Shrirang Mare is an Assistant Professor in the Computer Science Department at Western Washington University (WWU), focusing on computer security and privacy with emphasis on usable security solutions for diverse user groups including low-literate individuals, the elderly, and cross-cultural populations. His research bridges human-computer interaction and cyber-physical systems to create accessible security mechanisms for emerging technologies. His educational background includes a PhD in Computer Science from Dartmouth College (2016), where his dissertation on seamless authentication for ubiquitous devices established his research trajectory. Dr. Mare's research interests encompass security and privacy, human-computer interaction, and cyber-physical systems, with specialized focus on security for low-literate users and developing regions. His work consistently addresses real-world applicability through field studies in countries like India and Pakistan, examining mobile payment systems, SMS fraud, and smart home privacy challenges. Analysis of his 15 most recent publications (2018-2024) reveals a dominant trend in wearable-based authentication systems (wristbands for desktops/smartphones) and privacy solutions for consumer IoT, particularly smart homes. His research uniquely combines technical security mechanisms with deep user-centered design principles, often targeting underserved populations in developing regions. No scientific awards or fellowships were mentioned in the provided documentation. Teaching responsibilities include Privacy Enhancing Technologies, Object Oriented Design, and Data Structures at WWU, with prior guest lectures at UC Berkeley and the University of Washington; no current advisees or grant funding details were specified. Dr. Mare operates within the Computer Science Department at WWU but no dedicated research lab or team structure was referenced in the source materials.
Dr. Friedrich Götz is an Associate Professor of Psychology in the Department of Psychology at the University of British Columbia (Faculty of Arts). His research focuses on geographical psychology, exploring the causes and consequences of regional personality differences through an interdisciplinary Big Data approach. PhD, University of Cambridge (UK), 2021 MPhil, University of Cambridge (UK), 2017 BSc, University of Konstanz (Germany), 2016 Dr. Götz’s work bridges social and personality psychology with behavioral science, examining topics like mobility, migration, wanderlust, courage, and entrepreneurship. He co-developed large-scale survey studies with TIME Magazine, attracting over 3 million participants. His research often involves experience sampling methods and open science. His recent publications emphasize geographical psychology, personality-environment interactions, and methodological advancements. Articles span 2020–2025, with key themes including regional personality differences, misinformation susceptibility, and the psychological impact of environmental features. Rising Star Award (Association for Psychological Science), 2025 SAGE Emerging Scholar Award (Society for Personality and Social Psychology), 2025 Top 40 under 40 – Germany (CAPITAL Magazine), 2024 President’s New Researcher Award (Canadian Psychological Association), 2024 Best Dissertation Prize (German Psychological Society), 2021 Leading Scholar (Green College), 2021 Dr. Götz teaches undergraduate and graduate courses, including Personality Psychology and Contemporary Conceptual Issues in Personality, with a focus on geographical dimensions. He is based in the Personality and Geographical Ambiance (PANGEA) Lab, which prioritizes inclusivity and collaboration in studying person-environment interactions.
Christopher Kruegel is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he conducts research in systems security. He is affiliated with the International Secure Systems Lab (iSecLab) and was a co-founder of Lastline, Inc., which was acquired by VMware in 2020. His work focuses on creating practical security solutions that address real-world problems through system building and experimental validation. Professor Kruegel's research spans multiple areas of computer security including malware analysis, web security, network security, and vulnerability analysis. His work often involves developing systems that analyze programs for malicious behavior, scanning web applications for vulnerabilities, and improving privacy on social networks. He has made significant contributions to firmware security, smart contract analysis, and mobile security through his extensive publication record. His 15 most recent publications (2022-2023) demonstrate a strong focus on practical security solutions across diverse domains including firmware security (Shimware, Fuzzware), blockchain and smart contract security (Confusum Contractum, NFT security), mobile security (TEEzz, Columbus), and vulnerability detection techniques (Actor, Toss a Fault to Your Witcher). His research shows consistent innovation in security tools and methodologies with several papers receiving distinguished awards. Fellow of the Institute of Electrical and Electronics Engineers Outstanding Graduate Mentor Award, UCSB Academic Senate Distinguished Artifact Award for Fuzzware paper Distinguished Paper Award for Ramblr paper Best Student Paper Award for Detecting Spammers On Social Networks Professor Kruegel has advised numerous graduate students and collaborated extensively with researchers at UCSB and beyond. His work has been funded by various research grants supporting his security research initiatives. He is actively involved in the International Secure Systems Lab, which focuses on practical security solutions for real-world problems.
