Kees van Veen is an Associate Professor at the University of Groningen, affiliated with the Faculty of Behavioural and Social Sciences and the Department of Sociology. His expertise spans Corporate Governance , Policy Evaluation , and Sustainable Food Systems , with significant contributions to International Business & Management and Social Psychology during the pandemic. Education : MSc in Sociology (cum laude) from the University of Groningen. Research Focus : Interdisciplinary work bridging organizational behavior, prosociality, and global health behaviors, leveraging machine learning for cross-national pandemic analysis. His recent publications analyze prosocial behavior , conspiracy beliefs , and lockdown psychology through multi-country longitudinal data, emphasizing UN Sustainable Development Goals . He supervises MSc theses in Business Administration and Sociology and collaborates on open datasets like PsyCorona .
Justin P. Haldar is a Professor in the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California (USC), with a joint appointment in the Department of Biomedical Engineering. He co-directs the Biomedical Imaging Group and serves as Director of the Signal and Image Processing Institute. His affiliations include the Dornsife Cognitive Neuroscience Imaging Center, the Brain and Creativity Institute, and the Dynamic Imaging Science Center. Education : B.S. and M.S. in Electrical Engineering (2004, 2005), Ph.D. in Electrical and Computer Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on computational imaging, inverse problems, and magnetic resonance imaging (MRI), with an emphasis on constrained image reconstruction, parameter estimation, and novel data acquisition strategies. His work combines physical modeling, high-dimensional signal structures, and fast computational algorithms to address MRI's limitations in speed, noise, and cost. Recent publications analyze challenges like the 'hidden noise' problem in MR reconstruction (2025) and innovations in dynamic imaging. His research has enabled faster MRI exams and next-generation imaging techniques by exploiting dimensionality's 'blessings' while mitigating its 'curses.' Scientific awards : NSF CAREER Award (2014) IEEE ISBI Best Paper Award (2010) IEEE EMBC First-Place Student Paper Award Haldar's leadership roles include Chair of the IEEE Signal Processing Society's Technical Committee on Computational Imaging and editorial positions at IEEE Transactions on Computational Imaging and Magnetic Resonance in Medicine . He actively mentors students and develops novel MRI approaches at USC's Michelson Center for Convergent Bioscience.
Prof. Dr. Jonas Schützeneder is a Professor of Digital Journalism at the University of the Bundeswehr Munich, where he serves as Deputy Chair of the Examination Board. He holds a doctorate in Sports Journalism and Sports Communication and completed his habilitation in Innovation Communication. His academic responsibilities include teaching digital journalism in the Management and Media program (BA/MA), with a focus on data journalism, social media strategies, and online formats. Schützeneder's research explores transformative trends in journalism, with core interests in: Artificial intelligence applications in newsrooms Social media's impact on journalism practices Innovation communication and media evolution Podcast formats and audio storytelling strategies Ethical dimensions of digital journalism His publications demonstrate a consistent focus on journalism's digital transformation, particularly examining how emerging technologies like AI and social platforms are reshaping content production, distribution, and ethical frameworks across European media landscapes. His scientific recognitions include: University Teaching Award from Catholic University of Eichstätt-Ingolstadt (awarded twice) Multiple nominations for Teaching Award at Magdeburg-Stendal University of Applied Sciences Schützeneder leads the podcast project 'Held:innen von Magdeburg' where students research and produce content about contemporary and historical figures. Since 2018, he has served on the editorial board of Communicatio Socialis, an academic journal on media ethics, where he manages peer review processes. Since 2024, he co-heads the DGPuK Journalism Section, a 400-member organization within the German Society for Journalism and Communication Studies.
