جستجوی استاد راهنمای دانشگاهی

Michelle Borkinمشاهده پروفایل

استادیار

• Data Visualization
• Human-Computer Interaction
• Visual Analytics
• +۵ مورد دیگر

Michelle Borkin is an Assistant Professor in the Khoury College of Computer Sciences at Northeastern University’s Boston campus, where she co-leads the Visualization @ Khoury Lab and co-directs the Northeastern Visualization Consortium (NUVis). She additionally serves as Affiliated Faculty with the NULab for Text, Maps, and Networks and with the Information Design & Data Visualization Program in the College of Arts, Media, and Design. Education PhD, Applied Physics, Harvard University School of Engineering and Applied Sciences (2014) MS, Applied Physics, Harvard University BS, Astronomy & Astrophysics and Physics, Harvard University Research Interests Borkin’s research integrates data visualization and human-computer interaction to create novel techniques that enable discovery across disciplines. Her work spans: Multidimensional brushing-and-linking methodologies 3D data visualization and selection techniques Tree and network visualization Visualization evaluation methodologies and perception/cognition theory Accessibility and visualization for social good Medical and astrophysical visualization applications Publication Trends Across more than 50 peer-reviewed papers, Borkin’s research exhibits three dominant threads: (1) foundational studies on visualization perception and memorability, (2) design and evaluation of novel interactive tools for complex data (medical, astronomical, political, and social media), and (3) methodological contributions such as the Design Study “Lite” Methodology that accelerate visualization pedagogy and community-engaged research. Awards & Honors CHI 2020 Best Paper Award IEEE VIS 2020 Best Poster Honorable Mention IEEE VIS 2018 Best Poster Award NSF Graduate Research Fellowship NDSEG Graduate Fellowship TED Fellow Advising & Grants Borkin currently advises five PhD students—Jane Adams, Mackenzie Creamer, Franc O, Aditeya Pandey, and Laura South—and has previously mentored Michail Schwab and Uzma Haque Syeda. Her research has been supported by NSF, NDSEG, and TED fellowships, as well as internal Northeastern awards. Labs & Teams Co-Lead, Visualization @ Khoury Lab Co-Director & Co-Founder, Northeastern Visualization Consortium (NUVis) Affiliated Faculty, NULab for Text, Maps, and Networks Affiliated Faculty, Information Design & Data Visualization Program, CAMD

Brian Ziebartمشاهده پروفایل

استاد

• Machine Learning
• Robotics
• Assistive Technologies
• +۳ مورد دیگر

Brian Ziebart is a Professor in the Department of Computer Science at the University of Illinois at Chicago. He earned his Ph.D. in Machine Learning from Carnegie Mellon University in 2010. Research Interests: Machine Learning, Robotics, Assistive Technologies, Human-Computer Interaction, Adversarial Prediction, Inverse Optimal Control, Structured Prediction. Key Grants: NSF CAREER (RI)-1652530, NSF EAGER (SCH)-1650900, NSF IIS-1526379, NSF III-1514126, Future of Life Institute grant, NSF NRI-1227495. Notable Awards: Best Paper Runner-Up (ECCV, 2012), Best Paper Award (ICML, 2011), CMU School of Computer Science Dissertation Honorable Mention (2011). Teaching & Leadership: Senior Lecturer at CMU, actively involved in mentoring students and leading research teams.

Yicheng Songمشاهده پروفایل

استادیار

• Personalized Recommender Systems
• Digital Consumer Analytics
• Charity Analytics
• +۳ مورد دیگر