Pauli Murto is a Professor and Head of the Department at Aalto University School of Business, Department of Economics. His research spans microeconomic theory, information economics, and game theory, with a focus on strategic decision-making under uncertainty. Aalto University School of Business, Espoo, Finland Member of Helsinki Graduate School of Economics Research Interests: Dr. Murto's work examines strategic timing in economic decisions, information aggregation in games, auction theory, and investment behavior under uncertainty. His publications address topics like: Common value auctions and affiliated signals Stepwise investment under multi-dimensional uncertainty Equilibrium delay and neighborly coordination Irreversible investment in oligopolistic markets Publications (2002–2024): His research appears in top journals like Review of Economic Studies , Theoretical Economics , Journal of Economic Theory , and RAND Journal of Economics , often collaborating with scholars such as Juuso Välimäki and Chang-Koo Chi. Contact: Available at pauli.murto@aalto.fi or +358 40 353 8174. Office located in Room V308, School of Business building, Aalto University.
Erik Velldal is a Professor in the Language Technology Group (LTG) at the Section for Machine Learning , Department of Informatics, University of Oslo . With over 25 years of experience in machine learning and natural language processing (NLP), he leads the SANT project focused on sentiment analysis and contributes to major research initiatives including MediaFutures , NorwAI , and Integreat (Norwegian Center for AI Research). His work bridges linguistic theory and computational methods, emphasizing semantic modeling and uncertainty detection. Research interests include sentiment analysis , language modeling , event extraction , and machine learning applications to NLP. Recent publications address cross-domain sentiment classification , generative event analysis , and multilingual model adaptation . He co-developed the Norwegian Review Corpus (NoReC) and Norwegian Anaphora Resolution Corpus (NARC) , foundational resources for Norwegian NLP. His projects often involve collaboration with international institutions, reflected in publications at venues like ACL, COLING, and EMNLP. Current efforts focus on entity-level sentiment analysis , diagnostic datasets for Norwegian , and evaluating compositional generalization in language models. No public record of scientific awards or part-time appointments exists.
Phillip B. Gibbons is a Professor in both the Computer Science Department and Electrical & Computer Engineering Department at Carnegie Mellon University. He received his Ph.D. in Computer Science from the University of California at Berkeley in 1989 and has held research positions at AT&T Bell Laboratories, Lucent Bell Laboratories, and Intel Research Pittsburgh before joining CMU's faculty. His research spans parallel computing, distributed systems, databases, computer architecture, and machine learning. Gibbons' work bridges theory and systems, with publications in top-tier conferences including SOSP, OSDI, SIGMOD, VLDB, NeurIPS, and many others across computer science and engineering disciplines. His research has been supported by significant funding from NSF, Intel, and other organizations. Gibbons has made substantial contributions to streaming algorithms, parallel computing frameworks, distributed systems security, and large-scale machine learning systems. His work on data stream algorithms with Alon, Matias, and Szegedy has been particularly influential in the field. He has served in numerous leadership roles including Editor-in-Chief of ACM Transactions on Parallel Computing (2012-2018) and on the editorial boards of Journal of the ACM and IEEE Transactions on Cloud Computing. He has also been active on program committees for major conferences in systems, databases, and theory. IEEE Fellow (2014) - For contributions to parallel computing and databases ACM Fellow (2006) - For contributions to parallel computing, databases, and sensor networks Selected for Oral Presentation at NeurIPS '13 (only 20 selected out of 1420 submissions) Co-winner of the best paper award for NSDI '06 Gibbons has advised numerous students and mentored researchers who have gone on to make significant contributions in academia and industry. His research has been supported by major grants including the $15M Intel Science and Technology Center for Cloud Computing (2011-2015) where he served as Co-PI/Co-Director. He currently leads research projects on write-efficient algorithms, big learning systems, and visual cloud systems. His laboratory work focuses on bridging theoretical computer science with practical systems implementation, particularly in the areas of parallel and distributed computing. Current research directions include adapting algorithms for emerging memory technologies and optimizing machine learning systems for large-scale deployment.
