جست‌وجوی استاد و پژوهشگر

Walter Jetzمشاهده پروفایل

استاد

• Ecology
• Biodiversity Science
• Conservation
• +۵ مورد دیگر

Walter Jetz is a Professor of Ecology and Evolutionary Biology and the School of the Environment at Yale University, where he directs the Center for Biodiversity and Global Change. He chairs the E.O. Wilson Biodiversity Foundation and co-chairs the GEO BON Species Population Working Group. His work focuses on biodiversity science, conservation, and global change ecology. Education: D.Phil. in Zoology (University of Oxford, 2002), M.Sc. in Integrative Bioscience (Oxford, 1997) Research interests include macroecology, species distribution modeling, and conservation science across spatial scales. His group develops tools like Map of Life , Wildlife Insights , and Half-Earth Project to address biodiversity monitoring and area-based conservation. Current projects explore climate change impacts on tropical ecosystems, movement ecology, and machine learning applications in biodiversity science. Recent publications focus on niche scaling, climate change vulnerability, deep learning for species distribution, and mountain biodiversity monitoring. Awards include being an ISI Highly Cited Researcher since 2014. Over 30 former students hold faculty positions globally. The lab promotes diversity, equity, and inclusion in science and collaborates with NASA, Microsoft, and the Gordon and Betty Moore Foundation.

• Computational Social Choice
• Algorithmic Game Theory
• Fairness in Machine Learning
• +۳ مورد دیگر

Anson Kahng is an Assistant Professor in the Department of Computer Science and the Goergen Institute of Data Science at the University of Rochester. He previously held postdoctoral positions at the University of Toronto and completed his PhD at Carnegie Mellon University under the supervision of Ariel Procaccia, focusing on computational social choice. PhD, Computer Science, Carnegie Mellon University Undergraduate degree, Computer Science, Harvard College His research explores the intersection of computer science and democracy, developing frameworks like virtual democracy and liquid democracy while analyzing fairness in participatory budgeting and voting systems. He combines theoretical analysis with empirical methods, emphasizing interdisciplinary collaboration. Recent work includes advancements in ranked choice voting optimization, fairness metrics for elections, and structural analysis in cryo-electron tomography. He has published in top venues such as IJCAI, AAAI, NeurIPS, and ACM Transactions on Economics and Computation. NeurIPS 2019 Spotlight Presentation (top 2.5% of submissions) Kahng advises PhD students Alina Chadwick and Joe Saber, and has mentored multiple undergraduate researchers. He teaches courses on algorithmic game theory and computational statistics at the University of Rochester.

Leah Macfadyenمشاهده پروفایل

عضو هیئت علمی

• Critical Intercultural Studies
• Digital Literacies
• Digital Research Methods
• +۶ مورد دیگر

Leah Macfadyen is an Associate Professor of Teaching in the Department of Language & Literacy Education at the University of British Columbia (UBC), Faculty of Education. She serves as Coordinator for Curriculum & Instruction in the Master of Educational Technology (MET) program. With interdisciplinary training in experimental sciences and humanities, she bridges analytical rigor with cultural theory in her research on digital education and learning analytics. Her research spans learning analytics , digital literacies , and critical intercultural communication . Key projects include developing UBC’s Introduction to Global Citizenship online course (2005) and co-authoring MET program courses like ETEC 542. She explores ethical dimensions of ‘big data’ in education and data literacy challenges. Recent publications (2020–2023) focus on institutional learning analytics frameworks, curriculum NLP analysis, and ethical codes for practitioners. Collaborative work with Shane Dawson and others has been published in journals like Journal of Learning Analytics , Computers & Education , and Journal of Genetic Counselling . Key Themes : Intercultural communication in digital spaces, systems thinking for educational analytics, ethical implications of data-driven learning Courses Developed : ETEC 500, 520, 542, 543, 581, and 590