Yicheng Song serves as an Assistant Professor in the Department of Information & Decision Sciences at the Carlson School of Management, University of Minnesota. His research develops personalization technologies using machine learning and structural economic models to enhance user satisfaction and business revenue through data-driven solutions. His educational background includes: PhD in Business (2017), Questrom School of Business, Boston University PhD in Computer Science (2012), Institute of Computing Technology, Chinese Academy of Sciences BA in Computer Science (2006), Wuhan University Dr. Song's research specializes in Personalized Recommender Systems, Digital Consumer Analytics, and Charity Analytics. He develops advanced machine learning frameworks to address information overload in digital platforms, with applications spanning e-commerce, customer journey optimization, and nonprofit donation systems. His work uniquely bridges technical innovation in AI with practical business impact through structural economic modeling. Analysis of his publication trajectory (2011-2024) reveals consistent focus on personalization algorithms, evolving from multimedia geolocation to reinforcement learning for customer interventions. Recent work emphasizes explainable AI in donor matching systems and multi-category utility modeling, demonstrating increasing sophistication in handling complex consumer behavior data across digital and charitable contexts. His research excellence has been recognized with prestigious awards: Best Paper Award at INFORMS CIST 2018 Best Paper Award at WITS 2014 Runner-up for Best Paper Award at INFORMS CIST 2023 While specific grant details and student advising records aren't publicly listed, his publications indicate active collaboration with researchers in marketing, operations, and computer science. The absence of laboratory information suggests integration within the Carlson School's existing research infrastructure rather than standalone facilities.

Henning Piezunkaمشاهده پروفایل

دانشیار

• Competition
• Collaboration
• Crowdsourcing
• +۳ مورد دیگر

Henning Piezunka is an Associate Professor of Management at The Wharton School, University of Pennsylvania. He holds a PhD from Stanford University, a Master of Science from the London School of Economics, and a Diploma Kaufmann from the University of Mannheim. Before academia, he co-founded and led a web design company for 18 years, growing it to 30+ employees serving 80+ countries before its sale in 2016. His research examines: Competition and collaboration dynamics in entrepreneurial firms, family businesses, and sports contexts Crowdsourcing innovation and platform strategies Organizational decision-making structures and learning processes CEO succession planning and its organizational impacts His recent publications (2019-2025) demonstrate methodological diversity, combining archival analysis of Formula One/soccer data, crowdsourcing platform experiments, and organizational case studies. Key thematic focuses include: how competition manifests in collaborative settings, AI's role in strategic learning, and how organizational structures shape individual behavior. Awards & Honors: Wharton Teaching Excellence Award (2023) Emerging Scholar Award, TIM Division, Academy of Management (2022) Poets & Quants Best 40 Under 40 Professor (2019) Multiple teaching commendations for MBA/EMBA courses (2014-2023) He teaches core entrepreneurship courses including MGMT2300 (Entrepreneurship) and MGMT2310 (Entrepreneurship Launchpad), focusing on venture creation, resource acquisition, and scaling strategies. He also leads doctoral seminars on research design and maintains an active advisory practice through the 'Between the Lines' webinar series featuring business school authors.

• Scholarly Communication
• Information Science
• Research Evaluation
• +۵ مورد دیگر

Ángel M. Delgado-Vázquez serves as Associate Professor in Library and Information Science at Pablo de Olavide University, concurrently holding the position of Head of Learning and Research Support Services at the university's Library/CRAI. He is formally affiliated with the Department of Geography, History and Philosophy while coordinating the Official Master's Degree in History and Digital Humanities and directing the Postgraduate Certificate in Research Support Services. His academic credentials include a Humanities degree from Pablo de Olavide University, a Library and Information Science degree from Universitat Oberta de Catalunya, and a Master's in Libraries and Digital Information Services from Universidad Carlos III de Madrid. These qualifications underpin his specialization in scholarly communication infrastructure and research evaluation systems. Delgado-Vázquez focuses on the intersection of digital literacy, open science, and responsible research assessment, with particular expertise in bibliometric methodologies and academic publishing ethics. His work addresses critical challenges in scholarly communication including AI integration in research workflows, metadata standardization for scientific journals, and ethical surveillance mechanisms within research support ecosystems. Over fifteen years, he has developed training programs for all academic levels on research data management and scholarly publishing practices. Analysis of his recent publications reveals a pronounced trend toward reforming scientific evaluation frameworks, with 70% of 2023-2025 works examining CoARA principles, narrative bibliometrics, and the implications of journal retractions ('Fallen Journals'). His research consistently emphasizes practical solutions for Spanish academia within evolving European open science policies, particularly regarding ANECA accreditation procedures and sexenios evaluation criteria. As an institutional leader, he contributes to national higher education policy through membership in ANECA's Evaluation and Monitoring Commission and previously collaborated with the EDUINNO Eduinnovagogía research group. His service initiatives include designing professionalization programs for research support staff and advising on digital competence frameworks for university students and researchers.

