جست‌وجوی استاد و پژوهشگر

Ian Greerمشاهده پروفایل

پژوهشگر ارشد

• Industrial Relations
• Marketisation
• Welfare States
• +۷ مورد دیگر

Ian Greer is a Research Fellow at Cornell University's School of Industrial and Labour Relations , with a career focused on marketisation , industrial relations , and transnational solidarity . He holds a PhD from Cornell University and has previously studied at Bard College. His work examines labor dynamics in globalised industries , welfare states , and multinational corporations , often through qualitative comparative methods . Education : BSc (Bard College), MSc/PhD (Cornell University) Greer's research spans marketisation of employment services , social movement unionism , and labour policy in crisis situations . His publications include studies on European welfare-to-work schemes , healthcare privatisation , and labour migration . He is associated with the Centre for Employment Relations, Innovation and Change (CERIC) at the University of Leeds. Greer's recent work analyses precarious labor and project-based employment in social services across Slovenia and France. He also contributes to debates on social dumping , work-first welfare states , and activist labor strategies in sectors like healthcare and automotive manufacturing. He has no listed scientific awards. His work often involves collaboration with scholars like Marco Hauptmeier , Charles Umney , and Nathan Lillie , though no formal advisees are named in the provided text. His email is icg2@cornell.edu .

• Combinatorics
• Operator Theory
• Graph Theory
• +۲ مورد دیگر

Sergio Bermudo Navarrete is a Professor at the Department of Economics, Quantitative Methods and Economic History, Universidad Pablo de Olavide. His research spans combinatorics, graph theory, and operator theory. Education: PhD in Mathematics (2003, University of Seville) with thesis on functional models of operators in Hilbert spaces. Research Interests: Focus on graph theory, domination problems, topological indices, and operator theory. Publication Trends: Recent work includes vertex-degree-based indices for oriented graphs, domination parameters in product graphs, and differential analysis of line graphs. Keywords span Computer Science , Mathematical Chemistry , and Operations Research . Collaborations: Frequent co-authors: José María Sigarreta Almira, José Manuel Rodríguez García, Juan Alberto Rodríguez-Velazquez. Contact: Email sbernav@upo.es .

Harry Nelsonمشاهده پروفایل

دانشیار

• Ecosystems and Climate Change
• Sustainable Forest Management
• Natural Resource Policy
• +۳ مورد دیگر

Harry Nelson is an Associate Professor at the University of British Columbia (UBC) within the Faculty of Forestry , specifically the Department of Forest Resources Management . His work focuses on natural resource policy, climate change adaptation, and sustainable forest management in Canada. Research Themes : Ecosystems and Climate Change, Sustainable Forest Management, Indigenous Governance Key Interests : Climate change impacts on forestry, ecosystem services, policy development Nelson’s research explores the structural transformation of the forest sector under changing markets and public expectations. He investigates ecosystem services as a business model for Indigenous forest management in BC and analyzes global climate adaptation strategies. Recent publications highlight cross-border forestry challenges, wildfire risks, and socio-economic dynamics in forest enterprises. His 15 most recent articles (2019–2025) span interdisciplinary topics such as climate change adaptation, Indigenous governance, bioeconomy, and global forest policy. These works emphasize the integration of ecological and economic frameworks to address sustainability. Scientific awards and recognitions: No awards explicitly mentioned in the provided texts. Nelson’s email address ( harry.nelson@ubc.ca ) and research areas are publicly available. No student advisement details or grant information is provided in the scraped data.

