Carolyn Rouse is the Ritter Professor of Anthropology at Princeton University and an HMEI Associated Faculty member in the Grand Challenges Program. Her work interrogates the intersections of race, religion, healthcare disparities, and development through ethnographic and visual anthropological methods. Research Interests: Development, medical anthropology, visual anthropology, resistance, critical race theory, consciousness, North America, Ghana, environmental humanities, and environmental policy/ethics. Key Affiliations: Department of Anthropology, Princeton University; Environmental Humanities and Environmental Policy and Ethics through HMEI Grand Challenges Program. Her research critically examines how evidence shapes narratives of social inequality, particularly in healthcare access, racial disparities, and international development. She authored Engaged Surrender , Uncertain Suffering , and Televised Redemption , and created the Ethnographic Data Visualization Lab (VizE Lab) in 2016 to bridge biological and social scientific data. Recent publications explore necropolitics, liberal bias in the Trump era, and epistemological challenges in evidence-based policy. Her films include Chicks in White Satin (Academy Award-nominated), Purification to Prozac , and Listening as a Radical Act . Scientific Awards: 1995 American Anthropological Association Award for Excellence ( Tales from Arab Detroit ) Academy Award nomination for Chicks in White Satin
Prof. Dr. Andrea Sick is Professor of Cultural and Media History/Theory at the University of the Arts Bremen (HfK Bremen) where she leads the Digital Media study program. She founded the Binational Artistic PhD Program, collaborating with institutions including Leiden University, University of Groningen, and University of Gothenburg. Her research explores intersections between technology, art, and cultural production through both academic and curatorial work. Education includes studies in German Studies, Political Science, Cultural Studies, and Art History at Heidelberg, Bremen, and Hamburg universities, culminating in a 2001 PhD from Universität Hamburg on cartographic knowledge systems. She co-directs the art-science project thealit Frauen.Kultur.Labor , producing exhibitions, conferences, and publications. Research focuses span: Technological media's impact on artistic production Art-biology-information technology intersections Performance art history/theory Queer Studies frameworks Artistic research methodologies Generative AI in cultural analysis Her work critically examines how digital tools transform cultural documentation and archival practices. Recent projects include: Latent Museums (AI analysis of museum collections) The Dynamic Archive (ongoing digital archiving project) Re Capitulating.Queer (2024-2026 curatorial project) Administrative roles include: Dean of Art and Design (2012-2018) Co-Rector for Research & International Affairs (2018-2023) Lead of Binational Artistic PhD Program (since 2022) Awards include the Heinrich-Böll-Stiftung doctoral scholarship (1998-2001). She mentors 12+ PhD students in artistic research, including projects on sonic archaeology, queer archives, and decolonial practices.
John Finn serves as Associate Professor and Department Chair of the Department of Sociology, Social Work and Anthropology at Christopher Newport University's College of Arts and Sciences. He holds joint appointments with the Honors Program, Center for Crime Equity and Justice Research and Policy, and Center for Sustainability in Education. PhD in Geography, Arizona State University MA in Geography, University of Missouri BA in International Studies, University of Missouri Finn's research examines the socioeconomic, environmental, and health consequences of persistent racial segregation in the United States, with particular focus on Hampton Roads, Virginia and Latin American contexts including Cuba and Brazil. His work integrates urban geography, environmental justice, and human-environment interaction through field research methods. His 2024 solo exhibition 'Living Apart: Geography of Segregation in the 21st Century' at the Virginia Museum of Contemporary Art demonstrates his innovative approach to translating academic research into public engagement. Finn's recent publications reveal strong thematic focus on urban renewal impacts, environmental justice mapping, and Latin American geographies, with increasing emphasis on climate gentrification and spatial epidemiology. 2024 SCHEV Outstanding Faculty Award (Virginia's highest faculty honor) 2021 Alumni Society Award for Teaching and Mentoring 2020 Faculty Excellence Award in Scholarship Class of 2013 Faculty Development Award (2019) Finn has secured over $200,000 in research funding and delivered more than 100 invited lectures across North America, Latin America, and Europe. His work bridges academic research and practical applications through partnerships with medical schools, planning associations, and environmental organizations. He maintains active research teams focused on mapping segregation patterns and analyzing environmental health disparities in coastal Virginia.