Germain Gauthierمشاهده پروفایل

استادیار

• Political Economy
• Public Economics
• Econometrics
• +۷ مورد دیگر

Germain Gauthier is an Assistant Professor at the Department of Social and Political Sciences, Bocconi University. His work bridges economics and political science with a focus on political economy, public economics, and machine learning methods. He develops AI tools for social scientists, particularly for analyzing unstructured data like texts and images. Ph.D. in Economics, Ecole Polytechnique (2018–2023) Postdoctoral Researcher, ETH Zürich (2023) M.Sc. in Analysis and Policy in Economics, Paris School of Economics (2017–2018) M.Sc. in Quantitative Economics, HEC Paris (2013–2017) His research spans two main areas: applied studies on digital technologies' societal consequences (e.g., X's algorithms, #MeToo's impact) and methodological innovations in machine learning for social science data. Recent publications include work on protest dynamics, inequality, and narrative extraction from texts. Key trends in his publications include: Machine learning applications to political and economic analysis Text mining for social science narratives Empirical studies on protest movements and digital governance Algorithmic bias in labor markets Economic policy evaluation using big data He has received significant funding: Swiss National Sciences Foundation Grant (300K CHF, 2023–2026) Swiss National Sciences Foundation Grant (100K CHF, 2020) Laboratoire d’Excellence Ph.D. Grant (2018–2023) He teaches courses on Public Finance (Bocconi) and Text as Data for Social Sciences (LMU München), and has developed open-source software packages like relatio and DeepLatent for text analysis and latent variable modeling.

Marshall Ganzمشاهده پروفایل

مدرس ارشد

• Leadership
• Organizing
• Social Movements
• +۵ مورد دیگر

Marshall Ganz is the Rita E. Hauser Senior Lecturer in Leadership, Organizing, and Civil Society at the Harvard Kennedy School . He specializes in leadership development, narrative strategy, and organizing frameworks for social movements and civic institutions. His career spans decades of activism, academia, and global training initiatives. Education: Completed an undergraduate degree in history and government (2000), MPA (1993), and PhD in sociology (2000) at Harvard University. His research focuses on the role of leadership in social change, public narrative as a mobilization tool, and strategic capacity-building in grassroots movements. He has published extensively in American Journal of Sociology , American Political Science Review , and policy journals like Stanford Social Innovation Review . Recent scholarly work emphasizes the intersection of storytelling and collective action, with trends toward democratizing power structures in civic communities. Awards include the Michael J. Harrington Book Award (2009) for Why David Sometimes Wins and an honorary doctorate in divinity (2010) from Episcopal Divinity School. His sponsored projects include Leadership for Democracy and Social Justice (funded by The City College of New York) and Democratic Governance Assessment Project (with Girl Scouts of the USA). As co-founder of the Leading Change Network , Ganz trains global leaders in organizing and leadership development. He has also designed executive programs like Public Narrative: Leadership, Storytelling, and Action and Leadership, Organizing, and Action: Leading Change , which have been adopted across sectors.

• Sports Law
• Corporate Compliance
• Legal Ethics
• +۳ مورد دیگر

Tyler Custis serves as an Associate Professor at the University of South Dakota's Beacom School of Business, specializing in Business Law and the Legal Environment. His academic appointments reflect deep engagement with contemporary legal challenges in sports, finance, and corporate governance. His educational background includes: JD from University of South Dakota (2013) MBA from University of South Dakota (2012) BS from Texas A&M University (2007) Custis' research focuses on high-impact legal intersections, particularly NCAA regulations, corporate fraud mechanisms, and healthcare compliance failures. His work bridges theoretical legal frameworks with real-world economic consequences, examining how regulatory gaps enable systemic misconduct in sports leagues and financial institutions. Key themes include Title IX implications for athlete compensation, internal control failures in banking scandals, and antitrust considerations in collegiate athletics. His publication portfolio reveals strong emphasis on sports law evolution (2016-2025), corporate ethics case studies (2018-2022), and financial regulation analysis (2019-2024). The research demonstrates methodological diversity spanning empirical analysis of NCAA labor models, forensic accounting of banking fraud, and policy evaluation of legislative responses to corporate misconduct. Award recognition includes: Beacom School of Business Faculty Excellence Teaching Award (2023) Excellence in Teaching Award Nominee (2023) Best Paper Award at ICTO International Conference (2019) Custis actively disseminates research through scholarly presentations at venues including ASHE Annual Conferences, Academy of Legal Studies meetings, and Beacom Scholar Series. His work engages directly with policymakers on NCAA reform and corporate compliance frameworks, demonstrating applied impact beyond academic circles.