Sharat Chandranمشاهده پروفایل

استاد

• Computer Graphics
• Computer Vision
• Visual Computing
• +۳ مورد دیگر

Sharat Chandran is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay (IIT Bombay), where he has been actively engaged in teaching and research for several decades. His office is located in Room KR102 (also known as A202) in the Rekhi Building on the IIT Campus in Mumbai, India. His primary research interests span two major areas in computing: Computer Graphics and Computer Vision . He has extensively worked in these fields with his students and research staff, producing various publications, talks, and research projects over the years. His current teaching focus includes Math for Visual Computing (CS 740), a course designed for postgraduate students new to the IIT system who may have some apprehension about mathematics. Professor Chandran has supervised numerous PhD students whose work covers diverse topics including 3D modeling, efficient computing with tomographic measurements, vision for drones, cancer prognosis, hierarchical visibility, projector-camera systems, arterial pulse analysis, and optimization algorithms for motion factorization. His teaching portfolio is extensive, having offered courses such as Basic Freshman Programming, Software Systems, Parallel Programming Paradigms, Graphics I & II, Multimedia Systems, Computer Vision, Digital Image Processing, Algorithms, and Spatial Data Structures. He has held multiple administrative and service roles at departmental, institutional, and external levels. Departmental roles include PhD Faculty Advisor, Awards Committee Chair, Faculty Search Chair, and Web Team Chair. At the institutional level, he served as Founding PMRF Coordinator, Head of the Application Software Centre, and IIT Research Fellowship Initiative Coordinator. Externally, he has coordinated the DST India Digital Heritage Project and served as Program Co-Chair for conferences like Mysore Park Vision Conference and ICVGIP. Professor Chandran is actively involved in campus community activities including Sanskriti @ IITB, Taekwando @ IITB, and serves as Secretary for Kendriya Vidyalaya PTA. His office hours are from 12:30 PM to 1:00 PM on Monday, Tuesday, and Thursday, and he emphasizes using Piazza rather than email for student communications.

Tengyu Maمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Reinforcement Learning
• +۳ مورد دیگر

Tengyu Ma is an Assistant Professor of Computer Science at Stanford University. His research focuses on machine learning, deep learning, optimization, and theoretical computer science. He is particularly known for work on neural networks, reinforcement learning, and algorithmic guarantees in AI systems. His email is tengyuma@stanford.edu . Ma's research interests span foundational aspects of machine learning, including generalization theory, optimization algorithms, and the theoretical underpinnings of deep learning. He has contributed to areas such as self-play theorem provers, learning rate schedules, and robustness in low-light vision tasks. His work often bridges theoretical insights with practical algorithm design. His recent publications emphasize advancements in large language models (LLMs), theorem proving via self-play, and understanding training dynamics in deep networks. Despite prolific output, no specific scientific awards are explicitly mentioned in the provided texts. Ongoing work includes exploring in-context learning mechanisms, formal verification of AI systems, and efficient pretraining techniques. His research has implications for both theoretical understanding and real-world applications of AI.

Grant Hoمشاهده پروفایل

استادیار

• Security and Privacy
• Machine Learning for Security
• Data Science
• +۳ مورد دیگر

Grant Ho is an Assistant Professor in the Computer Science Department at the University of Chicago. His research focuses on computer security, particularly at the intersection of data and security. Prior roles include a CSE Postdoctoral Fellowship at UC San Diego, a Visiting Researcher position at Corelight Labs, and a PhD in Computer Science from UC Berkeley (advised by Vern Paxson and David Wagner). He holds a B.S. in Computer Science from Stanford University. **Research Interests**: Enterprise security, AI/ML applications in security, large-scale threat analysis, and data-driven cybersecurity practices. His work spans detecting attacks (e.g., phishing, ransomware), improving security measures, and evaluating the efficacy of security policies. **Awards**: 2023 IEEE Euro S&P Best Paper Award, 2019 and 2017 USENIX Security Distinguished Papers, 2017 Internet Defense Prize, NSF and Facebook Fellowships, and the 2015 IEEE S&P Distinguished Practical Paper Award. **Advising & Teaching**: Current advisees include Aniket Anand (PhD), Christiana Marchese (PhD), and Robert Liu (B.S.). Taught courses include Introduction to Computer Security (CMSC 23200) and seminars on AI/ML and NLP in cybersecurity. Collaborates with industry partners like Barracuda Networks and Dropbox. **Labs & Teams**: Leads a research group focused on enterprise security challenges, emphasizing practical impact and interdisciplinary approaches.

