Raakel Plamper is a Doctoral Researcher at the Department of Education, University of Turku, with additional roles as Project Specialist in Geography and Development Specialist in Research Services. Her research focuses on higher education sociology, academic work dynamics, student roles in marketized systems, and university history. She teaches courses on social class and education, research methods, and multivariable analysis. Her work critically examines the marketization of universities, student-as-customer discourses, and managerialism in academic leadership. Key themes include tuition fee policies, institutional identity shifts, and equality in education systems. Recent publications analyze leadership rhetoric, writing retreats for researchers, and cross-country education strategies. Plamper actively contributes to interdisciplinary projects, such as the EU-funded Young Adulllt study on skill governance, and maintains a blog (Kas! blogi) discussing academic work and education policy. She holds an MA and is pursuing a PhD examining student roles in neoliberalized higher education.
Dr. Shufang Sun is an Assistant Professor in the Departments of Behavioral and Social Sciences and Psychiatry and Human Behavior at Brown University’s School of Public Health, and Associate Director of the Mindfulness Center. Her work focuses on understanding how stress, trauma, and systemic inequities contribute to health disparities, particularly among marginalized populations like LGBTQ+ individuals, youth, and communities affected by HIV. She develops mindfulness-based, technology-mediated interventions to promote mental health and reduce stigma, with a global focus including China, the Philippines, and Ukraine. Education: PhD in Counseling Psychology from the University of Wisconsin-Madison (2018). Research interests include mindfulness interventions, mHealth (mobile health), global mental health, HIV prevention, minority stress, and stigma reduction. Her work emphasizes community-engaged research and rigorous evidence synthesis through meta-analyses and systematic reviews. Current projects include interventions for displaced Ukrainians, suicide prevention in rural China, and HIV prevention among transgender women in the Philippines. Her interventions address topics like queer resilience, pandemic mental health, and health equity for vulnerable groups. Awards include the APA’s Barbara Smith Early Career Award and Brown University’s Early Career Research Achievement Award. Grants: Principal investigator on NIH-funded projects totaling over $7.5M, including a $3M R24 grant for mindfulness evidence synthesis and a $621K NIMH grant for school-based suicide prevention in China. Labs/Teams: Director of the Mindfulness for Health Equity Lab, collaborating with global researchers on stigma reduction and digital health innovations.
Professor Catherine Allerton is a faculty member in the Department of Anthropology at the London School of Economics and Political Science (LSE). She specializes in the materialities and mobilities of everyday life, with a focus on place, kinship, childhood, migration, and temporalities in island Southeast Asia. Her fieldwork spans a two-placed village in Flores, Indonesia, and Kota Kinabalu, Sabah, East Malaysia. Her research emphasizes interdisciplinary ethnographic methods, particularly involving child participants to challenge adult-centric approaches. She launched the 'Childhood in the Migrant City' exhibition using child-taken photographs from her ESRC-sponsored research. Current projects include exploring discordant temporalities between migration systems and childhood development, as well as completing a book manuscript on moral economies of belonging. Key research interests include the social and political dimensions of landscapes, the anthropology of children, and the impacts of legal status on marginalized youth. She teaches an LSE course on 'Children and Youth in Contemporary Ethnography' and actively supervises PhD students focusing on childhood, migration, citizenship, and Southeast Asian studies. Her work addresses exclusionary practices tied to race, religion, and legal frameworks in Malaysia and Indonesia. Languages spoken include Bahasa Manggarai, English, Indonesian, and Malay. No part-time status is mentioned, indicating full-time faculty commitment.
Michael S. Horn is a Professor of Learning Sciences and Computer Science at Northwestern University, serving as Program Coordinator for Learning Sciences. He holds a PhD in Computer Science from Tufts University and a ScB in Computer Science from Brown University. His research focuses on the intersection of human-computer interaction and learning, emphasizing the use of emerging technologies in museums, classrooms, and informal settings. Notable projects include multi-touch tabletops in natural history museums, tangible programming languages for early education, and the TIDAL Lab’s innovative exhibits like Build-a-Tree and DeepTree. Education background includes: PhD in Computer Science (Tufts University, 2009) MS in Computer Science (Tufts University, 2006) ScB in Computer Science (Brown University, 1997) Research interests span tangible interaction design, computational literacy, and museum-based learning. He has led projects such as the ‘Energy Monsters’ board game and the TunePad music-coding platform. His work integrates technology with pedagogical practices to foster collaborative and exploratory learning environments. Active collaborations include the Computer History Museum and the California Academy of Sciences. Advising contributions include mentoring doctoral students like Dr. Mmachi Obiorah and Pei-Yi. His lab, TIDAL, explores interactive technologies for education, with grants from NSF and industry partnerships. Recent articles highlight innovations in computational thinking integration, music-coding hybrid practices, and AI-driven qualitative analysis.