Dr. Yu-Ting Lin is a Senior Lecturer and Postgraduate Research Coordinator at the School of Marketing, The University of New South Wales (UNSW) . With a PhD in Marketing from Imperial College London , an MS in Management Information Systems from National Chengchi University , and a BBA in Management Information Systems from National Chiayi University , she bridges human-computer interaction and digital marketing through innovative research. Education: BBA, National Chiayi University MS, National Chengchi University PhD, Imperial College London Her research focuses on the intersection of digital technology and consumer behavior , particularly in emotional ad design , immersive media , and real-time marketing . She also explores mHealth applications for behavioral change. Dr. Lin’s work spans Journal of Marketing , Journal of Service Research , and other high-impact venues. Her recent Google Scholar publications highlight themes in branding psychology , digital interventions , and user experience analytics . Scientific Awards: 2024 ANZMAC Best Paper in Track Artificial Intelligence and Innovation 2024 Research Impact Award, UNSW Business School 2024 Research Supervisor Award, UNSW 2022 Dean's Research Fellowship, UNSW Business School 2021 Research Excellence Award – Early Career Researcher, UNSW Business School 2021 AMA TechSIG Lazaridis Prize for Best Paper on Marketing Innovation 2020 Finalist MSI Paul Root Award 2019 Technologies Incubation Scholarship, MOE (Taiwan) 2018 Case Centre Fellowship, Imperial College Business School 2017 Tutorial Fellowship, Imperial College Business School Dr. Lin’s grants include over AUD 400,000 in funding from ARC Discovery Projects , Australian Marketing Institute , and Taiwanese Overseas Pioneers Grant . She contributes to the Media Engagement and Analytics Lab (MEAL) at UNSW Business School.
Iona Cheng is a Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco (UCSF), where she conducts groundbreaking research in cancer epidemiology. She serves as co-Investigator of the SEER Greater Bay Area Cancer Registry and is Principal Investigator of multiple NIH- and foundation-funded projects examining genetics, lifestyle factors, and neighborhood characteristics in relation to cancer risk. Dr. Cheng has developed an extensive research program focused on racial/ethnic differences in cancer risk and leads population-based cancer surveillance studies that document variations in cancer incidence and mortality patterns across diverse racial and ethnic groups. University of California, Davis, BS, 1990–1994, Physiology Yale University, MPH, 1999–2001, Chronic Disease Epidemiology University of Southern California, PhD, 2001–2005, Epidemiology University of California, San Francisco, Postdoc, 2006–2008, Genetic and Molecular Epidemiology Dr. Cheng's research spans multiple disciplines within cancer epidemiology, with particular emphasis on understanding how environmental exposures, genetic factors, and social determinants interact to influence cancer risk and outcomes across different racial and ethnic populations. Her work frequently examines the impact of air pollution, endocrine-disrupting chemicals, and neighborhood characteristics on cancer development and survival. She has made significant contributions to understanding cancer disparities among Asian American, Native Hawaiian, and Pacific Islander populations, bringing attention to the unique cancer risks and outcomes within these understudied groups. Her research often leverages the Multiethnic Cohort Study, one of the largest prospective studies of cancer incidence and mortality across diverse racial/ethnic populations. Analysis of Dr. Cheng's recent publications reveals a consistent focus on environmental and social determinants of cancer risk across multiple organ sites. Her work demonstrates a sophisticated integration of epidemiological methods with environmental exposure assessment, genetic analysis, and health disparities research. Many of her studies examine the intersection of environmental exposures and racial/ethnic