Cecilie Schou Andreassenمشاهده پروفایل

استاد

• Behavioral Addictions
• Social Media Psychology
• Workaholism
• +۳ مورد دیگر

Cecilie Schou Andreassen is a Professor at the Department of Clinical Psychology, University of Bergen . She specializes in behavioral addictions , including workaholism, social media addiction, and substance use interactions. Email: cecilie.andreassen@uib.no Visitor Address: Alrek Health Cluster, Årstadveien 17, 5009 Bergen Research Focus: Andreassen's work examines the psychosocial antecedents of addictive behaviors, with emphasis on personality traits , workplace dynamics , and digital platform interactions . Her research spans cross-cultural validation studies and longitudinal health outcomes related to technology and substance misuse. Article Trends (2017-2022): Analyzing 15 recent publications reveals a consistent focus on addiction scale validation , social media epidemiology , and workaholism's health impacts . Key themes include measurement invariance , digital-chemical addiction comorbidity , and psychological withdrawal mechanisms . Scientific Contributions: Co-developer of Bergen Work Addiction Scale Creator of Bergen-Yale Sex Addiction Scale Leadership in behavioral addiction epidemiology Recipient of Norwegian Research Council grants Advising & Collaborations: While no direct advisees are listed, Andreassen collaborates extensively with international researchers in work psychology , social media studies , and public health . Her work involves partnerships with Nottingham Trent University , Yale University , and National Competence Service for Sleep Disorders . Labs & Teams: Affiliated with the Department of Clinical Psychology and previously with the Department of Social Psychology at University of Bergen, she contributes to national health registry studies and cross-occupational research on addiction patterns.

Jakob Meraneمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Legal Technology
• Compliance and Regulation
• +۳ مورد دیگر

Jakob Merane is a postdoctoral researcher at ETH Zurich's Professorship of Law, Economics and Business, and a visiting researcher at the Max Planck Institute and Harvard Law School. He holds a Ph.D. from ETH Zurich and law degrees from the University of Basel, with additional studies in applied statistics. His research focuses on AI-driven legal enforcement, legal technology, and compliance-by-design approaches, leveraging computational and empirical methods. Merane's work includes developing tools like SwiLTra-Bench for multilingual legal translation and LEXam for benchmarking AI legal reasoning. He has contributed to GDPR compliance studies, automation of legal enforcement processes, and quantitative analyses of Swiss legal datasets. Awards include the 2024 Young Scholar Prize from the German Law and Economics Association. Teaching responsibilities include ETH's Law & Tech course since 2020, emphasizing AI regulation and interdisciplinary collaboration between law and computer science. Merane's research also addresses AI liability in medical contexts, digital advertising regulations, and ethical AI integration in legal systems. His work bridges legal theory with practical applications, aiming to enhance justice accessibility through technology.

Imre Leaderمشاهده پروفایل

استاد

• Extremal Combinatorics
• Ramsey Theory
• Combinatorial Number Theory
• +۳ مورد دیگر

Professor Imre Leader is a distinguished mathematician at the University of Cambridge, where he serves as Professor of Pure Mathematics in the Department of Pure Mathematics and Mathematical Statistics (DPMMS), which is part of the Faculty of Mathematics. His office is located in room C2.02 at the DPMMS building. Professor Leader's research primarily focuses on Extremal Combinatorics and Ramsey Theory , two fundamental areas of discrete mathematics. His work explores deep connections between combinatorial structures, set theory, and algebraic properties. He has made significant contributions to understanding partition regularity, monochromatic structures, extremal set theory, and combinatorial geometry. His research often bridges the gap between pure combinatorics and applications in computer science and theoretical mathematics. Over his prolific career, Professor Leader has published numerous influential papers in top mathematical journals, collaborating with leading mathematicians worldwide. His work spans various aspects of combinatorics including hypergraph theory, geometric combinatorics, additive number theory, and combinatorial game theory. He has been particularly active in advancing our understanding of Ramsey-type phenomena in infinite structures and developing new techniques in extremal combinatorics. Research Group: Combinatorics Email: I.Leader@dpmms.cam.ac.uk Telephone: 01223 765902 Personal homepage: https://www.dpmms.cam.ac.uk/~ibl10

