques into database systems. He teaches courses such as Database Management Systems and Data Science fundamentals. Notable contributions include the Aurora and Borealis stream processing engines, S-Store for transaction processing, and DBPal for natural language interfaces. His work emphasizes scalable, efficient systems for large-scale data challenges. Education: PhD in Computer Science, University of Maryland, 2001 MS in Computer Science, Bilkent University, 1996 BS in Computer Science, Bilkent University, 1994 Research Interests: Data management, stream processing, distributed systems, predictive analytics, and AI integration with databases. Key projects include optimizing database systems for modern hardware, developing real-time stream processing frameworks, and exploring interactive data exploration techniques. Grants & Advising: Extensive contributions to grants and collaborations, though specific grant details are not listed. Supervises graduate students in areas like database systems and machine learning integration. Part of the Brown Data Management Group. Labs/Teams: Leads research within the Brown Data Management Group, focusing on advancing database systems for big data and real-time analytics.

Dawn Elizabeth Cavanaghمشاهده پروفایل

پژوهشگر

• Intellectual Disability Healthcare
• Mental Health Policy
• Healthcare Access for Marginalized Groups
• +۳ مورد دیگر

Dr Dawn Elizabeth Cavanagh is a Researcher at Manchester Metropolitan University, affiliated with the Faculty of Health and Education. Her work focuses on healthcare equity for individuals with intellectual disabilities and autism, particularly addressing systemic issues like restrictive practices and long-term segregation. She holds a PhD from the University of South Wales, where her research explored annual health checks and self-management for people with learning disabilities. Dr Cavanagh’s research has included NIHR-funded studies on psychotropic medication decision-making and the impact of the pandemic on people with learning disabilities. She is currently evaluating the HOPE(S) Programme to End Long-Term Segregation, focusing on mothers of children detained in secure hospitals. Her advocacy extends to campaigning against institutional segregation through initiatives like Stolen Lives Wales and her role as a trustee of the Paul Ridd Foundation. Her research interests intersect personal advocacy, as she is autistic and the parent of an adult son with multiple disabilities whose experiences informed her work. She co-chaired the 2023 RRN conference and has been recognized with awards for her contributions to restraint reduction and disability advocacy. Education: PhD in Intellectual Disability Healthcare (University of South Wales) Dr Cavanagh’s articles emphasize ethical healthcare practices, policy reform, and co-produced solutions for marginalized groups. Her work bridges academic research with grassroots advocacy, aiming to dismantle systemic barriers in healthcare access and institutional care. Awards: Restraint Reduction Network’s 2024 Outstanding Contribution Award, Cardiff Parents’ Federation 2024 Trustee Award She collaborates with organizations like the Rightful Lives Team and leads Stolen Lives Wales, advocating for systemic change in healthcare provision for vulnerable populations.

Stephen Caveمشاهده پروفایل

استاد

• Philosophy of Technology
• Ethics of AI
• Robotics Ethics
• +۳ مورد دیگر

Professor Stephen Cave is the Academic Director of the Leverhulme Centre for the Future of Intelligence (CFI) and Co-Director of the Institute for Technology and Humanity at the University of Cambridge. With a PhD in Philosophy from Cambridge, he previously served as a policy advisor and diplomat in the British Foreign Office for nearly a decade before returning to academia. Education: PhD in Philosophy, University of Cambridge Current Roles: Academic Director (CFI), Co-Director (Institute for Technology and Humanity) Media Engagement: Regular contributor to Financial Times , Guardian , New York Times , and media appearances on BBC and NPR His research bridges philosophy and ethics of technology , with two primary strands: (1) the ethics of AI and robotics , focusing on responsible AI development and societal impact through works like AI Narratives and Feminist AI ; and (2) the ethics of life-extension and immortality , explored in Immortality and Should You Choose to Live Forever? . Recent publications analyze algorithmic fairness, gender representation in AI narratives, and digital death. The articles listed reflect his engagement with responsible AI frameworks , cultural portrayals of AI , and existential implications of life extension . His work often synthesizes historical, ethical, and cultural perspectives to address contemporary challenges in AI governance and mortality philosophy.