• Semantic Web
• Knowledge Representation
• Artificial Intelligence
• +۶ مورد دیگر

Deborah L. McGuinness is the Tetherless World Senior Constellation Chair and Professor of Computer, Cognitive, and Web Sciences at Rensselaer Polytechnic Institute (RPI). She serves as founding director of the Web Science Research Center, focusing on next-generation ontology-enabled research infrastructure for interdisciplinary applications. Leaders in Semantic Web and AI research Bridging AI with eScience and healthcare Developer of semantic frameworks for data-intensive resource efforts Her research spans artificial intelligence, knowledge representation, clinical decision support systems, and ontology engineering. She investigates how semantic technologies can enhance AI explainability, data interoperability, and interdisciplinary science. Her recent publications highlight trends in AI explainability frameworks Knowledge graph construction Clinical decision support Commonsense reasoning benchmarks Health informatics Data harmonization Scientific awards include Fellow of the American Association for the Advancement of Science (AAAS) Robert Engelmore Award from the Association for the Advancement of Artificial Intelligence (AAAI) She leads large data-intensive research efforts and has contributed to projects involving blockchain integration with semantic web standards, FAIR data principles, and incentivized research data sharing mechanisms.

Nichole Kellyمشاهده پروفایل

دانشیار

• Health Psychology
• Eating Behavior
• Body Image
• +۵ مورد دیگر

Nichole Kelly is an Evergreen Associate Professor at the College of Education , University of Oregon. She is affiliated with multiple departments including Counseling Psychology, Couples and Family Therapy, Family and Human Services, and Prevention Science. Postdoctoral Research Fellowship, Behavioral Health Psychology (2013-2016), Uniformed Services University and NIH PhD in Counseling Psychology (2013), Virginia Commonwealth University BA in Psychology (2004), University of Virginia Her research focuses on eating behaviors , body image , weight stigma , and chronic disease risk . She investigates cognitive and emotional mechanisms of eating behaviors linked to mental health and disease risk, using diverse methods such as test meals , ecological momentary assessments , and neuropsychological evaluations . Her work emphasizes understudied populations like men, rural communities, and ethnically/racially diverse groups. The 15 most recent articles reflect trends in health psychology , pediatric behavioral health , and culturally-informed interventions . Key subfields include disordered eating pathology , social media impacts , weight stigma reduction , and ecological frameworks . Her studies often integrate experimental designs , network analyses , and public health data . Labs & Teams : Leads The Renew Lab , focusing on health equity through psychological science. The lab develops interventions targeting systemic bias , health disparities , and culturally-sensitive practices .

Xia Ningمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Xia Ning is a Professor jointly appointed in the Department of Computer Science and Engineering , the Division of Medicinal Chemistry and Pharmacognosy (College of Pharmacy), and the Department of Biomedical Informatics at The Ohio State University . She also holds affiliation with the Translational Data Analytics Institute at OSU. Education: Ph.D. in Computer Science & Engineering, University of Minnesota, Twin Cities (2012) M.S. in Computer Science, University of Minnesota, Twin Cities M.S. in Statistics, University of Minnesota, Twin Cities B.S. in Computer Science, Chu Kechen Honors College, Zhejiang University, China Research Focus : The Ning Lab pioneers data-driven Artificial Intelligence, Machine Learning, and Big-Data analytics with targeted applications in drug discovery, medical informatics, health informatics, and e-commerce . Recent thrusts include generative AI for molecule design, graph neural networks for retrosynthesis, large-language models specialized for chemistry (LlaSMol) and e-commerce (eCeLLM), and reinforcement-learning frameworks for precision-medicine drug selection. The lab’s methodologies are intentionally generalizable, enabling spill-over benefits to domains such as social networks and system monitoring. Publication Trends : Over the past four years Professor Ning has released a steady stream of high-impact articles spanning retrosynthesis planning, LLM instruction tuning for scientific domains, reinforcement learning for drug discovery, and COVID-19 health-analytics . These works repeatedly integrate cutting-edge AI techniques (deep RL, graph Transformers, large-scale instruction datasets) with rigorous experimental validation in chemistry and biomedicine. Scientific Awards & Honors : Sanofi iDEA-TECH Award (2024) 10-Year Highest-Impact Award, International Conference on Data Mining (ICDM, 2020) Grants & Collaborations : Funding includes the Sanofi iDEA-TECH Award and collaborative grants with Amazon Web Services for COVID-19 knowledge graphs. Her open-source datasets (ECInstruct, SMolInstruct, CTKG) and models (G2Retro, LlaSMol, eCeLLM) are publicly released on HuggingFace and GitHub, fostering broad academic and industrial adoption. Labs & Teams : Professor Ning heads the Ning Lab at OSU, a multidisciplinary team focusing on AI/ML methodology and translational applications in health and medicine. The lab actively releases code and interactive web portals to accompany each major publication.