disparities in cancer outcomes, particularly regarding breast cancer, lung cancer, and other malignancies. She has published extensively on the impact of air pollution on cancer risk and survival, as well as the effects of endocrine-disrupting chemicals like bisphenol A, parabens, and phthalates. American Association for Cancer Research Scholar-in-Training Award (2007) National Institutes of Health Loan Repayment Award (2007) National Institutes of Health Loan Repayment Renewal Award (2009) American Association for Cancer Research Faculty Scholar Award (2011) National Institutes of Health Loan Repayment Renewal Award (2011) National Institutes of Health Loan Repayment Renewal Award (2013) American Journal of Epidemiology/Society of Epidemiology Research Top 10 manuscripts (2014) Cancer Prevention Institute of California Mentoring Award (2015) American Society of Human Genetics Top poster As Principal Investigator of multiple NIH-funded projects, Dr. Cheng oversees substantial research grants focused on cancer epidemiology and health disparities. Her work often involves large interdisciplinary collaborations with researchers across multiple institutions, including the Multiethnic Cohort Study which follows over 200,000 participants from diverse racial/ethnic backgrounds. She has demonstrated leadership in mentoring junior researchers, particularly those from underrepresented backgrounds in science, as evidenced by her Cancer Prevention Institute of California Mentoring Award. Her research program integrates data from cancer registries, electronic health records, and geospatial information to provide comprehensive insights into cancer patterns and risk factors. Dr. Cheng's research is closely connected to the UCSF Helen Diller Family Comprehensive Cancer Center and leverages collaborations with Lawrence Berkeley National Laboratory, which provides advanced technological resources for cancer research. Her work benefits from access to extensive cohort data, sophisticated exposure assessment methods, and interdisciplinary expertise in genetics, environmental science, and computational biology available through these institutional partnerships. She frequently collaborates with researchers studying the genetic and environmental determinants of cancer across multiple organ systems, contributing to a more comprehensive understanding of cancer etiology and prevention strategies.
Cristina Bicchieri is the S. J. Patterson Harvie Professor of Social Thought and Comparative Ethics at the University of Pennsylvania , where she also holds appointments as Professor of Philosophy and Psychology and Professor of Legal Studies at the Wharton School. She founded and directs the Penn Center for Social Norms and Behavioral Dynamics , the Philosophy, Politics & Economics Program , and the Master of Behavioral and Decision Sciences . Education : PhD in Philosophy from Cambridge University and a Laurea (Summa cum Laude) from the University of Milano . Her research lies at the intersection of philosophy , game theory , and cognitive psychology , focusing on: Judgment and Decision-Making : Fairness, trust, cooperation, and how expectations influence behavior. Social Norms : Their nature, evolution, measurement, and application in policy (e.g., sanitation, corruption). Epistemic Foundations of Game Theory : Rational choices under bounded knowledge and computational models for game solutions. Her recent articles explore topics like norm stability , language framing effects , and sanitation interventions in India . These works emphasize behavioral dynamics , cognitive psychology , and public policy applications . Scientific Awards : Member, American Academy of Arts and Sciences (2021) Member, German Academy of Sciences (2021) Honorary Fellow, Wolfson College, Cambridge (2016) Pufendorf Medal (2015) Cavaliere Ordine al Merito della Repubblica Italiana (2007) She leads the Behavioral Ethics Lab and collaborates with organizations like UNICEF , the World Bank , and the Gates Foundation to implement norm-based interventions globally.
