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Agnes HorvatView profile

Associate Professor

• Human-Centered Computing
• Network Science
• Artificial Intelligence
• +5 more

Agnes Horvat is an Associate Professor of Communication (with a courtesy appointment in Computer Science) at Northwestern University. She directs the Technology and Social Behavior (TSB) joint doctoral program between the McCormick School of Engineering and the School of Communication, and leads the Lab on Innovation, Networks, and Knowledge (LINK). Her research focuses on human-centered computing, network science, and AI's impact on information production/sharing in digital platforms. She has received NSF CAREER, CRII, and collaborative awards as PI. Her work examines algorithmic bias in online spaces, AI-assisted creativity (e.g., LLMs in biomedical writing and music), and collective intelligence dynamics. Media coverage includes Nature , Washington Post , and Le Monde . Her advisees have won prestigious fellowships like the Northwestern Presidential Fellowship and best paper awards at top conferences. Research interests include: (1) algorithmic bias in social media and crowdfunding, (2) AI-driven creativity expansion, (3) network structures of scientific attention, and (4) opinion dynamics in online discussions. Current projects explore LLMs' role in scientific writing and music composition, while past work analyzed gender disparities in scholarly self-promotion and retraction paper attention patterns. Grants: NSF CAREER Award (202?), NSF CRII (202?), Collaborative Grant (202?) Labs/Teams: LINK Lab (focusing on innovation networks), TSB Program (interdisciplinary engineering/communication PhD)

Gita Steiner-KhamsiView profile

Professor

• Policy borrowing and lending
• Globalization studies
• Comparative policy studies
• +9 more

Gita Steiner-Khamsi is the William Heard Kilpatrick Professor of Comparative Education at Teachers College, Columbia University, where she chairs the Department of International and Transcultural Studies. She also holds a UNESCO Chair in Comparative Education Policy at the Geneva Graduate Institute of International and Development Studies. Her career spans over three decades with significant contributions to understanding how educational policies travel across national borders and are adapted in local contexts. Her educational background includes a Ph.D. in Social Psychology from the University of Zürich (1983) and an honorary doctoral degree from Mongolian State University of Education (2004). Prior to joining Columbia, she worked for ten years on multicultural and anti-racist education policies at the Ministry of Education in Zurich, Switzerland. Steiner-Khamsi's research focuses on policy borrowing and lending, globalization studies, comparative policy analysis, school reform, and teacher policy. She has pioneered system-theoretical approaches to understanding externalization, reception, and translation of educational policies across borders. Her work examines how international organizations govern education in the absence of coercive measures and how governments respond to global norm-setting. Her publication record shows consistent scholarly output with increasing focus on knowledge brokerage as a global governance tool, soft governance through international comparison, and transnational accreditation of public schools. Her most recent book (2025) explores the seven temporalities of global school reform, demonstrating her continued evolution in examining the time dimensions of policy transfer. William Heard Kilpatrick Professor of Comparative Education UNESCO Chair in Comparative Education Policy Dr. h.c. from Mongolian State University of Education Steiner-Khamsi has supervised over 60 doctoral students (PhDs and EdDs) and has led significant international projects including the USAID Teacher Education Project in Pakistan, which she describes as giving "ownership to Pakistanis" rather than having donors dictate implementation. Her research has been supported by various international organizations including UNICEF, where she investigated teacher shortages in Eastern Europe and Central Asia. She maintains active research projects examining public-private partnerships in education, global governance mechanisms, and transnational accreditation systems, continuing to shape the field of comparative education policy through both theoretical contributions and practical applications in diverse international contexts.

Ali GhodsiView profile

Professor

• Machine Learning
• Deep Learning
• Natural Language Processing
• +3 more

Ali Ghodsi is a Professor at the University of Waterloo and Director of the Data Science Lab, with affiliations at the Vector Institute. His research spans machine learning, deep learning, and artificial intelligence, with applications in natural language processing, bioinformatics, and computer vision. His group develops theoretical frameworks and algorithms for analyzing large-scale datasets, focusing on neural network architectures, knowledge distillation, and model efficiency. Current projects include deep learning for identity control, computational antibody design, and generative AI/large language models. Ghodsi has authored influential tutorials on diffusion models, graph neural networks, and large language models. Notable research contributions include computational methods for de novo peptide sequencing from mass spectrometry data, green simulation-assisted reinforcement learning, and efficient natural language processing models. His lab maintains collaborations with industry partners including Google, Amazon, and Roche.