Roi Livne is an Associate Professor and Department Associate Chair in the Department of Sociology at the University of Michigan, within the College of Literature, Science, and the Arts. He holds a Ph.D. from the University of California-Berkeley (2016). His research focuses on the intersections of morality, culture, and economics within healthcare systems, particularly addressing end-of-life care, healthcare economics, and the sociological implications of modern medicine. Education: Ph.D. in Sociology from UC Berkeley (2016). Current courses include SOC 305-001: Introduction to Sociological Theory. Research interests include the sociology of morality, medical sociology, qualitative approaches, and the sociological analysis of science and technology. His seminal work, Values at the End of Life: The Logic of Palliative Care , examines the moral and economic tensions in end-of-life decision-making. Livne's recent projects explore the moral economy of healthcare pricing, sociological dimensions of the COVID-19 pandemic, and the concept of limits in modernity. His publications address topics such as the cultural and economic frameworks shaping healthcare decisions, the ethics of resource allocation, and the societal impact of pandemics. While no specific awards are listed, his work has contributed significantly to debates in medical sociology and economic theory. Advising and grants are not explicitly detailed here, though his roles suggest active mentorship and research leadership. His work is affiliated with the University of Michigan's Sociology Department, with office hours booked via https://www.wejoinin.com/livne.
Mats Danielsson is a Professor at KTH Royal Institute of Technology, leading the Medical Imaging research group within the Department of Particle Astrophysics and Medical Imaging. He has coordinated major projects like the ERC Advanced Grant for the Si3 project (starting 2024) and the EIC Pathfinder's 1MICRON project (starting 2025). His work focuses on advancing photon-counting detectors, X-ray technologies, and medical imaging systems. Notable recognitions include the 2024 KTH Innovation Award and the 2022 Hans Wigzell Science Prize. Danielsson has co-founded companies such as Sectra Mamea AB and C-RAD AB, and holds 135 patents with over 150 scientific publications. Education: MSc (1990) and PhD (1996) from KTH, followed by postdoctoral research at Lawrence Berkeley National Lab (1996–1998). He joined KTH in 1999, where he has held his current professorship since then. His research spans medical imaging, detector innovation, and radiation physics applications in healthcare. Research Interests: Development of high-resolution CT detectors, photon-counting technologies, compact X-ray sources, and AI-driven image processing. His recent work emphasizes minimizing radiation exposure while enhancing diagnostic precision through novel detector designs and machine learning algorithms. Key Projects: ERC Si3 project (3D detector for nuclear medicine), EIC 1MICRON (micrometer-scale imaging), and MedTechLabs collaboration with Karolinska Institutet. He has pioneered innovations such as MicroDose mammography and advanced photon-counting spectral CT systems. Awards: KTH Innovation Award (2024), Hans Wigzell Prize (2022), IVA membership (2017), Polhem finalist (2014), and INGVAR Award (2004). Advising & Grants: Over 150 scientific publications, 135 patents, and leadership in multi-institutional projects. Teaches courses on medical imaging and modern physics at KTH. Labs/Teams: Director of the Medical Imaging Group at KTH, co-founder of MedTechLabs, and collaborator across academia and industry in medical imaging innovation.
Klaus Hurrelmann is a Senior Professor of Public Health and Education at the Hertie School. Previously, he served as the founding dean of the first Faculty of Health Sciences in Germany at Bielefeld University and directed the SFB 227 research center for twelve years. His research emphasizes health and education policy, prevention strategies in childhood and adolescence, and the governance of healthcare systems. He has coordinated major studies such as the HBSC for the WHO and leads ongoing national studies on family and youth development. He studied at the University of Münster and the University of California, Berkeley, where he earned a doctorate focusing on educational systems and society. His work spans multidisciplinary collaborations, including leadership roles in longitudinal studies like the COPSY project analyzing youth mental health during the pandemic. Research interests include health literacy, systemic crisis response in education, and the interplay between societal trends and youth development. His recent publications highlight generational shifts in responsibility, pandemic impacts on mental health, and policy reforms in healthcare governance. He advises government agencies on youth policy and health system reforms, leveraging his expertise in evidence-based strategies. His current focus includes digital health literacy and the role of schools in addressing societal polarization.