Dr. Arpan Man Sainju is an Assistant Professor and Internship Coordinator in the Department of Computer Science at Middle Tennessee State University (MTSU). He holds a PhD (2021) and MS (2020) from the University of Alabama, and a B.E. (2011) from Tribhuvan University. His research focuses on spatial big data analytics, spatiotemporal data mining, and GIS applications in environmental modeling, disaster management, and geospatial science. He develops innovative algorithms for Earth imagery segmentation, flood inundation mapping, and physics-aware machine learning models. Education: PhD in Computer Science, University of Alabama (2021) MS in Computer Science, University of Alabama (2020) B.E. in Computer Science, Tribhuvan University (2011) Key research interests include deep learning for geospatial tasks, semi-supervised learning with limited labels, and parallel computing for big spatial data. His work bridges computer science and environmental science, addressing challenges in hydrology, urban safety, and disaster response. He has published extensively in top journals like ACM TIST, IEEE TKDE, and Environmental Modelling & Software, focusing on applications like flood modeling, road safety analysis, and 3D shape analysis. Dr. Sainju collaborates on interdisciplinary projects involving physics-guided models, hidden Markov structures, and GPU-accelerated algorithms. His research has been applied to real-world scenarios such as hurricane flood analysis and malware detection through Windows log analysis.
Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.
Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.
Kris Baetens is a Professor in the Department of Psychology Brain, Body and Cognition at Vrije Universiteit Brussel (VUB). His research focuses on the neural mechanisms underlying social cognition, mentalization, and inhibitory control, particularly exploring the role of the cerebellum and prefrontal cortex in these processes. He employs techniques such as transcranial direct current stimulation (tDCS), EEG, and fMRI to investigate cognitive and clinical phenomena. Leading projects like ANI423 (neural correlates of inhibitory control in adolescents) and FWOAL1160 (cerebellum's role in social cognition). Recipient of the EUTOPIA Young Leaders Academy fellowship (2024-2026). Active collaborations in the PRISM network for mental health research. Key research interests include: - Cerebellar contributions to cognitive and social functions - Neurostimulation techniques for mental health interventions - Mentalizing processes in social action prediction - Personality and learning mechanisms His articles consistently analyze the interplay between neural structures like the cerebellum and behavioral outcomes in clinical and cognitive contexts. Recent work emphasizes applications of tDCS in treating alcohol use disorders and disordered eating, highlighting translational research in non-invasive brain stimulation. Advising/Grants: Supervises student research projects and manages grants from FWO and OZR agencies. Labs/Teams: Core member of the PRISM network and involved in the EUTOPIA fellowship initiative.
Maneesh Agrawala is the Forest Baskett Professor of Computer Science at Stanford University and Director of the Brown Institute for Media Innovation. His research spans computer graphics, human-computer interaction, and information visualization. Agrawala's lab develops computational tools for visual communication, investigating how design principles improve media effectiveness. Current projects include diffusion models for image and video generation, sketch-based interfaces, and visualization tools for scriptwriting. His team creates systems that enable new forms of content creation and analysis. His publications demonstrate consistent innovation in visual computing, with recent advances in controllable generative models, video understanding, and visualization design. Agrawala has received numerous honors including the MacArthur Fellowship and ACM Fellowship for his contributions to visual computing.
Dr. Teresa Wang is a Senior Lecturer in Data Science at Monash University's Faculty of Information Technology, specializing in entity/user modeling, relational/structural machine learning, and graph/network analysis. She holds a Ph.D. from the University of Queensland and degrees from Nanjing University. Currently, she directs the Master of Data Science Program and teaches courses like FIT5201 Machine Learning. Her research focuses on social, e-commerce, and health data modeling, with notable projects including the Knowledge Enriched Approach for Effective Personalization (2025–2027) and collaborations on AI in Mental Health and Site Safety. Dr. Wang has co-authored over 59 publications, emphasizing areas like ontology matching and multimodal data analysis. She actively supervises PhD students and contributes to initiatives like the CSIRO Next Generation Graduates Program for clean energy and sustainability. Education: Ph.D. in Computer Science (2017), University of Queensland Master of Computer Science (2013), Nanjing University Bachelor of Software Engineering (2010), Nanjing University Research Interests: Entity modeling, spatio-temporal data analysis, graph mining, recommender systems, and health/medical records mining. She explores applications in social media, e-commerce, and healthcare sectors. Projects: "Knowledge Enriched Approach for Effective Personalization" (2025–2027) "AI for Clean Energy and Sustainability" (2023–2027) "CSIRO Next Generation Graduates Program: AI in Mental Health" (2023–2027) "Large-scale multimodal knowledge management" (2022–2025) Grants & Collaborations: Engaged with CSIRO, Crank Group, and Pola Practice Pty Ltd. Her work aligns with UN SDGs in education and sustainable energy systems. Labs/Teams: Part of the Monash Energy Institute and Monash Data Futures Institute, contributing to interdisciplinary AI and energy research.
