Aleksandra Pomiecko is a Lecturer in Modern History at King's College London, specializing in Eastern European and Soviet history. She has held teaching positions at the University of St Andrews, the University of Manitoba, and the University of Toronto, and was a postdoctoral fellow at the Mandel Center for Advanced Holocaust Studies. PhD, University of Toronto MA, Uniwersytet Jagielloński Her research focuses on war and violence in twentieth-century Eastern Europe, particularly paramilitary activity, partisan movements, and local experiences of conflict. She explores topics such as Belarusian nationalism, post-war insurgency, and the role of religious institutions during the Holocaust. Recent publications examine paramilitarism in Polish borderlands, Soviet nation-building policies, and religious resistance in wartime Poland. Her work contributes to understanding the longue durée of paramilitary dynamics and their global implications. Scientific awards: Postdoctoral Fellowship at the Mandel Center for Advanced Holocaust Studies
Filip Biljecki is an Assistant Professor jointly appointed at the Department of Architecture within the College of Design and Engineering and the Department of Real Estate at the NUS Business School, National University of Singapore. He is the founder and principal investigator of the NUS Urban Analytics Lab and was awarded the prestigious NUS Presidential Young Professorship in 2020. With over 150 peer-reviewed publications, his research bridges geomatic engineering, geospatial technologies, and urban data science to advance digital twins and data-driven urban planning. Dr. Biljecki's educational background includes: PhD in 3D GIS (cum laude), Delft University of Technology, Netherlands (2017) MSc in Geomatics, Delft University of Technology, Netherlands (2010) BSc in Geodesy and Geoinformatics, University of Zagreb, Croatia (2008) His research interests focus on emerging urban data sources, particularly urban imagery, and their application in 3D city modeling, digital twins, and GeoAI. He explores how crowdsourcing and open science can inform cutting-edge techniques for urban sensing and analytics at city-scale. His work significantly contributes to establishing smart cities through innovative methods that integrate recent advancements in computer science, geomatics, and urban data science. Analysis of his recent publications reveals a strong focus on street view imagery applications for urban analytics, digital twin development, and geospatial AI. His research spans multiple domains including urban morphology, environmental assessment, public health applications, and urban comfort analysis. The interdisciplinary nature of his work is evident in collaborations with researchers from diverse fields, producing impactful studies that address complex urban challenges through innovative methodological approaches. His notable scientific achievements include: Annual Teaching Excellence Award (ATEA), 2025 College Educator Award AY2023/2024, 2025 Urban Informatics Paper of the Year Award, 2023 Top 2% scientists worldwide (Stanford University), 2021 Presidential Young Professorship (NUS), 2020 As an educator, Dr. Biljecki has supervised dozens of students leading to publications in leading journals and placements at top universities and organizations. He has delivered talks at over 120 universities and organizations worldwide including MIT, Stanford, Harvard, and ETH Zurich. His research is supported through various grants and affiliations including his role as Principal Investigator at the Future Cities Lab Global at the Singapore-ETH Centre. The NUS Urban Analytics Lab, which he established, brings together scholars from diverse disciplines to drive research on making cities smarter and more data-driven. The lab has developed innovative tools like ZenSVI for street view imagery analysis and has produced influential research on urban digital twins, urban morphology, and GeoAI applications. Through his leadership, the lab continues to pioneer methods that advance data-driven urban planning and smart city development.
David I. August is a Professor of Computer Science at Princeton University, affiliated with the Department of Electrical Engineering. He earned his Ph.D. from the University of Illinois at Urbana-Champaign in 2000. His research focuses on compilers and computer architecture, emphasizing synergistic design between compilers and microarchitecture. He leads the Liberty Research Group, which explores topics such as automatic parallelization, memory profiling, and speculative execution. August joined Princeton in 1999 as a lecturer, advancing to full professor in 2012. He has served as program chair for MICRO 2009 and on committees for ISCA, PLDI, and ASPLOS. His notable accolades include the IEEE Fellow designation, Best Paper Awards at PLDI and CGO, and teaching awards from Princeton's School of Engineering. His work spans compiler optimizations, hardware-software co-design, and security architectures like TrustGuard. Recent research includes GPU scheduling (GhOST), memory profiling frameworks (PROMPT), and instruction prefetching (PDIP). He advises over 20 graduate students, many now leading roles at tech companies and academia. August teaches courses such as COS-126 (Intro to CS), COS-375 (Computer Architecture), and graduate seminars. His projects often bridge theory and practice, with tools like NOELLE and Liberty Research Group initiatives advancing compiler infrastructure and parallelism extraction.