Sebastian Pfotenhauerمشاهده پروفایل

استاد

• Innovation Cultures
• Science, Technology, and Innovation Policy
• Regional Innovation Strategies
• +۳ مورد دیگر

Sebastian Pfotenhauer is a Carl von Linde Professor for Innovation Research at Technical University of Munich (TUM) and Deputy Head of the STS Department. He specializes in the societal dimensions of innovation, including governance of emerging technologies, regional innovation cultures, and responsible innovation practices. His work bridges academic research and policy, with leadership roles in major initiatives like the €50M Munich Cluster for the Future of Mobility (MCube) and the EU-funded SCALINGS project on co-creation in innovation. He holds a PhD in Physics from the University of Jena and postdoctoral training at MIT and Harvard. Research interests include innovation policy, science governance, and the interplay between technology and societal change. Notable projects include comparative studies of innovation cultures, governance frameworks for AI and neurotechnology, and global partnerships in science and innovation. He advises governments and international bodies like the OECD and the German Engineers’ Association (VDI). Publications span journals like Research Policy , Social Studies of Science , and Nature Biotechnology , addressing topics from regulatory sandboxes to neurotechnology ethics. Awards include the Leading Technology Policy Fellowship (MIT) and NSF grants for studying complex international partnerships.

Steven H. H. Dingمشاهده پروفایل

استادیار

• Cybersecurity
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.

• Inclusive Education
• Equity in Education
• School Improvement
• +۳ مورد دیگر

Mel Ainscow is a Professor in Education at the University of Glasgow and holds adjunct and emeritus roles at Queensland University of Technology and the University of Manchester. He is recognized globally for his work on inclusion and equity in education, particularly through systemic reforms and collaborative research with schools. His career includes roles as a head teacher, adviser, and researcher, emphasizing strategies to make schools effective for all students. Key projects include leading the Greater Manchester Challenge (a £50M initiative for school improvement) and Schools Challenge Cymru (a Welsh Government program focusing on disadvantaged students). He advises UNESCO and the Organization of American States on equity in education. His research focuses on systemic change, policy analysis, and inclusive practices, with over 90 publications including books like Struggles for Equity in Education and articles in journals like Journal of Educational Change and Prospects . Dr. Ainscow's awards include a CBE for services to education (2012). His work bridges theory and practice, advocating for equity through collaboration, ethical leadership, and evidence-based strategies. He has collaborated with international networks in Australia, Portugal, Spain, and Latin America, emphasizing global approaches to educational challenges.

B. Aditya Prakashمشاهده پروفایل

دانشیار

• Data Science
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Aditya Prakash is an Associate Professor and Associate Chair for Academic Affairs in the School of Computational Science and Engineering at Georgia Tech. He holds a PhD from Carnegie Mellon University (2012) and a B.Tech from IIT Bombay (2007). His research focuses on data science, machine learning, and AI applied to epidemiology, healthcare, security, and urban computing. His work has led to impactful tools used by organizations like CDC, ORNL, and Walmart. Notable awards include the NSF CAREER Award (2018) and IEEE's 'AI Ten to Watch' (2017). Education: PhD (Computer Science, CMU, 2012), B.Tech (IIT Bombay, 2007) Research Interests: Epidemic forecasting, network analysis, healthcare informatics, and large-scale data-driven solutions for societal challenges. He has authored over 80 papers and holds two patents. His lab develops methods for disease modeling, urban infrastructure analysis, and cybersecurity. Key projects include the NSF-funded BEHIVE initiative for pandemic prediction and collaborations with MIDAS network for infectious disease modeling. Awards: NSF CAREER, Facebook Faculty Award, IEEE AI Recognition, and multiple best-paper awards. His group advises students across PhD, MS, and undergraduate levels, with notable alumni in academia and industry. Labs & Affiliations: Core faculty at ML@GT (Machine Learning Center) and IDEaS (Institute for Data Engineering and Science). Active in organizing conferences like AAAI, KDD, and SIGMOD.