Junier Oliva is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill and Lead Faculty of the Master of Applied Data Science program. His research focuses on machine learning, artificial intelligence, and nonparametric statistics, particularly in high-dimensional density estimation, sequential modeling, and learning from complex/structured data. He holds a B.S., M.S., and Ph.D. in Computer Science from Carnegie Mellon University, with prior industry experience at Yahoo! and Uber ATG. Research Interests: Machine learning, artificial intelligence, nonparametric statistics, deep learning, statistical data mining, signal processing, kernel methods, and scalability. His work bridges machine and human learning via collective approaches, emphasizing simple yet flexible models for massive datasets. Awards/Grants: $592K AIM-AHEAD/NIH Grant for Human+AI Collaboration $594K NSF Grant for Scientific Discovery $500K NSF Grant for 'Machine Detectives' Project ACM BCB Best Paper Award (2022) for transparent single-cell classification work Labs/Teams: Director of the LUPA Lab, which develops machine learning techniques for holistic data understanding across domains like healthcare, earth science, and computer vision.
Irene Pañeda Fernández is a Research Fellow at the Department of Migration, Integration, and Transnationalization at the WZB Berlin Social Science Center. She coordinates the TRANSMIT project, investigating migration aspirations and decisions in West Africa. Her research focuses on inequality and migration, exploring factors influencing migration decisions and attitudes toward immigrants/refugees. She holds a Ph.D. in Social and Political Sciences from the European University Institute (2022). Her research areas include migration studies, social inequality, climate change impacts on migration, welfare state analysis, and social science methodologies. Her recent work examines how climate disasters affect migration intentions in West Africa and the role of teacher bias in education systems. Her studies combine mixed-methods approaches, including factorial experiments and large-scale surveys. Key contributions include analyzing climate-induced migration patterns, educational discrimination mechanisms, and disaster-driven redistributive preferences. Current projects aim to bridge migration theory with policy-relevant insights, particularly in transnational contexts. She collaborates closely with international teams and institutions focused on migration and climate change intersections. Her work is methodologically rigorous, emphasizing policy-oriented outcomes.
Goran Avlijaš is a researcher affiliated with Singidunum University in Belgrade, specializing in project management, operations research, and retail logistics. He holds a Doctorate in Engineering Management (2011–2016) from Singidunum University, a Master’s in Project Management (2008–2009) from the Faculty of Organizational Sciences, and a Bachelor’s in Management (2003–2007) from the same institution. His research focuses on optimizing project schedules through methods like Earned Value Management and Monte Carlo Simulation, analyzing supply chain efficiency, and exploring gig economy impacts on well-being in Balkan countries. Key research areas include: Project Management Innovation: Developing risk analysis tools (e.g., Event Chain Methodology) and applying earned value metrics to construction projects. Retail Operations: Investigating automated replenishment systems and inventory management challenges in retail environments. Social-Economic Dynamics: Studying gig economy effects on workforce well-being and regulatory impacts on entrepreneurship. His work spans 30+ peer-reviewed articles and conference papers, including contributions to Management , Sustainability , and Frontiers in Psychology . He co-authored textbooks like Project Management and Entrepreneurship for Singidunum University’s curriculum. Active in academic events such as Sinteza and FINIZ conferences, he bridges theoretical research with practical industry applications.
Dr. Timothy Fraser is a Computational Social Scientist serving as Ezra Systems Research Associate in Cornell University's Systems Engineering Program and Coordinator for the Center for Transportation, Environment, & Community Health (CTECH). Holding a PhD in Political Science from Northeastern University (2022), he focuses on climate change adaptation, disaster resilience, and energy policy using big data analytics, GIS, and AI. His work bridges computational methods with societal challenges, emphasizing community engagement and policy impact. Education: PhD in Political Science, Northeastern University (2022) MA in Political Science, Northeastern University BA in International and Global Studies, Middlebury College Research Interests: Fraser’s research integrates computational social science with environmental policy, exploring how social networks and governance structures influence cities' climate adaptation strategies. Key areas include renewable energy adoption, disaster evacuation dynamics, and pandemic response mechanisms. He employs mixed methods such as network analysis, statistical modeling, and fieldwork. Grants & Awards: Fulbright Fellowship (2016), Kyushu University Japan Foundation Doctoral Fellowship (2020) USDOT Multimillion Grant Administrator (2022-2023) Teaching & Mentorship: Fraser teaches statistical methods and research design at Cornell, advising over 30+ students in projects published in leading journals. He coordinates capstone teams and mentors researchers in data science and policy analysis. Labs & Projects: Leads the Climate Action in Transportation dashboard initiative (Gao Labs), developing tools for emissions visualization. Collaborates on UNDP social capital mapping projects in Mexico and Paraguay, applying spatial analysis techniques for vulnerable communities.