Jeehwan Kim is an Associate Professor in Mechanical Engineering and Materials Science and Engineering at MIT. He joined the Mechanical Engineering faculty in 2015 and became a joint faculty member in DMSE in 2016. His research focuses on nanotechnology for computing/electronics, electronic/photonic devices, neuromorphic computing, and heterogeneous integration. He holds over 100 patents from IBM and has received awards like the Samsung Fellow (2022) and DARPA Director’s Award (2021). Education : BS (Hongik University), MS (Seoul National University), PhD (UCLA), all in Materials Science and Engineering. Research Interests : Kim’s group innovates in 2D materials, remote epitaxy, neuromorphic systems, and next-gen electronics. Key areas include monolithic 3D integration, bioelectronic devices, and energy-efficient semiconductors. His work bridges material physics with practical device applications. Awards : Samsung Fellow (2022) DARPA Director’s Award (2021) Young Faculty Award (2019) IBM Faculty Award (2016) IBM Master Inventor (2012) Labs/Teams : Jeehwan Kim Research Group at MIT, focusing on advanced material synthesis and device engineering. Active in cross-disciplinary projects involving AI and semiconductor innovation.
Dr. Li Wan is an Associate Professor in Urban Planning and Development at the Department of Land Economy, University of Cambridge, and a Fellow of Gonville and Caius College. He serves as Director for the MPhil in Planning, Growth and Regeneration and is a co-investigator of the Centre for Smart Infrastructure and Construction. Dr. Wan is also a Trustee of the IJURR Foundation and leads a research group focused on understanding urban land and transport development through applied modeling and data analytics. Dr. Wan holds a BArch, MPhil, and PhD from the University of Cambridge. Prior to joining Land Economy, he worked in Architecture and Engineering Departments, giving him a highly interdisciplinary perspective. His research focuses on spatial economic modeling of urban land use and transport systems, with recent interests including strategic planning at city/regional levels, impact studies of flexible working, micromobility, and electric vehicles. Dr. Wan's research group has produced significant work in city digital twins, as evidenced by his 2023 book Digital Twins for Smart Cities: Conceptualisation, challenges and practices . His publications span urban analytics, transport emissions, spatial equilibrium modeling, and economic geography, demonstrating the interdisciplinary nature of his work. Recent research trends show increasing focus on post-pandemic urban dynamics, digital governance, and sustainable mobility solutions. His research group has secured funding from initiatives like AI@Cam for projects examining how local authorities use AI for urban decision-making. Dr. Wan actively supervises PhD and MPhil students, with his group comprising researchers working on diverse urban topics from land-use efficiency to micromobility impacts. As an educator, Dr. Wan teaches courses including Tripos Paper 10 - The Built Environment, PGR01 - Urban and Environmental Planning, PGR02 - Urban and Housing Policy, PGR05 - Place-based Policy, and RM03 – Spatial Analysis and Modelling. His group has presented at major international conferences including CUPUM and ICML, reflecting his active engagement in the academic community.
Lawrence Goodridge is a Professor and Director of the Canadian Research Institute for Food Safety (CRIFS) at the University of Guelph's Ontario Agricultural College. He holds the Leung Family Professorship in Food Safety and leads research at the intersection of food safety, antibiotic resistance, and One Health principles. His work focuses on applying genomic technologies to study foodborne pathogens (E. coli, Salmonella, Listeria, Cronobacter) and leveraging wastewater surveillance for infectious disease outbreak prediction. Academic History: BSc Microbiology (University of Guelph, 1995), MSc Food Microbiology (2003), PhD Food Microbiology (2002), followed by post-doctoral training in Food Safety at the University of Georgia (2002). Joined CRIFS in 2003. Research Interests: Genomic analysis of pathogen emergence, wastewater-based epidemiology, bacteriophage applications, and consumer education strategies for food safety. His lab develops innovative methods for rapid pathogen detection in food systems and environmental samples. Articles Trends: Over 100 peer-reviewed publications emphasize genomic surveillance of foodborne pathogens and SARS-CoV-2, with a focus on wastewater sampling innovations. Recent work explores multi-modal data integration for public health forecasting and ethical data protection frameworks for surveillance programs. Awards: While no specific prizes are listed, his $50M+ research funding from Canadian/international sources underscores recognition of his impactful work. Grants support projects like phage-based sanitization and antimicrobial resistance tracking. Advising & Labs: Leads CRIFS laboratory operations and collaborates globally on food safety initiatives. His research has informed food industry guidelines and policy frameworks for mitigating pathogen risks in agricultural and environmental systems.