Sabine SüsstrunkView profile

Professor

• Computational Imaging
• Computational Photography
• Color Image Processing
• +4 more

Sabine Süsstrunk is a Full Professor and Director of the Images and Visual Representation Laboratory (IVRL) at EPFL's School of Computer and Communication Sciences. She holds a BS in Scientific Photography from ETH Zürich, MS from Rochester Institute of Technology, and PhD from University of East Anglia. Her career includes positions at Hewlett-Packard Labs and Corbis Corporation. Her research explores computational imaging, computational photography, color processing, computer vision, and image quality. Key interests include near-infrared applications, multispectral imaging, and computational aesthetics. Her work bridges hardware and software solutions for imaging challenges. Publications demonstrate consistent focus on advancing generative models (diffusion models, neural cellular automata), 3D reconstruction (NeRF variants), and media integrity (DeepFake detection). Recent trends show increased emphasis on 3D vision, robustness in generative AI, and video analysis. Awards & Honors: IS&T/SPIE Electronic Imaging Scientist of the Year (2013) Raymond C. Bowman Teaching Award (2018) EPFL AGEPoly IC Polysphere Award (2020) 8 Best Paper/Demo Awards Fellowships: IEEE, IS&T, ELLIS, AIIA She leads the IVRL lab and advises PhD candidates while serving as President of the Swiss Science Council. Research is supported through competitive grants and industry collaborations.

• Family Business Governance
• Entrepreneurial Firm Innovation
• Internationalization
• +2 more

Cristina Bettinelli is a full professor in the Department of Management at the University of Bergamo. She serves as Director of the MSc Program in International Management and Marketing (IMM) and Director of the Center for Young and Family Enterprise (CYFE). Her research focuses on family business governance , entrepreneurial firm innovation , and internationalization , with publications in journals like Family Business Review , Entrepreneurship Theory and Practice , and Journal of Family Business Strategy . Member of editorial boards: Family Business Review , Journal of Family Business Strategy Professional activities: Innovative training projects, Marketing Lhab research group (since 2024) Scientific Awards: Best Contribution to Practice Paper (2024) - IFERA Best Unpublished Research Paper Award (2022, 2015) - FFI Multiple Best Paper Awards/Nominations - IFERA, EIASM, ICSB Family Business Review Best Paper Award (2012) Recent Research Trends: Analyzes family firm dynamics, pandemic response behaviors, cross-border e-commerce strategies, and B corporation ethics. Her 2024-2025 publications emphasize organizational identity , crisis management , and strategic governance .

Stephanie RogersView profile

Assistant Professor

• Geospatial Technologies
• Environmental Applications
• Water Quality and Contamination
• +6 more

Stephanie Rogers is an Assistant Professor of Geosciences at Auburn University's College of Sciences and Mathematics, specializing in geospatial technologies and environmental applications. She leads the GeoIDEA Lab, focusing on GIScience, water quality modeling, and environmental impacts on honey bee colonies. Her research integrates emerging technologies like drones for ecological monitoring and addresses interdisciplinary challenges such as groundwater management and pollution tracking. Education: PhD in Geosciences from the University of Fribourg, Switzerland. Research Interests: Rogers' work bridges geospatial innovation with real-world problem-solving. Key areas include: GIS-driven environmental monitoring and modeling Drone-based assessment of water quality and algal blooms Groundwater contamination dynamics and public health implications Honey bee colony health through spatial analysis Advising & Grants: Currently mentors two trainees (Bethany Foust and Mallory Jordan) and collaborates on projects funded by environmental agencies. Her grants focus on geospatial data integration for ecological decision-making. Labs/Teams: GeoIDEA Lab coordinates multidisciplinary efforts in environmental geoscience, with active projects in Alabama's Black Belt region and international glacial archaeology initiatives.