Yang (Gilbert) Ye is an Assistant Professor in the Department of Civil and Environmental Engineering at Northeastern University, joining in January 2025. His research focuses on human-AI/robot teaming, automation in engineering, and assistive technologies, with a particular emphasis on human-centric robotics and sensorimotor processes. He holds a PhD in Civil Engineering from the University of Florida (2024), advised by Dr. Eric Jing Du. **Affiliations**: Member of ASCE, IEEE, and HFES. His work integrates VR/AR, robotics (e.g., drones, exoskeletons), and AI to enhance civil engineering workflows and workforce training. He leads the Ye Lab, actively recruiting PhD students and postdocs with coding experience (Python/C++/C#) and backgrounds in engineering or computer science. **Key Research Themes**: Human-robot interaction, construction automation, exoskeleton training, and delayed feedback mitigation in teleoperation. Over 20 peer-reviewed publications in journals like ASCE JoCEN, IEEE Access, and Advanced Engineering Informatics. **Lab Opportunities**: PhD/postdoc applicants require strong academic records (GPA ≥3.5) and coding skills. Undergrad/master students can apply for thesis/research roles. Funding covers tuition, insurance, and stipends.
Stephen M. Hart is a Professor of Latin American Film, Literature and Culture at University College London (UCL), affiliated with the School of European Languages, Culture and Society (SELCS) and the Department of Spanish, Portuguese and Latin American Studies. He is a General Editor at Tamesis Publishers and founder-director of the Centre of César Vallejo Studies at UCL. Education: BA (1980), MA (1984), PhD (1985) from University of Cambridge Academic Career: Lecturer at Westfield College (1984-1990), Associate/Full Professor at University of Kentucky (1991-1998), Senior Lecturer/Reader at UCL (1998-present) Specializing in Latin American literature, film, and culture, Hart has published extensively on César Vallejo and Santa Rosa de Lima, including critical editions of their works. His research spans literary theory, art history, and East-West relations, with a focus on documentary film-making and magical realism as a framework for understanding post-truth narratives. Recent publications address colonial sainthood processes, poetic modernism, and China-Latin America connections. He has directed documentary projects in Cuba since 2006 and received honors including the Order of Merit from the Peruvian Government and Honorary Doctorates from Peruvian institutions. Key Awards: Order of Merit for Distinguished Services (Peruvian Government, 2004), Honorary Doctorate (San Marcos University, 2004), Corresponding Member of Academia Peruana de la Lengua (2014) Leadership Roles: Director of UCL's ESRC DTC (2014), Director of Documentary Film-Making Summer School (Cuba, 2006-present) Teaching: Undergraduate courses on Latin American supernaturalism and cultural dilemmas; MA documentary film-making courses
Libby Gerard is an Associate Adjunct Research Professor at the University of California, Berkeley School of Education and a Research Director for the Technology-Enhanced Learning in Science (TELS) Center. Her work focuses on leveraging innovative technologies to enhance science education through student idea capture, automated assessment, and teacher professional development. Doctorate in Educational Leadership (EdD), Mills College (2008) Bachelor’s in English Literature and Philosophy, Emory University (2000) Her research emphasizes: Automated scoring of student essays using NLP to improve science explanations Real-time instructional customization using embedded assessment data Technology-driven professional development for teachers and principals Social justice integration in science pedagogy Collaborative revision frameworks for inquiry-based learning K-12 education adaptation during the pandemic Recent publications highlight trends in educational technology for science learning, with a focus on NLP applications, interactive inquiry modules, and equitable teaching practices. She has authored studies in journals like Science , Review of Educational Research , and Computers & Education , often exploring how automated systems can enhance teacher-student dynamics. Scientific Awards : Best Paper Award at the AI4EDU Workshop (AAAI Conference, 2020) Libby leads funded projects such as: TIPS (NSF, 2021-2025): NLP for science education ARISE (Hewlett Foundation, 2020-2023): Anti-racism in science education STRIDES (NSF, 2018-2022): Responsive instruction for science teachers PLANS (NSF, 2015-2020): Automated learning support systems She contributes to teacher training through courses like Research Methods for Science Teachers and Apprentice Teaching in Science , emphasizing data-driven pedagogy and inquiry-based instruction.