Dr. Imad El Haddad serves as Group Head of the Molecular Cluster and Particle Processes group at the Laboratory of Atmospheric Chemistry (LAC), part of the Center for Energy and Environmental Sciences at Paul Scherrer Institute (PSI), Switzerland, since 2018. Previously, he held positions as Tenured Scientist and Deputy Head (2018-2019), Senior Scientist in the Smog Chamber group (2015-2018), and Postdoctoral Fellow (2011-2015) at PSI. His research aims to quantify how anthropogenic emissions alter atmospheric pollutant composition and impact Earth's climate and public health through molecular-level analysis using advanced mass spectrometry techniques. His academic background includes: Ph.D. in Atmospheric Chemistry, University of Provence, Marseille (2007-2011) Master's in Environmental Sciences (with distinction, rank 1/9), University of Provence (2006-2007) Master's in General Chemistry (with distinction, rank 1/10), Saint-Joseph University of Beirut (2005-2006) Bachelor of Science in Chemistry (with distinction, rank 1/14), Saint-Joseph University of Beirut (2002-2005) El Haddad's work centers on molecular fingerprinting of atmospheric aerosols , utilizing mass spectrometry (GC/MS, HPLC/APCI-MS2, HPLC/ESI-MS2) to identify primary and secondary molecular markers. He conducts smog chamber experiments to characterize emissions from wood burning, traffic, and cooking processes, determining secondary organic aerosol potential and oxidation state evolution. His group also studies in-cloud aqueous-phase aging and collaborates with global modelers to link aerosol composition to climate forcing and health outcomes like oxidative stress. Recent publications (2025-2024) reveal three dominant trends: (1) rigorous molecular-scale analysis of secondary aerosol formation under varying humidity/temperature, (2) source apportionment breakthroughs in diverse regions (India, Europe, Arctic) using 14C and AMS data, and (3) quantification of health-relevant aerosol properties such as oxidative potential through DTT assays. High-resolution mass spectrometry is a consistent methodological thread across these studies. His scientific awards include: MENRT research fellowship from French ministry of research (2007-2010) Excellence Scholarship (top 1% student, University of Saint Joseph, 2005) Distinction Prize (best student, University of Saint Joseph, 2005) As Group Head, El Haddad oversees the Molecular Cluster and Particle Processes group's research direction and mentorship of junior scientists. While specific grant details are absent from the text, his leadership in multi-institutional publications (e.g., CERN CLOUD, iCUPE) implies active grant management and international collaboration. The group's work bridges laboratory simulations, field deployments, and health/climate modeling to address air pollution complexities. The Molecular Cluster and Particle Processes group develops cutting-edge online/offline mass spectrometers for 1 Hz-resolution atmospheric analysis. They deploy instruments in laboratory smog chamber experiments and global field studies, focusing on molecular marker identification, emission source characterization, and aging process quantification. Collaborations with biochemists and climate modelers extend their impact beyond pure aerosol physics into health risk assessment and policy-relevant climate science.
Dr. Rong-Hao Liang is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with both the Future Everyday Group (Department of Industrial Design) and the Signal Processing Systems Group (Department of Electrical Engineering). His research bridges intelligent sensing systems and user interface technology for ubiquitous computing and embodied human-computer interaction . He co-organized international ACM conferences (CHI, UIST, DIS) and has over 70 peer-reviewed publications and 10 patents. PhD in Computer Science (2014) and MSc in Electrical Engineering (2010) from National Taiwan University Founded GaussToys Inc. in 2015, focusing on magnetic-field sensors Cross-appointed to Electrical Engineering in 2021 His research explores intelligent sensing systems , tangible user interfaces , and physiological sensors for real-world challenges. Key trends in his work include ubiquitous health monitoring (e.g., preterm infants), wearable technology , and innovative interaction design . Articles like GaussBits and NFCStack demonstrate his focus on magnetic and RFID-based tangible systems . Scientific awards include the ACM CHI 2013 Best Paper Award , 2014 Honorable Mentions , and the ACM SIGGRAPH Asia 2012 Emerging Technologies Prize . He mentors passion-driven projects in user interface design and embedded systems , emphasizing technical rigor and creativity. His STRAP project (2020–2025) addresses heart disease prevention via big data and AI . Labs and teams include the Future Everyday Group and Signal Processing Systems Group , with collaborations across healthcare , education , and technology startups . His work aligns with UN Sustainable Development Goals , particularly good health and well-being .