Hal S. Stern is Provost and Executive Vice Chancellor at the University of California, Irvine (UCI), and a Distinguished Professor in the Department of Statistics. He previously served as founding Chair of the Department of Statistics, Dean of the Donald Bren School of Information and Computer Sciences, and Vice Provost for Academic Planning at UCI. Earlier, he held faculty positions at Iowa State University and Harvard University. B.S. in Mathematics, Massachusetts Institute of Technology M.S. and Ph.D. in Statistics, Stanford University Stern is a leading expert in Bayesian statistical methods, with significant collaborative work in life sciences and social sciences. His current research focuses on forensic statistics (e.g., footwear impression and bloodstain pattern analysis), psychiatric studies of early-life adversity's impact on brain development, and statistical applications in sports analytics. He co-directs the NIST-funded Center for Statistics and Applications in Forensic Evidence and leads the Conte Center's NIMH-funded research on mental health vulnerabilities. His notable contributions include the third edition of Bayesian Data Analysis , which expanded computational methods and Bayesian nonparametric modeling, featuring STAN software. Stern has secured major grants from NIST and NIMH for interdisciplinary projects. Fellow, American Association for the Advancement of Science Fellow, American Statistical Association Fellow, Institute for Mathematical Statistics He has mentored graduate programs as Vice Provost for Graduate Education and contributed to UCI's academic strategy as Vice Provost for Academic Planning. Stern's leadership extends to directing centers that bridge statistics with forensic science and mental health research.
Pascal Mettes is a tenured Assistant Professor at the University of Amsterdam within the Informatics Institute, specializing in Artificial Intelligence. He leads groundbreaking research in hyperbolic deep learning, a field he has significantly advanced through theoretical developments and practical applications in computer vision and multimodal learning. His research focuses on three primary domains: hyperbolic vision-language models that address the hierarchical nature of language-vision relationships; hierarchical deep learning using hyperbolic embeddings that naturally accommodate exponential growth patterns; and robust deep learning in hyperbolic space that improves out-of-distribution detection and network resilience. Mettes has established himself as a leading figure in this emerging field through numerous publications at top-tier conferences including CVPR, ICCV, ICML, NeurIPS, and ICLR. His recent work demonstrates how hyperbolic geometry provides natural solutions to fundamental limitations in modern deep learning, particularly regarding hierarchical data structures that cannot be adequately represented in Euclidean space. The publication trends show increasing impact and recognition in the computer vision and machine learning communities, with multiple papers receiving oral presentations and best paper nominations. Best paper nomination ESWC25 for 'Designing Hierarchies for Optimal Hyperbolic Embedding' Finalist MM 2023 Best Open-Source Software Competition (for HypLL) Multiple reviewer awards across major conferences including CVPR, ICLR, ECCV, ICML, and NeurIPS MM 2016 Best Doctoral Student Award TRECVID 2015 Winner Multimedia Event Detection Benchmark Mettes actively mentors eight PhD students working on hyperbolic learning and related topics, while also securing significant research funding including ELLIs PhD Award, NWO ClickNL, Google Perception Academic Funding, and Data Science Centre PhD Grants. He serves in prominent academic roles as Program Chair for International Conference on Multimedia Retrieval 2026 and has organized multiple workshops on hyperbolic learning at major conferences. His leadership in establishing hyperbolic deep learning as a recognized research direction is evident through his survey paper in IJCV 2024 and the development of the HypLL library for hyperbolic learning.