M. Granger Morganمشاهده پروفایل

استاد

• Energy Systems
• Climate Change Policy
• Risk Analysis
• +۵ مورد دیگر

M. Granger Morgan is the Hamerschlag University Professor of Engineering at Carnegie Mellon University , with appointments in the Department of Engineering and Public Policy , Department of Electrical and Computer Engineering , and H. John Heinz III College . He co-directs the NSF Center for Climate and Energy Decision Making and the Electricity Industry Center at CMU. Education: Ph.D., Applied Physics and Information Science, University of California, San Diego (1969) M.S., Astronomy and Space Science, Cornell University (1965) B.A., Physics, Harvard College (1963) His research spans science, technology, and public policy with focus areas in energy systems , climate change mitigation , electric grid resilience , and uncertainty characterization in policy analysis . Recent publications analyze hydrogen market barriers , carbon sequestration timelines , and interdependent energy infrastructure risks . Scientific leadership includes: Member, National Academy of Sciences Member, American Academy of Arts and Sciences Co-chair, NAS Report Review Committee Board member, International Risk Governance Council Foundation Advisory Board, E.ON Energy Research Center, RWTH Aachen DOE Electricity Advisory Committee member Former EPA Science Advisory Board Chair Fellow of AAAS, IEEE, and Society for Risk Analysis Contact: Office 5220 Wean Hall, Phone 412-268-2672, Email granger.morgan@andrew.cmu.edu

Sainyam Galhotraمشاهده پروفایل

استادیار

• Artificial Intelligence
• Causal Inference
• Database Systems
• +۴ مورد دیگر

Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for trustworthy analytics, integrating causal inference, data management, and machine learning to enhance robustness, explainability, and fairness in algorithmic systems. PhD: University of Massachusetts Amherst (2020), advised by Barna Saha B.Tech: Indian Institute of Technology Delhi (2014), advised by Amitabha Bagchi Postdoctoral Research: University of Chicago (Computing Innovation Fellow) His work spans artificial intelligence, causal inference, and responsible data science, emphasizing ethical algorithm design and reliable data integration. Recent publications highlight advancements in fair clustering, causal feature selection, and entity resolution frameworks. His research trends from 2023–2024 include contributions to spatio-temporal data correlation, community detection in geometric graphs, and distribution-aware dataset search. Key themes are fairness in machine learning, causal modeling, and scalable data management solutions. Computing Innovation Fellowship (2021) DAAD AInet Fellow (2021) ACM SIGMOD Entity Resolution Programming Contest Finalist (2021) Krithi Ramamritham Computer Science Scholarship (2019) BEST Paper Award in SIGSOFT FSE 2017 He actively seeks PhD or Master’s students interested in data science and trustworthy AI. Contact via email: sg@cs.cornell.edu .