Albert ChengView profile

Professor

• Real-Time Systems
• Cyber-Physical Systems
• Internet of Things (IoT)
• +3 more

Professor Albert Cheng is a faculty member in the Department of Computer Science at the University of Houston. His research focuses on real-time systems, cyber-physical systems, smart cities, and embedded systems with societal impacts. He has authored over 270 publications and a textbook on real-time systems. Cheng holds roles as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering and ACM Computing Surveys. His research interests span real-time scheduling, machine learning applications, and systems optimization. Recent work includes vehicular traffic modeling for epidemiological risk reduction, quantum computing response time analysis, and satellite mission planning. Awards include Fulbright Specialist, Distinguished ACM membership, and IEEE Senior Member status. Cheng’s articles demonstrate expertise in real-time scheduling algorithms, cyber-physical systems development, and smart city infrastructure. His contributions bridge theoretical computer science with practical implementations in transportation, healthcare, and aerospace domains. Ongoing efforts include fault-tolerant systems, energy-efficient scheduling, and CPS education initiatives. Awards: Fulbright Specialist, ACM Distinguished Member, IEEE Senior Member, Institute of Physics Fellow Labs/Teams: Hewlett Packard Enterprise Data Science Institute (HPE DSI), Research Computing Data Core (RCDC)

Stephen FerrignoView profile

Assistant Professor

• Cognitive Development
• Comparative Cognition
• Number Cognition
• +4 more

Stephen Ferrigno is an Assistant Professor and Chair of the Biology of Brain and Behavior Area Group at the University of Wisconsin-Madison's Department of Psychology. His research investigates the origins of uniquely human cognition through developmental, comparative, and cross-cultural methodologies. He focuses on foundational cognitive abilities such as number sense, recursive grammar, logical reasoning, and metacognition, exploring their evolutionary and developmental bases. Ferrigno's work bridges disciplines including cognitive neuroscience, developmental psychology, and cultural anthropology, with practical applications in early childhood education and curriculum design. His research employs cross-cultural studies with indigenous populations (e.g., the Tsimane) to assess cultural variability in cognitive development. Key themes include spatial mappings of numerical concepts, recursive sequence processing in non-human primates, and the metacognitive capacities shared between humans and monkeys. The Cognitive Origins Lab, led by Ferrigno, seeks to uncover universal cognitive principles while identifying culturally mediated differences. No scientific awards or grants are explicitly listed in the provided materials. While no advisees are mentioned, his research program suggests involvement in mentoring graduate students through the Department of Psychology's PhD program. Current projects include investigating the developmental trajectories of logical reasoning, the neural correlates of recursive sequence processing, and the design of culturally adaptive educational interventions targeting early math and language skills in preschool settings.

Andrea GreveView profile

Lecturer

• Cognitive Psychology
• Memory Studies
• Neuroscience
• +3 more

Dr Andrea Greve is a Lecturer in the Department of Psychology at the University of Cambridge . Her research focuses on cognitive processes related to memory, prediction error, and learning mechanisms. Key areas of interest include declarative memory formation, semantic predictions, and the influence of novelty on memory retention. She has explored topics such as word learning in variable-choice paradigms, the role of hippocampal lesions in memory binding, and predictive coding in neuroimaging contexts. Her work integrates experimental psychology with neuroscience methodologies, particularly leveraging neuroimaging techniques to investigate memory systems. Notable contributions include studies on false memory effects, the nonmonotonic relationship between object-location memory and expectedness, and the impact of prior knowledge on memory encoding. Dr. Greve has also contributed to methodological advancements, such as improved MRI anonymization for MEG coregistration. While her research spans multiple decades, recent efforts (2023–2025) emphasize predictive frameworks and their applications in understanding cognitive phenomena like semantic surprise and episodic memory formation. Her findings challenge traditional assumptions about fast mapping in adults and highlight the importance of integrating computational models with empirical data. Dr. Greve collaborates extensively with neuroimaging and cognitive science teams, contributing to interdisciplinary projects that bridge theoretical and applied research in memory systems. Her work maintains a strong focus on methodological rigor, particularly in experimental design and data interpretation.