Etienne Ollion is a Professor of Sociology at École Polytechnique and a Research Director at the Centre national de la recherche scientifique (CNRS). He maintains dual appointments that position him at the intersection of traditional political sociology and emerging computational methods. His academic work spans both French and international institutions, with teaching invitations at ENS-Paris, Berkeley, University of Chicago, Sciences Po Paris, and other leading universities worldwide. His research program focuses on two interconnected domains: the sociology of politics and power, and computational social sciences. Ollion's work examines political professionalization, parliamentary dynamics, and the transformation of political fields, particularly through his ethnographic study of the 2017 French National Assembly documented in his book The Candidates: Amateurs and Professionals in Politics (Oxford University Press, 2024). Simultaneously, he pioneers methodological innovations applying machine learning and natural language processing to social science research. Ollion's recent publications reveal a trajectory increasingly focused on the intersection of AI and social science methodology, with numerous 2024-2025 publications addressing LLM applications, text annotation, and the ethical considerations of proprietary AI systems in research. His work demonstrates how computational methods can enhance traditional social science approaches while maintaining critical awareness of technological limitations. As an academic leader, Ollion directs the Computational Social Sciences initiative at the IPP and has developed educational resources including online courses and the aweSOM software for data analysis. He regularly organizes summer schools (SICSS-Paris) and workshops to disseminate computational methods across the social sciences. Ollion serves on the editorial board of Actes de la recherche en sciences sociales and maintains an active public presence through media appearances, including a notable interview on France Inter about AI and Social Sciences in September 2024. His upcoming book talk at The Seminary Co-op in Chicago on March 7, 2025 further demonstrates his active engagement with the international academic community.
Lisa Wu Wills is an Assistant Professor in the Department of Computer Science and Electrical and Computer Engineering at Duke University, leading the APEX Lab (Application-driven Programmable Efficient Accelerated Systems Lab). Her research focuses on hardware acceleration for big data analytics in genomics, graphs, and databases to advance healthcare and natural sciences. Education: Ph.D. in Computer Science, Columbia University, 2014 Research Interests: Dr. Wills pioneers computer architecture and hardware-software co-design to create efficient accelerators for emerging applications. Her work targets genomics , graph analytics , and database systems , emphasizing simplified hardware deployment and energy efficiency for scientific breakthroughs in healthcare and AI. Publication Trends: Her 2022-2025 publications reveal a strong focus on open-source frameworks (Beethoven, PyTFHE) for accelerator development, hardware acceleration in privacy-preserving computing, and optimization for large language models. Key themes include transfer learning for EDA, domain-specific architectures for genomics, and energy-efficient image processing. Scientific Awards: Google ML and Systems Junior Faculty Award (2025) Advising and Grants: Dr. Wills mentors three PhD students: Chris Kjellqvist (Beethoven framework architect), Mason Ma (PyTFHE lead for FHE applications), and Mansi Choudhary (COCOSSim simulator creator). Her 2025 Google award funds research on accelerating vector databases and retrieval-augmented generation for LLMs. Labs and Teams: She directs the APEX Lab at Duke, developing tools like Beethoven (open-source accelerator composer) and PyTFHE for hardware-software integration, enabling domain scientists to leverage custom acceleration with minimal hardware expertise.
J. Ilja Siepmann is a Distinguished McKnight University Professor and Distinguished University Teaching Professor at the University of Minnesota's Department of Chemistry, with affiliations spanning Chemical Engineering, Materials Science, and Data Science. His research integrates molecular simulations, force field development, and machine learning to study adsorption phenomena, phase equilibria, polymer chemistry, and nanoporous materials. Education: Undergraduate: University of Freiburg, Germany (1983-1987) Graduate: University of Cambridge, UK (PhD, 1988-1991) Post-doctoral: IBM Zurich Research Lab, Koninklijke/Shell Lab, and University of Pennsylvania (1991-1994) Research interests focus on chemical theory, materials genomics, and environmental chemistry, with emphasis on energy-efficient separations, nanostructured materials, and sustainable chemical processes. Computational methods like Monte Carlo algorithms and machine learning underpin his investigations into fluid interfaces, nucleation, and catalytic systems. Recent publications emphasize adsorption thermodynamics, molecular simulations of complex fluids, data-driven materials discovery, and polymer self-assembly. Trends include integration of machine learning with molecular modeling, nanoporous materials for clean energy, and phase behavior of refrigerants. Awards: Distinguished McKnight University Professor Distinguished University Teaching Professor Advises graduate and undergraduate researchers in computational chemistry projects. Leads the Siepmann Group at Kolthoff Hall, part of the Chemical Theory Center and Nanoporous Materials Genome Center. Research funded through MURI and industry partnerships.