Professor Jean Burgess is a leading scholar in digital media studies, holding positions as Distinguished Professor of Digital Media at Queensland University of Technology (QUT) and Associate Director of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S). She is affiliated with the Digital Media Research Centre (DMRC) and School of Communication at QUT. Her work focuses on the social implications of digital platforms, algorithmic culture, and innovative digital methods. Education: PhD (Queensland University of Technology) M.Phil (University of Queensland) B. Arts (Hons) and B. Mus (Hons) (University of Queensland) Research Interests: Burgess explores digital media technologies' societal impacts, platform governance, and algorithmic systems. Her recent work includes studies on GenAI, Instagram's visual culture, and automated decision-making. She co-authored Everyday Data Cultures (2022) and contributes to platforms like The Conversation. Awards: Fellow, Australian Academy of the Humanities Member, ARC College of Experts Recipient of the Vice-Chancellor’s Award for Excellence Grants & Projects: Key projects include the ARC-funded ADM+S Centre, research on Instagram’s machine vision, and studies on algorithmic transparency in advertising. She collaborates with industries like Australia Post and the Australian Centre for the Moving Image. Labs/Teams: Leads the DMRC and ADM+S QUT node, fostering interdisciplinary research on digital media's role in society.
Jonathan P. Wong is a Senior Policy Researcher at the RAND Corporation and Professor of Policy Analysis at the RAND School of Public Policy. His work bridges academic research and defense policy, focusing on military strategy, acquisition, force planning, and the integration of emerging technologies into military operations. Education: Ph.D. and M.Phil. in Policy Analysis (Pardee RAND Graduate School), M.A. in Security Studies (Georgetown University), B.A. in Political Science (UC San Diego) Professional Experience: U.S. Marine Corps infantry officer (2001–2011), Consultant at Boston Consulting Group, current RAND researcher and professor Wong’s research interests center on defense innovation, military logistics, artificial intelligence in warfare, space capabilities, and the human dimension of military operations. He has led studies on human-machine teaming, non-lethal weapons, defense acquisition reform, and U.S. military posture in the Indo-Pacific. His work emphasizes practical, policy-relevant insights grounded in operational experience. The trends in his recent publications reveal a deep engagement with modern defense challenges: integrating commercial technologies into military systems, improving acquisition agility, enhancing battlefield awareness, and ensuring that defense innovation serves warfighter needs. His research spans strategic, operational, and tactical levels, often focusing on the U.S. Army and Marine Corps. Wong has not received public recognition in the form of listed awards in the provided texts, but his leadership in congressionally mandated studies and high-impact policy research suggests significant influence in defense circles. Advising & Grants: Co-led major projects such as the Long Range Precision Fires study and research on integrating women into Marine Corps infantry. His work is frequently funded by the Department of Defense and other federal entities, though specific grant details are not listed. Wong is affiliated with RAND’s defense and national security research teams, contributing to strategic analysis and policy development. He is not associated with a formal lab but works within RAND’s collaborative research environment, often partnering with other veterans and defense experts to produce actionable insights for military leaders and policymakers.