• Lean construction
• Takt planning
• Industrialized Construction
• +12 more

Iris D. Tommelein serves as the Roy W. Carlson Distinguished Professor in the Civil and Environmental Engineering Department at the University of California, Berkeley's College of Engineering, where she directs the Project Production Systems Laboratory (P2SL). A globally recognized pioneer in Lean Construction, she has revolutionized architecture-engineering-construction (AEC) practices through research, industry workshops, and leadership since co-founding the Lean Construction Institute in 1997. Her educational foundation spans multiple disciplines: Ph.D. in Civil Engineering (Construction Engineering and Management), Stanford University, 1989 M.S. in Computer Science (Artificial Intelligence), Stanford University, 1989 M.S. in Civil Engineering (Construction Engineering and Management), Stanford University, 1985 B.S. (5-year degree) in Civil Engineer-Architect, Vrije Universiteit Brussel, Belgium, 1984 Professor Tommelein's research centers on transforming construction processes through Lean principles and digital innovation . Her work pioneers takt planning for workflow reliability, industrialized construction for labor and sustainability challenges, and mistakeproofing to eliminate errors. She integrates digital twins , AI , and optimization to develop practical decision-support systems for supply chains, logistics, and production management. Recent focus includes modular offsite construction and Industry 4.0 applications. Analysis of her 2023-2025 publications reveals intensifying research on takt planning maturity models and industrialized construction feasibility , with growing emphasis on mass timber automation and visual management systems. Her work consistently bridges lean theory with practical implementation across megaprojects, subcontracting networks, and heavy civil engineering. Her exceptional contributions have earned: Lean Pioneer Award (Lean Construction Institute, 2015) National Academy of Construction induction (2019) PPI Technical Achievement Award (2022) Robert B. Harris Award (University of Michigan, 2024) ASCE Construction Management Award (2024) - first woman recipient in 51 years Through the P2SL, she leads industry-collaborative research on production system design, mistakeproofing frameworks, and digital transformation. Her grant-funded projects develop assessment tools for industrialized construction adoption and takt planning methods adaptable to diverse project types. She actively mentors graduate students and drives knowledge transfer via workshops and the annual Construction Innovation Day. The Project Production Systems Laboratory (P2SL) operates as a global hub for construction innovation, partnering with owners, contractors, and suppliers to implement lean production systems. Current initiatives include developing serious games for mistakeproofing training, optimizing work density methods for heavy civil projects, and creating digital twins for real-time construction management.

Carl Henrik EkView profile

Professor

• Machine Learning
• Artificial Intelligence
• Bayesian Non-parametric Methods
• +6 more

Carl Henrik Ek is a Professor of Statistical Learning at the Department of Computer Science and Technology (Computer Laboratory) at the University of Cambridge. He is also a fellow and Director of Studies at Pembroke College, and holds visiting positions at Karolinska Institute in Stockholm and the Royal Institute of Technology. He serves as co-Director for the UKRI AI Centre for Doctoral Training in Decision Making for Complex Systems, a collaboration between Cambridge and Manchester universities, and is involved with the Accelerate Program in the Computer Laboratory. Dr. Ek's educational background includes a MEng degree in Vehicle Engineering from the Royal Institute of Technology in Stockholm, followed by a PhD from Oxford Brookes University. During his PhD, he spent time at the University of Manchester and the University of Sheffield. His PhD supervisors were Professor Neil Lawrence and Professor Phil Torr, and his postdoctoral research was conducted at UC Berkeley with Professor Trevor Darrell and Professor Raquel Urtasun. Professor Ek's research focuses on statistical learning, particularly on developing data-efficient and interpretable machine learning methods. His work spans modeling and inference in machine learning, with special emphasis on Bayesian non-parametric methods and Gaussian processes. He explores how to specify assumptions that allow learning from small amounts of data, bridging theoretical foundations with practical applications in various domains. His recent publications demonstrate a strong trend toward applying machine learning to healthcare, drug discovery, and engineering design. There's significant work on Gaussian processes, reinforcement learning, and generative models, with applications ranging from medical diagnostics to structural engineering. His research shows an increasing interdisciplinary focus, connecting machine learning with fields like cardiology, pharmacology, and computational geometry. Professor Ek has received numerous teaching awards throughout his career: Pilkington Price for Teaching Excellence (2024) Teacher of the year in Computer Science at University of Bristol (2016) Docent in Machine Learning at Royal Institute of Technology (2016) Teacher of the year at Royal Institute of Technology, Sweden (2015) Teacher of the year from Student chapter in Industrial Economics at Royal Institute of Technology (2015) Teacher of the year in Computer Science at Royal Institute of Technology (2012) Professor Ek teaches Advanced Data Science, Advanced topics in machine learning, and Machine Learning and the Physical World. He has supervised PhD students throughout his career but is not currently accepting new PhD students for 2025/26 or 2026/27. His research is supported by various grants, including his role as co-Director of the UKRI AI Centre for Doctoral Training. He is an active member of the ml@cl research group at Cambridge and has previously been involved with research groups at University of Bristol and Royal Institute of Technology. His work connects with several interdisciplinary initiatives, particularly in healthcare AI and engineering applications of machine learning.