Nancy G. Love is the Borchardt and Glysson Collegiate Professor and JoAnn Silverstein Distinguished University Professor of Environmental Engineering at the University of Michigan, affiliated with the Department of Civil and Environmental Engineering and the African Studies Center. Her research focuses on water infrastructure, public health, and environmental systems, emphasizing interdisciplinary approaches to address challenges in both domestic and global contexts. Education: Ph.D. (1994) in Environmental Systems Engineering from Clemson University; MS (1986) and BS (1984) in Civil Engineering from the University of Illinois. Research interests include water quality, pathogen fate and transport, sustainable resource recovery (e.g., urine-derived fertilizers), and infrastructure resilience in shrinking cities. She leads the Love Research Group, which integrates chemical, biological, and computational methods to develop technologies for contaminant removal, resource recovery, and public health protection. Her work addresses pressing issues like drinking water equity in Detroit, Legionella outbreaks in Flint, and global sanitation in Ethiopia. She advocates for transdisciplinary collaboration and community-informed solutions to environmental challenges. Awards include prestigious professorships at the University of Michigan. She serves on editorial boards (e.g., ACS ES&T Engineering) and contributes to policy initiatives on water infrastructure and environmental justice. Labs/Teams: Love Research Group; Collaborations span academia, industry, and NGOs, including projects on urine diversion, sensor-mediated wastewater treatment, and civic engagement in infrastructure decisions.
Edith Hemaspaandra is a Professor in the Department of Computer Science at the Rochester Institute of Technology (RIT), located in the Golisano College of Computing and Information Sciences. She holds a BS, MS, and Ph.D. in Computer Science from the University of Amsterdam (the Netherlands). Her research focuses on computational social choice, computational complexity theory, logic complexity, and formal methods. She teaches courses such as CSCI-262/263 (Introduction to Computer Science Theory) and CSCI-664 (Computational Complexity). Her work explores the algorithmic aspects of voting systems, including election manipulation, control, and bribery, with a focus on their computational complexity. She has also contributed to formal methods for automata theory, educational tools like JFLAP extensions, and the study of complexity classes such as LWPP and WPP. Her research bridges theoretical computer science with practical applications in social choice theory and algorithm design. Her grants include an NSF-funded project on computationally protecting elections from manipulation (2011). She actively publishes in top venues like STACS and ISAAC, addressing topics ranging from graph reconstruction to hybrid election models. Though no awards are explicitly listed, her extensive publication record highlights her contributions to theoretical computer science. Her advising and grant activities include collaborative research projects and educational tool development. She is affiliated with RIT’s Department of Computer Science and maintains a personal website and ORCID profile.
Professor Luke Harding is a faculty member at the Department of Linguistics and English Language , Lancaster University , within the School of Social Sciences . His work bridges applied linguistics, language assessment, and critical discourse studies, with a focus on the ethical and societal implications of testing. Research Interests : Language testing and assessment, World Englishes and English as a Lingua Franca (ELF), second language listening and pronunciation assessment, diagnostic approaches to language evaluation, and language assessment literacy. Recent projects integrate digital technology and corpus linguistics into testing frameworks. Publications : Published extensively in Language Testing , Applied Linguistics , and Language Assessment Quarterly . Co-edited the Routledge Handbook of Language Testing (Second Edition) (2022), a key reference work in the field. Teaching : Leads modules in Language Test Construction and Evaluation , Issues in Language Testing , and Statistical Analysis for Language Testing within the university's distance MA program. Leadership : Convened the Language Testing Research Group with colleagues Tineke Brunfaut and John Pill, advancing interdisciplinary approaches to assessment.
Juan Yao is a Senior Lecturer at the Finance Discipline, Business School, The University of Sydney. Her research focuses on empirical asset pricing , funds management , foreign exchange markets , and business forecasting . She has contributed to national research projects such as "Strategies and Approaches to Teaching and Learning Cross Cultures" (2007-2009) and is affiliated with the Sydney Environment Institute, China Study Centre, and Australia-China Business Network. Research Interests: Juan’s work explores financial market efficiency, investor behavior, and cross-cultural economic dynamics. Her publications address hedge fund performance, mutual fund strategies, and behavioral anomalies in both Australian and Chinese markets. Publications: Recent articles analyze price bubbles, sentiment analysis, and institutional trading impacts, spanning journals like Journal of Banking & Finance and Pacific-Basin Finance Journal . Grants: She served as Chief Investigator for a national teaching and learning grant (2007-2009) and a 2014 CIPR grant on asset-price bubbles in Australia.