• Data Governance
• Computer Supported Collaborative Learning
• Student Persistence
• +۴ مورد دیگر

Dawn Laux serves as Assistant Dean of Academic Programs and Professor of Practice in the School of Applied and Creative Computing at Purdue Polytechnic Institute, Purdue University. She concurrently holds the position of Division Head for Military Science and Technology and chairs the Purdue University Teaching Academy. With over 15 years of service since 2007, Dr. Laux teaches undergraduate information governance courses and has earned recognition including the Charles B. Murphy Award for Outstanding Undergraduate Teaching (2019) and induction into Purdue's Book of Great Teachers (2023). Her educational background includes: PhD in Human Computer Interaction, Iowa State University (2014) MS in Management Information Systems, Iowa State University (2007) BS in Business Education and Office Administration, Ball State University (1994) Dr. Laux's research centers on data governance, computer-supported collaborative learning, and student persistence in technology education. She investigates technology acceptance, recruitment of women and minorities into IT, database management, and information governance frameworks. Her work bridges educational theory with practical applications to enhance student engagement and diversity in computing fields. Analysis of her publications (2011-2016) reveals consistent focus on educational technology interventions, particularly examining virtual communities for student persistence, diversity initiatives in computing, and classroom technology adoption. Her research demonstrates interdisciplinary integration of information systems, educational psychology, and social computing principles with practical applications in higher education settings. Her distinguished recognition includes: Book of Great Teachers, Purdue University (2023) Academic Leadership Program Fellow, Big Ten Academic Alliance (2022-2023) Teaching Academy Member, Purdue University (2019) Charles B. Murphy Award for Outstanding Undergraduate Teaching (2019) College of Technology Exceptional Early Career Teaching Award (2014-2015) Teaching for Tomorrow Fellowship Award (2013-2014) Bringing 10 years of pre-academic industry experience from Purdue Employees Federal Credit Union and Insight Communications, Dr. Laux integrates practical IT expertise into her teaching and leadership. Her administrative roles encompass academic program oversight and military technology education initiatives, supported by her active participation in the National Center for Women and Information Technology Academic Alliance since 2011. As Division Head of Military Science and Technology, Dr. Laux leads specialized technology education programs while chairing the university-wide Teaching Academy to advance pedagogical excellence across Purdue's academic units.

Markus Christenمشاهده پروفایل

پژوهشگر

• empirical ethics
• neuroethics
• ICT ethics
• +۵ مورد دیگر

Markus Christen is a researcher and Managing Director of the Digital Society Initiative at the University of Zurich, where he leads the Digital Ethics Lab within the Institute of Biomedical Ethics and History of Medicine. His work bridges empirical ethics, neuroethics, and ICT ethics with a focus on data analysis methodologies. Affiliation: University of Zurich (Faculty of Medicine) Role: Managing Director of the Digital Society Initiative Lab: Digital Ethics Lab Christen’s research explores ethical challenges in AI, cybersecurity, and digital health. He investigates value conflicts in technology design, moral sensitivity training through serious games, and human-AI accountability frameworks . His recent publications address digital twins in medicine , AI accessibility for disabled students , and cross-cultural responsibility gaps in AI systems. Key trends in his work include: Empirical ethics applied to AI and cybersecurity Neuroethical dimensions of technology Responsible AI integration in education and healthcare Data privacy and fairness in insurance Cross-cultural ethical assessments Christen’s lab develops frameworks for value-sensitive design and human-AI collaboration , with projects like "Responsible AI in practice" and "DSI AI-WEEK."

Liane Colonnaمشاهده پروفایل

استادیار

• AI Ethics
• Data Protection Law
• Algorithmic Regulation
• +۲ مورد دیگر

Liane Colonna is an Assistant Professor in Law and Information Technology at the Department of Law, Stockholm University , where she investigates ethical and legal challenges arising from AI-driven practices in higher education. She also engages in methodologically oriented research at the intersection of AI and Law, contributing to the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society. Additionally, Liane serves as the director of the Swedish Law and Informatics Research Institute (IRI) and is a member of the New York Bar since 2008. Primary Affiliation: Department of Law, Stockholm University Institute Leadership: Director, Swedish Law and Informatics Research Institute (IRI) Professional Status: Member of the New York Bar Research Interests: Ethical and legal challenges of AI in higher education Methodological approaches in AI and Law Data protection and privacy by design Regulatory frameworks for AI and emerging technologies Privacy implications of lifelogging and health IoT International data governance and surveillance law Publications demonstrate expertise in AI regulation, GDPR compliance, and privacy-preserving technologies, particularly for assisted living and educational contexts. Her work bridges technical implementation with legal accountability, emphasizing human oversight and ethical design.