Tamás Budaváriمشاهده پروفایل

دانشیار

• Computational Statistics
• Bayesian Inference
• Astronomy
• +۶ مورد دیگر

Tamás Budavári is an Associate Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University (JHU), with joint appointments in Physics and Astronomy and a secondary appointment in Computer Science. He is affiliated with the Whiting School of Engineering and the Institute for Data-Intensive Engineering and Science (IDIES). His research focuses on computational and statistical methods for big data in astronomy and interdisciplinary applications such as urban blight analysis. Education: PhD in Astrophysics (2001), Eötvös Loránd University, Budapest Master’s in Theoretical Physics (1997), Eötvös Loránd University Research Interests: Budavári develops algorithms for handling large astronomical datasets, including Bayesian inference, streaming algorithms, and GPU-accelerated processing. His work includes SkyQuery (an online astronomy data tool), photometric redshift estimation, and cross-matching catalogs. He also applies computational methods to urban planning, such as optimizing strategies to address vacant housing in Baltimore City. Publications & Tools: Budavári’s recent work spans topics like deep learning for astronomical image restoration, combinatorial optimization for urban policy, and probabilistic catalog matching. His tools, such as CUDAHM and NWAY, enable scalable analysis of multi-epoch survey data and N-way catalog cross-identification. Awards & Grants: Recipient of the Gordon and Betty Moore Fellowship and SAMSI Research Fellowship Funded by NSF, STScI, NIH, and others Leadership & Outreach: He serves on the Steering Committee of the 21st Centuries Cities Initiative and is a founding editor of the Journal of Astronomy and Computing. His interdisciplinary work bridges astrophysics, data science, and urban systems.

• Global Education Policy
• Comparative Education
• Teacher Education
• +۳ مورد دیگر

Professor Keita Takayama is a prominent academic in education studies at the University of South Australia’s UniSA Education Futures. His work focuses on global education policy, comparative education, and teacher education methodology. He actively engages with transnational policy processes, decolonial research frameworks, and critical analyses of international assessments like PISA. As editor of the Asia-Pacific Journal of Teacher Education (APJTE), he emphasizes rethinking teacher subjectivity and pedagogical practices. His research critiques the politics of knowledge production and advocates for methodological innovations like 'Asia as Method.' Recent work addresses contradictions in education export policies, linguistic imperialism in scholarship, and the role of education in resisting authoritarianism. Education Background: Doctorate in Education (focus on comparative policy studies) Advanced training in decolonial methodologies and policy analysis Research Interests: Professor Takayama’s work bridges global and local educational contexts. Key themes include: Policy mobilities & transnational education governance Reimagining comparative education through 'negative' comparative frameworks Ethics of academic publishing and knowledge dissemination Teacher education’s role in shaping democratic societies Labs/Teams: Leads the APJTE editorial collective and co-founded the iTKNe transnational knowledge exchange platform for teacher educators. Active in global academic networks addressing East Asian education stereotypes and postcolonial educational research.

• English Language Teacher Education (ELTE)
• Teacher Development
• Reflective Practice
• +۵ مورد دیگر

Steve Mann is a Professor in Applied Linguistics at the University of Warwick, where he has been affiliated since 2007. His work focuses on English Language Teacher Education (ELTE), teacher development, and qualitative research methodologies. He holds a PGCE from the University of Warwick (1984) and has extensive experience in ELT across Hong Kong, Japan, and Europe. Mann’s research group investigates reflective practice, teacher beliefs, mentoring, and technology integration in education. Notable contributions include co-editing the Routledge Handbook of English Language Teacher Education (2019) and pioneering studies on video-based teacher reflection. He has supervised numerous PhD students exploring aspects of teacher development, though he is currently not accepting new PhD candidates. Education: PGCE, University of Warwick (1984) Pre-service teaching in English and Drama in England (1980s) British Council Teaching Scheme in Hong Kong (1980s) Research Interests: Teacher education, reflective practice, qualitative interview methodologies, and the role of technology in professional development. His work emphasizes bridging theory and practice in ELT, particularly through collaborative dialogue and action research. Grants & Projects: Supporting Sustainable English Teacher Professional Development in Yunnan Province (British Council, 2022–2023) China Course Research: Postgraduate Curriculum Design (2019–2022) Video in Language Teacher Education (British Council, 2016–2018) Labs/Teams: Leads a research group focused on teacher development, mentoring, and blended learning strategies. Collaborates with institutions like the British Council on global teacher education initiatives.