Kilian Q. Weinberger is a Professor of Computer Science at Cornell University's College of Engineering, focusing on Machine Learning, Deep Learning, and AI applications. He has held previous roles as Associate Professor at Washington University in St. Louis and Research Scientist at Yahoo! Research. His research spans metric learning, resource-constrained learning, Gaussian Processes, and advancements in 3D perception for autonomous systems. Education : Ph.D. in Machine Learning (University of Pennsylvania), BA in Mathematics and Computing (University of Oxford) Key Research Areas : AI in Science, Computer Vision, Autonomous Vehicles, and Neural Network Efficiency His recent work emphasizes interpretable machine learning, large language models, and multimodal applications. Awards include NSF CAREER (2012) Daniel M Lazar '29 Teaching Award (2016) Ann S. Bowers Excellence Award (2024) ACM and AAAI Fellow (2024) He teaches advanced courses like CS6784 (Cornell) and has mentored numerous PhD students across institutions. Current affiliations include the Sloan Research Fellowships Selection Committee since 2024.
James D. Ivory is a Professor of Media Studies in the Department of English at Virginia Tech's College of Liberal Arts and Human Sciences. He has been a faculty member at Virginia Tech since 2005, initially in the Communication department before transitioning to the English department. His work bridges the humanities and digital media studies, focusing on the social and psychological impacts of interactive technologies. Ivory directs research in the VT G.A.M.E.R. Lab, part of the university's Digital Media Research Facility, and has established himself as a leading scholar in game studies and digital media effects research. Dr. Ivory's educational background includes: Ph.D. in Mass Communication from the University of North Carolina at Chapel Hill (2005) M.A. in Communication from the University of Wyoming (2002) B.S. in Communication from the University of Wyoming (2000) Dr. Ivory's primary research focuses on the social, behavioral, and cultural dimensions of interactive digital media, particularly video games, simulations, and virtual environments. His work examines how technological features of new entertainment media affect users' experiences and behaviors. He also investigates research practices and how scientific findings are communicated to both scholarly communities and the public. His interdisciplinary approach spans communication, psychology, human-computer interaction, and media studies, addressing critical questions about digital media's role in society, including issues of representation, ethics, and mental health impacts. His recent publications demonstrate a growing emphasis on methodological rigor in digital media research, with increasing attention to open science practices and research reproducibility. While maintaining his focus on video games and virtual environments, his work has expanded to address broader questions about scientific communication, research ethics, and the translation of findings to policy contexts. His scholarship shows a trajectory from examining specific media effects toward more meta-scientific concerns about how research in this field is conducted and communicated. Dr. Ivory has received recognition through media coverage of his expertise in major outlets including USA Today and The Washington Post, particularly regarding video games and digital communication. His work has been cited extensively across multiple disciplines. As an educator, Dr. Ivory has mentored numerous students through course instruction and curriculum development. He has been instrumental in developing innovative programs including the Digital Game Design/Analysis curriculum and Communicating Science initiatives. His teaching spans research methods, communication technology, media effects, and digital media production. Dr. Ivory leads the VT G.A.M.E.R. Lab (Games, Applied Media, and Experimental Research), which serves as a hub for interdisciplinary research on interactive media. The lab supports both faculty and student research projects examining various aspects of digital gaming and virtual environments. Through this facility, he fosters collaboration between humanities scholars and technologists to advance understanding of digital media's societal impacts.