Sudhir Kumarمشاهده پروفایل

استاد

• Molecular Evolution
• Phylomedicine
• Functional Genomics
• +۵ مورد دیگر

Sudhir Kumar is a Professor and Principal Investigator at Temple University, leading a research laboratory focused on molecular evolution, phylomedicine, and functional genomics. His lab develops mathematical methods, computational algorithms, and software packages for analyzing genomic variation across populations, pathogens, tumors, and species. Key contributions include the widely used MEGA software (www.megasoftware.net) for molecular evolutionary analysis and the TimeTree knowledge-base (www.timetree.org) that synthesizes evolutionary knowledge on species divergence times. Dr. Kumar's research interests center on integrating mathematical and computational techniques into evolutionary biology and biomedicine. His lab pursues a holistic paradigm where evolutionary and genomic patterns are discovered through comparative analysis of big datasets, then used to reveal underlying biological processes and develop predictive models. His work spans phylomedicine of genetic diseases, molecular phylogenomics, and the timetree of life, with recent innovations including Bayesian methods, machine learning algorithms, and statistical approaches for inferring molecular phylogenies, divergence times, and pathogenic mutations. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence and machine learning to evolutionary genetics, with multiple 2025 papers focused on sparse learning techniques, transformer-based models, and AI-assisted analytical protocols. His work increasingly bridges evolutionary biology with cancer genomics and precision medicine applications. His scientific achievements have been recognized with the prestigious 2025 George W. Beadle Award from the Genetics Society of America, which honors his "efforts to democratize evolutionary genetics." Dr. Kumar has mentored numerous doctoral candidates, postdoctoral researchers, and graduate students, many of whom have gone on to faculty positions at institutions including Oakland University and universities in Brazil. His lab includes current doctoral candidates working in bioinformatics and statistical molecular evolution, supported by technical staff including programmers, genome tech specialists, and informatics specialists. The Kumar Laboratory operates as an interdisciplinary research hub with multiple projects including MEGA (Molecular Evolutionary Genetics Analysis), TimeTree, myPEG (web-based evolutionary tools), and FlyExpress (a knowledge base for Drosophila melanogaster embryo images). The lab emphasizes green computing efforts aimed at democratizing scientific practice and making big data analytics more accessible.

• Dark Matter
• Particle Astrophysics
• Cosmology
• +۲ مورد دیگر

Pearl Sandick is a Professor in the Department of Physics and Astronomy and Interim Dean in the College of Science at the University of Utah. She has previously served as Associate Chair of the Department of Physics and Astronomy and Associate Dean for Faculty and Research in the College of Science. Her academic journey at the University of Utah began in 2011 as an Assistant Professor, progressing to Associate Professor in 2017, and achieving the rank of Professor in 2022. Her educational background includes: BA in Mathematics from New York University (2003) PhD in Physics from the University of Minnesota (2008) Sandick is a theoretical particle physicist whose research focuses on physics beyond the Standard Model, with particular emphasis on dark matter. Her work spans theoretical modeling, connections to astrophysical observations, and implications for experimental detection. She investigates various dark matter candidates and their potential signatures in current and future experiments, including collider searches, direct detection experiments, and indirect detection through astrophysical observations. Her research also extends to connections between particle physics and cosmology, including early universe phenomena and implications for cosmic structure formation. She has developed computational tools like MADHAT for dark matter analysis and has made significant contributions to understanding how stellar evolution can constrain axion physics. Her scholarly contributions have been recognized with several prestigious awards: University of Utah Early Career Teaching Award (2016) University of Utah Distinguished Mentor Award Linda K. Amos Award for Distinguished Service to Women University of Utah Presidential Scholar Sandick has been actively involved in mentoring graduate students, as evidenced by her teaching of PhD thesis research and Master's research courses. She has secured significant research funding from the National Science Foundation and other agencies to support her work on dark matter, dark energy, and new physics. Her grant portfolio includes projects on theoretical particle physics, connections to astrophysical observations, and studies on graduate education reform following a departmental tragedy. She is an active member of the American Physical Society, having served as Chair of the regional Four Corners Section in 2021-2022, demonstrating her commitment to the broader physics community and leadership in her field.