Adam Bonicaمشاهده پروفایل

دانشیار

• Data Science
• Money in Politics
• Campaigns and Elections
• +۵ مورد دیگر

Adam Bonica is an Associate Professor in the Department of Political Science at Stanford University . His research integrates data science and politics , focusing on money in politics , campaigns and elections , judicial politics , and political methodology . Research Interests : Data Science, Political Ideology, Campaign Finance, Judicial Polarization, Quantitative Modeling Contact : Encina Hall West, Room 307, Stanford, CA 94305-6044 | Email : bonica@stanford.edu | Phone : (650) 725-7987 His work has been published in leading journals such as the American Journal of Political Science , Political Analysis , Journal of Economic Perspectives , Journal of Law, Economics, and Organization , and JAMA Internal Medicine . Bonica co-authored The Judicial Tug of War , which explores the politicization of the American judiciary. He has developed comprehensive databases like DIME (Database on Ideology, Money in Politics, and Elections) to advance research on political ideology and campaign finance. Recent publications include analyses of ideological persuasion in U.S. elections, judicial reform dynamics, and supervised machine learning applications in political methodology. His research spans topics such as clerk hiring as ideological indicators , professional networks in fundraising , and polarization trends among physicians and legal professionals .

• Marketing Analytics
• Business Analytics
• Statistical Analysis
• +۱ مورد دیگر

Shaonan Tian is an Associate Professor in the Department of Marketing and Business Analytics at San José State University's Lucas College and Graduate School of Business. Her office is located in BT 752, and she can be contacted via email at shaonan.tian@sjsu.edu or phone at (408) 924-7245. Her Fall 2019 office hours were scheduled for Tuesdays from 11:45AM to 12:30PM and by appointment. Her research focuses on quantitative business methodologies including Marketing Analytics , Business Analytics , Statistical Analysis , and Data Mining , as evidenced by her teaching portfolio and departmental affiliation. Professor Tian has taught courses including: BUS2 194A: Statistical Analysis (Spring 2018) focusing on analytical techniques BUS2 193: Data Mining (Spring 2018) covering data extraction and pattern recognition methodologies

Aria Fallahمشاهده پروفایل

استادیار

• Evidence-Based Surgery
• Clinical Trials
• Pediatric Epilepsy Surgery
• +۷ مورد دیگر

Dr. Aria Fallah, MD, is an Assistant Professor in Neurosurgery at the University of California, Los Angeles (UCLA), with secondary appointments in Health Policy and Management. His research focuses on Evidence-Based Surgery , Clinical Trials , and Meta-Analyses for pediatric epilepsy surgery outcomes, including prognostic tools and comparative effectiveness studies . He actively participates in international collaborations like the CTSI and has published extensively in journals such as Epilepsia , Neurology , and Clinical Neurophysiology . University: University of California, Los Angeles Department: Neurosurgery Email: afallah@mednet.ucla.edu Dr. Fallah’s research integrates machine learning and deep learning to analyze high-frequency oscillations in epilepsy, aiming to refine diagnostic and therapeutic strategies. His recent work includes developing tools like PyHFO for oscillation detection and HOPS calculator for predicting seizure freedom after hemispherectomy. His publications highlight collaborations across institutions in pediatric epilepsy surgery , hemimegalencephaly , and thalamic neuromodulation . While no explicit awards or student advisement are listed, his contributions span clinical trials , neuroimmunology , and global neurosurgery initiatives , including work in Haiti.

Xiaoming Liuمشاهده پروفایل

استاد

• Computer Vision
• Pattern Recognition
• Image and Video Processing
• +۴ مورد دیگر

Xiaoming Liu is the Anil K. and Nandita Jain Endowed Professor of Engineering and MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University . Holding a Ph.D. from Carnegie Mellon University (2004), he leads cutting-edge research in computer vision and machine learning. Research Interests : Computer Vision Pattern Recognition Image and Video Processing Machine Learning Medical Image Analysis Multimedia Retrieval Recent Research Trends : Focus on 3D object detection and depth estimation Development of robust biometric recognition systems Integration of radar-camera fusion for autonomous systems Advancements in self-supervised and multimodal learning Exploration of adversarial AI security Creation of interpretable forgery detection frameworks Teaching : Spring 2013: CSE891-006 Computer Vision Seminar Fall 2012-2015: CSE803 Computer Vision Spring 2014-2017: CSE 471 Media Processing and Multimedia Contact Information : Email: liuxm@cse.msu.edu Office: EB 3137, Michigan State University Phone: +1 (517) 355-2359