David Latulippe is a Professor in the Department of Chemical Engineering at McMaster University. He joined McMaster in 2012 after postdoctoral work at Cornell University and a PhD at Penn State University, focusing on membrane filtration for DNA purification. His industrial experience includes roles at ZENON Environmental (now GE Water) in hollow-fiber membrane design for water treatment. Research interests include Membrane science and technology Bioprocessing of therapeutic viruses Microscale systems for biological applications Environmental engineering solutions for water treatment Current projects involve collaborations with industry partners like Ceapro and Aevitas, and the development of a biomanufacturing automation lab with Sartorius. Recent publications highlight advancements in Nanofiltration and microfiltration for viral vectors Conductive membranes for electrochemical applications Microfluidic systems for DNA analysis Environmental monitoring of biocides and microplastics Scientific recognition includes the Young Membrane Scientist Award (2014). Teaching activities focus on Fluid Mechanics (CHEMENG 2O04) and Industrial Separation Processes (CHEMENG 4M03).
Lilyan Fulginiti is a Roy Frederick Professor of Agricultural Economics at the University of Nebraska-Lincoln. Her work focuses on agricultural productivity, climate change impacts, irrigation policies, and sustainable resource management, particularly in regions like the Ogallala Aquifer and South America. Research areas include agricultural economics, environmental economics, and climate policy. Her recent publications address gene-edited crops, carbon farming, and productivity disparities linked to trade and climate. Her scholarly output spans topics such as irrigation efficiency, biofuel economics, and conflict impacts on agriculture, reflecting a commitment to integrating economic theory with pressing environmental challenges. While no specific awards or student advisement details are listed, her extensive publication record underscores her contributions to advancing sustainable agricultural practices and policy analysis.
Nicole Novielli, Ph.D., is Associate Professor at the University of Bari “A. Moro” , Italy, where she conducts research on affective computing applied to software engineering and human-computer interaction. She leads the Collaborative Development Group and coordinates national projects investigating emotions in software teams, AI quality and IoT ecosystems. Education: Ph.D. in Computer Science, University of Bari, 2010 – thesis on “Lexical Semantics of Dialogue Acts” M.Sc. in Computer Science (Knowledge & Software Engineering), University of Bari, 2006 – summa cum laude B.Sc. in Computer Science, University of Bari, 2004 – summa cum laude Visiting researcher at USC-ICT, University of Aberdeen, FBK-irst (Trento) Research interests revolve around recognizing and exploiting affective and cognitive states in computer-mediated cooperative work. She studies sentiment and emotion mining in developers’ textual communication, multimodal emotion recognition via low-cost biometric sensors, and natural-language dialogue simulation for intelligent interfaces. Her work couples software engineering with natural language processing , social media analytics and human-computer interaction . Recent articles (2021-2025) reveal a clear trend: integrating deep learning and large language models into software engineering tasks—automated issue labelling, sentiment classification, technical-debt detection—while validating these techniques through rigorous empirical studies and biometric experiments . A parallel stream explores developer experience , measuring how emotions and cognitive load influence productivity, code quality and collaboration. Scientific awards include the 2020 Apex Award for Publication Excellence , multiple Distinguished Reviewer Awards at flagship venues (ESEC/FSE, ICSME, MSR), the Best Paper Award SANER 2019 and the Best Student Paper Award ACII 2009 . She currently teaches “Sentiment Analysis” in the Data-Science MSc and “Computer Networks” in the ITPS programme. She has advised numerous B.Sc., M.Sc. and PhD projects and is PI or Co-PI of four ongoing grants: EmoQuest (SIR), EMPATHY (PRIN), FAIR-Spoke 6 (PnRR), and QualAI (PRIN 2022). Dr. Novielli serves on the editorial boards of Empirical Software Engineering and Journal of Systems and Software , has guest-edited special issues on affect awareness in SE, and has chaired tracks at ICSE, SANER, MSR, ICSME and SSBSE. She co-leads the Collaborative Development Group and actively releases datasets and open-source tools for the community.