Rasmus Paghمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Big Data
• +۷ مورد دیگر

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

Bei Jiangمشاهده پروفایل

دانشیار

• Biostatistics
• Functional Data Analysis
• Statistical Machine Learning
• +۶ مورد دیگر

Dr. Bei Jiang is an Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta , Canada. She holds the Canada CIFAR AI Chair and is affiliated with the Alberta Machine Intelligence Institute (Amii) . Her academic journey includes a PhD in Biostatistics (2014) from the University of Michigan, MS (2008) and BS (2004) from the University of Alberta and Beijing University of Technology, respectively. Current Positions : 2021–Present (Associate Professor), 2022–Present (CIFAR AI Chair) Past Appointments : Assistant Professor (2015–2021), Postdoctoral Fellow at Columbia University (2014–2015), Research Assistant at University of Michigan (2009–2013) Research Interests : Dr. Jiang specializes in methods for joint modeling of longitudinal and health outcome data , Bayesian hierarchical modeling , functional and imaging data analysis , and statistical machine learning . Her work integrates kernel machine regression , differential privacy , and synthetic data generation to address challenges in heterogeneous health data and neuroimaging. Scientific Awards : Highlights include the 2015 SAMSI New Research Fellow , multiple Rackham Conference Travel Awards (2013, 2012), and prestigious NSERC scholarships (2009–2012). She has also received the J Gordin Kaplan Graduate Award (2008) and Statistical Society of Canada Travel Award (2008). Grants : $375,000 (CIFAR AI Chairs, 2022–2027), $480,000 (MITACS Accelerate, 2022–2025), and $210,000 (Canadian Statistical Sciences Institute, 2022–2025) Students and Postdocs : She mentors numerous PhD , MSc , and Postdoctoral Fellows , including Junxi Zhang (2023–Present), Enze Shi (2022–Present), and former advisees like Wenxing Guo (now Lecturer at University of Essex) and Yafei Wang (Assistant Professor at University of Alberta).

Chenhao Maمشاهده پروفایل

استادیار

• Graph Computing
• Data Mining
• Database Systems
• +۳ مورد دیگر

Dr. Chenhao Ma is an Assistant Professor at the School of Data Science , The Chinese University of Hong Kong, Shenzhen , where he works on large-scale data management and data mining. Previously, he was a Postdoctoral Fellow at the University of Hong Kong (2021–2022) and earned his PhD in Computer Science from the University of Hong Kong (2021) and B.Eng. from Shandong University (2017). Current research focuses on graph computing (dense subgraph discovery, motif analysis, graph learning), AI+DB (Text-to-SQL, vector search), and traffic data mining (trajectory analysis, outlier detection). He has published over 40 papers in top venues including SIGMOD, PVLDB, KDD and received the ACM SIGMOD Research Highlight Award 2021 and Best of SIGMOD 2020 (4/458). Scientific Awards : ACM SIGMOD Research Highlight Award 2021 Best of SIGMOD 2020 (4/458) Presidential Young Fellow at CUHK-Shenzhen (2023) Hong Kong and China Gas Scholarship (2019-2020) Reaching Out Award (2019) HKU Postgraduate Scholarship (2017-2021) ACM-ICPC Gold Medal (2015) National Scholarship (2014, 2015) Advising and Research Team : He leads a team including Postdoc Dr. Yuanyuan Zeng, PhD students Lujie Ban, Yuwei Xu, and MPhil students Yi Yang, Yuyang Liang. Former mentees like Yichen Xu (PhD at Berkeley) and Jiayang Pang (Master at UC San Diego) have achieved academic placements. Professional Service : He has served as PC member/reviewer for VLDB, KDD, ICDE, WWW, NeurIPS, TKDE , and guest editor for Applied Sciences and Frontiers in Big Data . He chairs sessions at ICDE and VLDB.

Kenneth M. Andersonمشاهده پروفایل

استاد

• Software Engineering
• Crisis Informatics
• Human-Computer Interaction
• +۳ مورد دیگر

Professor Kenneth M. Anderson is Chair of the Department of Computer Science and holds the Palmer Endowed Chair at the University of Colorado Boulder's College of Engineering & Applied Science. He co-directs Project EPIC, a $4M NSF-funded initiative on social media use during mass emergencies, and serves as Co-Director of the Center for Software and Society. Ph.D. in Computer Science, University of California, Irvine (1997) Joined CU Boulder in 1998; tenured in 2005 Former Associate Dean for Education (2016-2019) Former Associate Chair (2010-2013) His research bridges software engineering, crisis informatics, and human-computer interaction. Current projects focus on large-scale social media analytics, crisis response systems, and software architecture for data-intensive environments. Recent publications explore multilingual social media analysis (ML-EPIC), bug fix patterns in software development (FIXR), and collaborative big data platforms. Themes include disaster risk communication, data modeling challenges, and asynchronous analysis tools. ATLAS Fellow (2010) As department chair, he spearheaded initiatives for inclusivity, including creating a Bachelor of Arts in Computer Science and establishing the NSF Broadening Participation in Computing plan. He oversees major academic reforms and departmental operations.