Kimberly Stratton is an Associate Professor in the Department of Religion at Carleton University within the College of the Humanities. She holds a Ph.D. in the History of Religions in Late Antiquity from Columbia University (2002), following degrees from Barnard College and Harvard University. Her research focuses on religion, violence, and social identity in antiquity, ancient magic, and gender studies. She has authored Naming the Witch: Magic, Ideology, and Stereotype in the Ancient World (2007), which won the F. W. Beare Book Award, and co-edited volumes such as Daughters of Hecate: Women and Magic in Antiquity (2014). Her work examines intersections between religion, power, and identity in Greco-Roman, early Christian, and Rabbinic Jewish contexts. Recent projects include exploring violence and Exodus narratives in early religious identity formation, as seen in her 2017 article in History of Religions . She has presented widely on topics like Roman imperialism and apocalyptic literature at venues such as the Society of Biblical Literature. Her research highlights how ancient societies used religious discourse to construct social boundaries and authority. Awards include recognition from students and scholarly societies for her impactful contributions. Education: B.A. Barnard College (1991), M.T.S. Harvard (1995), Ph.D. Columbia (2002) Affiliations: Canadian Society of Biblical Studies, American Academy of Religion Office: 2A47 Paterson Hall | Email: kim.stratton@carleton.ca
Mathias Niepert is a Professor at the Institute for Artificial Intelligence within the Faculty of Computer Science, Electrical Engineering and Information Technology at the University of Stuttgart. His research focuses on advancing machine learning techniques with applications in scientific computing, graph neural networks, and medical imaging. He is particularly known for contributions to physics-informed neural networks, equivariant models, and graph learning frameworks. Key research areas include: Scientific Machine Learning for PDEs and molecular modeling Graph neural networks and their theoretical limitations Medical vision-language models and multimodal learning Efficient neural network architectures (transformers, FNOs) Domain knowledge integration in deep learning His work often bridges theoretical foundations with practical applications, as evidenced by extensive publications (2018–2025) on topics like adaptive message passing, equivariant networks, and medical imaging systems. He has contributed to benchmark development through initiatives like PDEBench and pioneered methods for equivariant diffusion models and molecular representation learning. His current projects emphasize: Improving generalization in Fourier Neural Operators Addressing oversmoothing in graph networks Combining physics principles with neural architectures Medical AI applications through multimodal fusion
Jalaa Hoblos is an Associate Professor of Practice in the Department of Computer Science at Stony Brook University, part of the College of Engineering and Applied Sciences. She holds a B.S. from the Lebanese University in Beirut, Lebanon, and an M.S. and Ph.D. in Computer Science from Kent State University. Prior to Stony Brook, she served as an Assistant Professor at Penn State Behrend, a Visiting Assistant Professor at Hiram College, and adjunct faculty at Kent State University and the University of Akron. Her primary roles include teaching and research. Her research focuses on Data Quality Analysis, Cloud Computing (particularly load balancing and security), Wireless Networks Security, and Statistical Mathematics. She has explored topics such as fairness and throughput in multi-hop wireless networks, malicious behavior detection in clouds, and protocol modifications like the adaptive 802.11 MAC. Her work integrates statistical methodologies with network optimization and security challenges. Recent publications emphasize anomaly detection in time-series data and fairness-enhancing protocols. She has also applied techniques like Latent Semantic Analysis to educational technology. No scientific awards are explicitly mentioned in the texts. While no advising or grant details are provided, her teaching includes courses like CSE 114 (OOP), CSE 101 (Principles), CSE 310 (Computer Networks), and security-focused courses such as ISE 331 (Fundamentals of Computer Security). She has maintained consistent academic engagement across institutions and disciplines.
Prof. Margret Keuper is a Professor of Machine Learning at the University of Mannheim's School of Business Informatics and Mathematics, leading the Data and Web Science Group. She is also affiliated with the Max-Planck-Institute for Informatics and ELLIS (fellow since 2024). Her research focuses on robust deep learning, neural architecture search, and computer vision tasks like motion segmentation and adversarial defense. She holds a PhD from the University of Freiburg and previously held positions at the University of Siegen and the University of Mannheim. Her work spans projects funded by DFG and BMBF, including Climate Visions for social media analysis and TrackOpt for motion tracking. She teaches courses on computer vision, generative models, and reinforcement learning. She actively serves on program committees for top conferences like CVPR, ECCV, and NeurIPS, and is an associate editor for IEEE TPAMI and JAIR. Education: PhD in Computer Science from University of Freiburg (advisor: Thomas Brox) Research Projects: Learning to Sense (DFG), Climate Visions (BMBF), TrackOpt (BMBF) Key Roles: Head of Mannheim Master in Data Science Examination Board, Member of MSc Business Informatics Board Her research emphasizes robustness in AI systems, with contributions to adversarial attacks, domain generalization, and efficient solvers for large-scale problems. She advises over 15 PhD students across academic and industry partnerships.