Dr. Kevin Kochersberger is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , with a career spanning academic research, technical innovation, and educational leadership. His work focuses on autonomous aerial systems , robotic control , and applied aerodynamics , particularly through the Uncrewed Systems Laboratory . Kochersberger's research has pioneered UAV-based radiation detection , 3D terrain mapping , and low-resource drone applications , including establishing the African Drone and Data Academy in Malawi . Education: Ph.D., Mechanical Engineering, Virginia Tech (1994) M.S., Mechanical Engineering, Virginia Tech (1984) B.S., Mechanical Engineering, Virginia Tech (1983) A.S., Engineering Science, Jamestown Community College (1981) Kochersberger's publications demonstrate expertise in UAV path planning , smart material actuation , and radiation source localization , with over $9M in research funding. His scientific awards include AIAA Associate Fellow (2009) and Aviation Week Aerospace Laureate (2003). Notable projects involve helicopter-deployable robotic systems and urban canyon navigation without GPS. Recent articles highlight BVLOS drone simulators , 2.5D terrain mapping , and autonomous negative obstacle traversal , reflecting his focus on real-time adaptive control and heterogeneous robotic systems . He teaches Drone Technology and Flight Operations and Advanced Design Projects , emphasizing student-driven innovation and industry collaboration .
Matthew Lakin is an Associate Professor with tenure in the Department of Computer Science at the University of New Mexico, with a courtesy appointment in the Department of Chemical & Biological Engineering. He is affiliated with the UNM Center for Biomedical Engineering and the School of Engineering, and collaborates extensively with the UNM Health Sciences Center and external institutions. Education: Ph.D., Computer Science, University of Cambridge, 2010 M.A. (Cantab), University of Cambridge, 2009 B.A. (Hons), Computer Science, University of Cambridge, 2005 Dr. Lakin's research focuses on molecular computing, DNA nanotechnology, synthetic biology, and formal verification of biomolecular circuits. He develops computational models and experimental systems for programmable biological devices, especially using heterochiral DNA to enhance stability in living cells. His work spans software tools for biodesign and experimental validation in mammalian systems, with applications in nanomedicine and biosensing. The recent publications highlight a strong trend in engineering robust, intelligent biomolecular systems. His work integrates machine learning concepts into chemical reaction networks, advances geometric modeling of DNA systems, and pioneers L-DNA-based circuits for intracellular applications. The research spans theoretical foundations, software tools, and wet-lab experimentation, emphasizing interdisciplinary innovation. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE), 2025 NSF CAREER Award, 2021 UNM School of Engineering Junior Faculty Research Excellence Award, 2021 Multiple student awards under his mentorship, including the Outstanding Graduate Student Award and DNA28 Best Student Presentation recognition Dr. Lakin has advised numerous graduate and undergraduate students, including Ph.D. graduates in Biomedical Engineering and Computer Science. He leads major funded projects such as the NSF CAREER grant on heterochiral molecular computing, an EPSCoR Research Fellowship, and a $3M NSF grant on heavy metal biosensing in collaboration with Native American communities. He is also PI on multiple NSF grants related to synthetic cells and nucleic acid technologies. He directs the Lakin Lab for Programmable Biology, which operates within the Department of Computer Science and collaborates with Chemical & Biological Engineering and the Center for Biomedical Engineering. The lab emphasizes both computational modeling and experimental molecular biology, and runs an NSF-funded biotechnology summer camp in partnership with ¡Explora! science museum to strengthen STEM education in New Mexico.
George H. Chen is an Associate Professor at Carnegie Mellon University , with dual affiliations in the Heinz College of Information Systems and Public Policy and the Machine Learning Department . His research focuses on trustworthy machine learning methods for temporal reasoning , particularly in health applications such as time-to-event prediction (survival analysis) and electronic health records analysis . He has extensive experience in nonparametric methods requiring minimal data assumptions. Educational Background PhD in Electrical Engineering and Computer Science, MIT (2015) SM in Electrical Engineering and Computer Science, MIT (2012) BS in Electrical Engineering and Computer Sciences & Engineering Mathematics and Statistics, UC Berkeley (2010) His work spans survival analysis , deep learning , and time series modeling , with applications in neurological prognostication , medical adherence , and health equity . He has developed self-contained educational resources including a 2024 monograph on deep survival analysis and tutorials at CHIL and SIGMETRICS. His 2025 course 95-865: Unstructured Data Analytics focuses on practical unstructured data analysis techniques. Notable projects include advising the AgriTech startup CoolCrop , which provides cold storage and market forecasts for Indian farmers serving 9,000+ farmers across 7 states. His Google Scholar publications reveal a strong focus on temporal modeling in healthcare, with recent advancements in neural survival analysis and fairness-aware temporal prediction.