Hong HuaqingView profile

Professor

• Corpus Linguistics
• Computer-Assisted Instruction
• Machine Translation
• +3 more

Hong Huaqing is a Professor and doctoral supervisor at the Corpus Research Institute of Shanghai International Studies University. He holds roles as honorary director of the Chinese Corpus Linguistics Research Association and international expert at Peking University's Education Development Center. Formerly, he worked at Nanyang Technological University (Singapore) in roles such as researcher at the Learning Research and Development Center and director of the e-Learning Center of the Lee Kong Chian School of Medicine. His research spans machine translation, natural language processing, corpus linguistics, and educational technology. He supervises master's and doctoral students, co-supervises postdoctoral researchers, and focuses on smart education driven by big data analysis and innovative learning ecosystems. Research emphasizes corpus-based methods applied to language education, including computational frameworks for student engagement, wearable sensors in learning analytics, and cross-linguistic rhetoric studies. His work bridges technological innovation (e.g., AI-driven tutorial systems) with pedagogical practice, addressing challenges in non-English language education and teacher training.

Gianvito LanzollaView profile

Professor

• Digital Transformation
• Technology Strategy
• Competitive Dynamics
• +7 more

Gianvito Lanzolla is a Professor of Strategy at Bayes Business School (formerly Cass), City, University of London, where he has been employed since April 2006 and served as Dean of the Faculty of Management from 2016-2020. He founded the Bayes Digital Leadership Research Centre and is a Fellow of the Royal Society of Arts. Education: MSc in Mechanical Engineering, PhD in Strategic Management Visiting Appointments: London Business School, Indian School of Business, ESMT Berlin His research focuses on digital transformation, technology strategy, institutional change, and competitive dynamics. He examines how CEOs' digital orientation and board characteristics affect firm value, with publications in Academy of Management Journal , Harvard Business Review , and California Management Review . His work has won multiple academic prizes and been featured in major media outlets. Recent publications analyze digital ecosystems, agile transformation, and AI applications in finance. He teaches 'Strategic Leadership' and 'Digital Transformation' in MBA programs, having won teaching excellence awards in 2007, 2008, 2009, 2012, and 2015. Scientific Awards: City University Teaching Excellence Awards (2015, 2012, 2009, 2008) Strategic Management Society Best Paper Award (2012) SSRN Top Ten Downloaded Paper (2008) Spanish Academy of Management Best Paper Award (2009)

Ben HalpernView profile

Professor

• Marine Ecology
• Conservation Planning
• Climate Change Impacts
• +3 more

Ben Halpern is a Professor at the Bren School of Environmental Science & Management and Director of the National Center for Ecological Analysis and Synthesis (NCEAS) at UC Santa Barbara. He holds a PhD in Ecology from UCSB and a BA in Biology from Carleton College. His research focuses on marine ecology and conservation planning, with expertise in cumulative impact assessments, marine reserves, and the Ocean Health Index. He has led global projects on ocean health, biodiversity threats, and sustainable aquaculture, collaborating with institutions worldwide. Notable roles include co-founding the Conservation Aquaculture Research Team (CART) and serving as a part-time Chair in Marine Conservation at Imperial College London (2013–2018). Research interests span marine biodiversity conservation, climate change impacts on ecosystems, and the integration of ecological and social data into policy. His work emphasizes interdisciplinary approaches to address environmental challenges, such as mapping wastewater impacts, evaluating aquaculture sustainability, and developing tools for marine spatial planning. Awards include the Smith Fellowship Program (sponsored by The Nature Conservancy) during his postdoctoral work. He teaches Bren School courses, mentors graduate students, and leads collaborative research teams. Current projects include analyzing climate change effects on aquaculture and advancing the Ocean Health Index framework to support global conservation efforts.

• STEM Education
• Pedagogical Content Knowledge (PCK)
• Teacher Expertise
• +3 more

Amanda Berry is a Professor of STEM Education and Deputy Dean (Research & Innovation) in the School of Education at RMIT University, Australia. Her research focuses on science education, teacher education, and methodologies for capturing classroom practices. She leads initiatives to develop tools for representing teachers' pedagogical expertise and has contributed to frameworks like the refined consensus model of pedagogical content knowledge (PCK). Her work emphasizes teacher professional development, particularly for highly accomplished educators, and explores adaptive expertise in interdisciplinary teaching. She actively supervises postgraduate research students and collaborates internationally on projects like the Sharing Knowledge Project in inquiry-based teaching. Key research themes include STEM integration, teacher educator professionalism, and the role of student voice in assessment reform. Her interdisciplinary approaches bridge theory and practice, influencing both policy and classroom strategies in science and mathematics education.