Jonathan Cullen is Professor of Sustainable Engineering at the University of Cambridge and President of Fitzwilliam College, specializing in resource efficiency and decarbonization through top-down analysis of industrial material and energy systems. His work bridges academic research with industry applications across energy-intensive sectors. Education: Bachelor's in Chemical and Process Engineering, University of Canterbury, New Zealand MPhil in Engineering for Sustainable Development, University of Cambridge PhD in Engineering Fundamentals of Energy Efficiency, University of Cambridge His research develops metrics for quantifying energy and material consequences of production systems, focusing on circular economy implementation, minimum energy requirements, and zero-carbon transition pathways. Key applications target cement, steel, plastics, and petrochemicals where he pioneers methods like exergetic analysis and material flow accounting to expose carbon lock-ins and circularity opportunities. Recent publications reveal three dominant trends: (1) Frameworks for theoretical minimum energy requirements across industrial processes, (2) Geopolitical analysis of critical mineral flows and ownership structures, and (3) Circular economy metrics for plastics and construction materials. These consistently employ system-scale modeling validated through industry partnerships. Research Funding: Lead: C-THRU ($4M, VKRF) - carbon clarity in petrochemical supply chains Co-I: UK FIRES (£5.2M, EPSRC) - industrial decarbonization program Co-I: CirPlas (£1.25M, UKRI) - plastic waste elimination 7+ projects (EPSRC, Innovate UK, Horizon 2020) Academic Leadership: Teaching: Energy Systems and Policy (MPhil in Energy Technologies) Undergraduate supervision in Materials/Mathematics Graduate Tutor at Fitzwilliam College IPCC AR6 Lead Author (Industry Chapter) He directs the Resource Efficiency Collective, which develops open-source tools like Mat-dp for material demand projections and Starter Data Kits for energy planning. Current work focuses on scaling circular business models for construction retrofitting and quantifying geopolitical risks in critical mineral supply chains.
Scott Fraundorf is an Associate Professor in the Department of Psychology at the University of Pittsburgh , where he leads the MAPLE (Memory And Psycholinguistics in Learning & Education) Lab . He combines cognitive science and data science to study human behavior prediction, educational program evaluation, and psycholinguistics . His research focuses on student learning and metacognition language processing and educational technology interventions statistical modeling using regression , machine learning , and mixed-effects models as well as open-source tool development for cognitive science. Key technical skills include Python , R , and SQL programming, with 3 patents for intelligent tutoring systems in English grammar. He has mentored over 70 graduate students and faculty in quantitative methods.
Thomas Streinz serves as Full-time Professor - Joint Chair at the European University Institute's Department of Law and Robert Schuman Centre for Advanced Studies since January 2025. His interdisciplinary work bridges law, technology studies, and global governance frameworks. His research focuses on digital governance and global law, particularly examining regulatory frameworks for data economies, digital infrastructures, and the interplay between European law and global tech regulation. Key projects investigate software regulation, AI/cloud computing governance, and infrastructure-as-regulation mechanisms. He integrates perspectives from science and technology studies, infrastructure studies, and critical data studies to analyze socio-techno-legal systems across public/private and jurisdictional boundaries. Professor Streinz previously served as Adjunct Professor of Law at New York University School of Law, where he directed the Guarini Global Law and Tech initiative and participated in MegaReg/InfraReg research projects through NYU's Institute for International Law and Justice. Supervises PhD candidates on global law and technology topics Active in International Thinking and Planetary Futures research cluster Administrative support provided by Alice Pineschi
Ben Martin is Professor of Science and Technology Policy Studies at the University of Sussex Business School, leading SPRU (Science Policy Research Unit). With 40+ years of research experience, he specializes in science policy, innovation studies, and research evaluation. His work spans foresight methodologies, university-industry collaboration, and research integrity. Recent publications explore evolutionary economics, academic publishing ethics, and research misconduct frameworks. Key contributions include developing techniques for evaluating scientific performance, analyzing technological spin-offs, and pioneering studies on foresight. He has supervised 30+ doctoral students and secured funding from EU, ESRC, and DFID for projects like NETGENESIS and PRIME.