Ola Svenssonمشاهده پروفایل

دانشیار

• Approximation Algorithms
• Combinatorial Optimization
• Computational Complexity
• +۳ مورد دیگر

Ola Svensson is an Associate Professor at the School of Computer and Communication Sciences , EPFL. His research spans approximation algorithms, combinatorial optimization, computational complexity, and scheduling. He holds an ERC Consolidator Grant (2023–) and previously received an ERC Starting Grant (2014–2019) and SNF grant (2019–2023). Education: PhD in Computer Science from IDSIA, Università della Svizzera italiana (2009) M.Sc. from Uppsala University (2005) Research Focus: Svensson develops novel techniques for NP-hard problems, with emphasis on primal-dual methods, LP/SDP hierarchies, and hardness proofs. His work applies to clustering, scheduling, network design, and submodular optimization. Publications: His 15 most recent works (2018–2021) focus on learning-augmented algorithms, robust optimization, and improved approximations for clustering/TSP. Key trends include integration of ML with classical algorithms and quasi-polynomial methods for combinatorial problems. Awards: Best Paper Awards at FOCS (2011, 2017) and STOC (2018) I&C Teaching Award at EPFL Advising & Grants: He advises 6 current PhD students and graduated 8 others. Major grants include ERC Starting Grant 'OptApprox' (€1.4M) and ERC Consolidator Grant 'POTCO' (€2M). Teaching: Leads courses in Advanced Algorithms, Computational Complexity, and Approximation Algorithms. He developed pedagogical frameworks for scribe notes and project-based learning in theoretical computer science.

Arjan F. Kirkelsمشاهده پروفایل

استادیار

• Sustainability Assessment
• Life Cycle Assessment (LCA)
• Technology Assessment
• +۱۳ مورد دیگر

Arjan F. Kirkels is an Assistant Professor and University Lecturer in the Department of Technology, Innovation & Society within the School of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e). His work focuses on sustainability assessments, decision-making in transitions, and interdisciplinary education for sustainable innovation. His research interests include Life Cycle Assessment (LCA), Multi-Criteria Assessment (MCA), sustainability transitions, industrial ecology, and systems engineering. He applies these to emerging technologies such as batteries, hydrogen systems, and heat pumps, with a strong emphasis on integrating stakeholder values and addressing deep uncertainties in sustainability decisions. The recent articles highlight a consistent focus on assessing emerging technologies, particularly in renewable energy and circular economy applications. Trends include prospective LCA, experience curves in solar technology, socio-technical impact assessment, and educational innovations in sustainability. His work bridges technical analysis with social and governance dimensions of sustainability transitions. Best Teacher Award, 1st year Bachelor Sustainable Innovation, for course 0SV20 'Industrial Ecology' (2013) Best Teacher Award, 1st year Bachelor Sustainable Innovation, for course 0SV20 'Industrial Ecology' (2018) Best Teacher Award, 1st year Bachelor Sustainable Innovation, for course 0SV20 'Industrial Ecology' (2020) Educational award nomination, bachelor Sustainable Innovation, course 0SK30 Inter-University Sustainability Challenge (2023) Education Award 2024 - master Innovation Sciences (2025) Arjan F. Kirkels has supervised over 100 thesis students and more than 100 interdisciplinary student groups. He has developed and taught over 20 courses and co-authored 4 textbooks and 7 publications on educational innovation. He is currently supervising four researchers: Huiying Liu, Prapti Maharjan, Rishi Bhatnagar, and Seyed Mousavi. His research is supported by projects such as the EU-funded cVPP (Community-based Virtual Power Plant) and studies on Dutch sustainability transitions. He is actively involved in educational initiatives, including MOOC development and challenge-based learning, and contributes to public discourse through media appearances and workshops on sustainability education and systems thinking.

Jignesh M. Patelمشاهده پروفایل

استاد

• Data Management
• Database Systems
• Machine Learning
• +۳ مورد دیگر

Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University , focusing on Data Management , System Efficiency (e.g., Scalable Data Platforms), and Human Efficiency (e.g., LLM-Based Query Interfaces). His work bridges Database Systems , Machine Learning , and Human-Computer Interaction . Co-founder of four startups: Paradise (1997), Locomatix (2007), Quickstep (2015), and DataChat (2017). Member of SIGMOD 2025 (AE) , CIDR 2024 (Co-Chair) , and other program committees. Research Interests include efficient data analysis algorithms , LLM-based data interaction , and systems security . His group develops platforms combining scalability and user productivity . Scientific Awards include Best Paper Awards at SIGMOD and VLDB, and Fellowships from AAAS, ACM, and IEEE. He also received Teaching Awards at CMU. Professional Activities feature co-founding startups , serving on program committees , and teaching courses like Database Systems and Advanced Database Systems at CMU.