Suvi Saarikallio is a Professor of Music Education at the University of Jyväskylä, Finland , affiliated with the Faculty of Humanities and Social Sciences and the Department of Music, Art and Culture Studies . She leads interdisciplinary research bridging music psychology, education, and therapy, with a focus on youth development, emotion regulation, and well-being. Research Groups: Centre of Excellence in Music, Mind, Body and Brain (2022-2029), Musiconnect (2022-2027) Key Projects: Music and You, Stress & music listening, MPACT (Music and Sports), Music and Cross-modal Associations, SOSUS (Social Sustainability for Children) Research Trends: Her recent publications explore music's role in emotional regulation, cross-modal perception, health outcomes, and educational applications. Themes include AI's impact on music evaluation, rhythm's connection to cognitive skills, and music's influence on stress and social-emotional development. Contact: suvi.saarikallio@jyu.fi
James T. Hamilton is the Vice Provost for Undergraduate Education and Hearst Professor of Communication at Stanford University, where he also directs the Stanford Journalism Program. He previously taught at Duke University’s Sanford School of Public Policy and led the De Witt Wallace Center for Media and Democracy. His academic career spans over three decades, with a focus on media economics, investigative journalism, and environmental policy. Hamilton holds a B.A. (summa cum laude) and Ph.D. in Economics from Harvard University. His research explores how markets shape news content, the economics of investigative reporting, and the societal impact of information access. He co-founded the Stanford Computational Journalism Lab and is a Senior Fellow at the Stanford Institute for Economic Policy Research. His work emphasizes computational tools to enhance journalism’s accountability role, including automated fact-checking and data-driven story discovery. Key contributions include groundbreaking books like Democracy's Detectives (2016) and All the News That’s Fit to Sell (2004), which analyze media markets and transparency policies. Scientific Awards: David N Kershaw Award, Goldsmith Book Prize (twice), Frank Luther Mott Research Award (twice), Tankard Book Award Teaching Honors: Allyn Young Prize, Trinity College Distinguished Teaching Award, Susan Tifft Mentoring Award His current research addresses digital inequality, the psychological effects of online financial ads, and algorithmic transparency in journalism. He advises on media innovation through affiliations with the Brown Institute for Media Innovation and the JSK Fellowships Board.
Bradford S. Bell is the William J. Conaty Professor in Strategic Human Resources and Director of the Center for Advanced Human Resource Studies at Cornell University's ILR School. His academic career spans roles as editor of Personnel Psychology and fellowships with the Society for Industrial and Organizational Psychology and American Psychological Association. He holds a Ph.D. in Industrial and Organizational Psychology from Michigan State University. Education: B.A. Psychology, University of Maryland (College Park) M.A. and Ph.D. Industrial and Organizational Psychology, Michigan State University Research Focus: Dr. Bell's work centers on training/development, team dynamics, virtual work, and technology's impact on organizations. He has published widely in journals like Journal of Applied Psychology and Academy of Management Learning & Education , with over 150+ publications. His research emphasizes practical applications in workplace learning systems and team effectiveness. Awards: Early Career Achievement Award (Academy of Management HR Division, 2008) Professional Contributions: Advises organizations globally on HR strategy through the Center for Advanced Human Resource Studies. His consulting spans banking, manufacturing, and public sectors. Active in professional development, he teaches courses on HR management, training, and work teams.
Filipa Melo Lopes is a Lecturer in Social and Political Philosophy at the University of Edinburgh, affiliated with the School of Philosophy, Psychology and Language Sciences. She currently directs the Scottish Feminist Philosophy Network. Her research focuses on feminist philosophy, social theory, sexual ethics, and the work of Simone de Beauvoir, with recent attention to incel extremism, fashion ethics, and gender-based violence. Education: B.A. from Simon Fraser University (Canada), Ph.D. from University of Michigan (USA). Teaching includes undergraduate courses like 'Advanced Topics in Feminist Philosophy: Gender and Beauty' and PhD supervision in feminist ethics and political theory. She has supervised several doctoral students, including Lilith W. Lee (now Assistant Professor at Vrije Universiteit Amsterdam). Publications analyze themes such as misogynistic dehumanization, feminist fashion ethics, and Beauvoirian critiques of incel ideology. Her work bridges academic philosophy with public discourse on topics like sugar dating and incel violence. Active in feminist knowledge networks, she also writes for broader audiences on fashion, misogyny, and cultural criticism.
WonSook Lee is a tenured Full Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa’s Faculty of Engineering. Her expertise spans medical imaging, machine/deep learning, computer graphics, and computer vision. She earned her Ph.D. in Computer Science from the University of Geneva (Switzerland) and holds degrees from POSTECH (Korea) and NUS (Singapore). Before academia, she worked at Korea Telecom, Samsung Advanced Institute of Technology, and Eyematic Interfaces Inc. (USA). Her research focuses on applications such as virtual/augmented reality, MRI/CT/Ultrasound analysis, and 3D mesh modeling. She has authored over 130 publications, including 30+ journal papers, and serves on conference committees and editorial boards. Lee has secured major grants (NSERC, CFI, ORF) as Principal Investigator and contributed to global initiatives like South Korea’s National Research Foundation. Her lab explores cutting-edge techniques in medical imaging, AI-driven object detection, and multimodal systems. Notable projects include adversarial perturbation analysis for model robustness, cross-domain GANs for semantic segmentation, and real-time ultrasound-enhanced pronunciation training. She actively promotes interdisciplinary research in healthcare technology and autonomous systems.