• Machine Learning
• Datasets
• Reliable Generalization
• +۵ مورد دیگر

Ludwig Schmidt is an Assistant Professor in the Computer Science Department at Stanford University and a member of Stanford Data Science. He also serves as a member of the technical staff at Anthropic and LAION, contributing to both academic and industrial research in machine learning. Dr. Schmidt completed his PhD at MIT, where he received the prestigious George M. Sprowls Award for best PhD theses in computer science, followed by a postdoctoral position at UC Berkeley. His educational background provides a strong foundation for his research at the intersection of theoretical and applied machine learning. Dr. Schmidt's research focuses on the empirical foundations of machine learning, with particular emphasis on datasets, reliable generalization, multimodality, and language models. His work addresses critical challenges in ensuring machine learning models perform consistently across different domains and data distributions. His research group has made significant contributions to open source machine learning through projects like OpenCLIP, DCLM, and the LAION-5B dataset, which have become important resources for the machine learning community. An analysis of Dr. Schmidt's recent publications reveals a strong focus on dataset quality, multimodal learning, and language model training. His work spans from fundamental research on generalization and robustness to practical applications in vision-language systems and tabular data. A recurring theme is the importance of high-quality, diverse datasets for training robust machine learning models, with several papers addressing dataset curation, evaluation methodologies, and the impact of data quality on model performance. New Horizons Award at EAAMO Best paper awards at ICML & NeurIPS Best paper finalist at CVPR Sprowls dissertation award from MIT (George M. Sprowls Award) Dr. Schmidt actively mentors doctoral students and postdoctoral researchers. His current advisees include doctoral candidates Liangyu Chen, Shiye Su, Elaine Sui, Audrey Xie, John Yang, Yuhui Zhang, and Wanjia Zhao. He serves as Doctoral Dissertation Reader for Kyle Hsu and Aishwarya Mandyam, and as Postdoctoral Faculty Sponsor for Benjamin Feuer and Mike Merrill. His research has attracted significant funding that supports these students and enables his group to contribute to open source projects like OpenCLIP and LAION-5B. Dr. Schmidt leads a research group focused on empirical machine learning foundations. The group actively contributes to open source machine learning through code repositories and datasets, including OpenCLIP, OpenFlamingo, LAION-5B, and the DataComp datasets. Their work bridges theoretical insights with practical applications, developing tools and resources that advance the entire machine learning community.

• Educational Technology
• Creative Programming
• Video Game Design
• +۶ مورد دیگر

Pedro Neves Rito is an Associate Professor at the Department of Communication and Art within the School of Education at the Polytechnic Institute of Viseu, where he has been teaching since 2007. His teaching focuses on web programming, creative programming, microcontroller programming, sensors, and ICT training for pre-school and primary school teachers. He is also a member of the CI&DEI Research Group and has served as Coordinator of the Information and Communication Technologies Area since 2022. His educational background includes: Doctorate in Information Technologies and Systems from the University of Minho (2015) Master's degree in Multimedia in Education from the University of Aveiro (2007) Degree in Computer Engineering from the Instituto Superior de Engenharia de Coimbra Numerous professional certifications including Adobe Certified Expert in Dreamweaver CS3 and Flash CS3 Rito's research spans multiple innovative areas at the intersection of technology and education. His primary interests include the adoption and diffusion of technologies, creative programming and application development, video game design, and tangible interfaces. He has extensively explored how gamification techniques can enhance learning experiences, particularly in programming education, and has investigated the potential of augmented reality in educational contexts. His work often focuses on practical applications for classroom settings, especially for pre-school and primary school teachers. His recent publications show a strong trend toward integrating artificial intelligence in educational game design, with particular emphasis on STEAM education and programming concepts. He has conducted systematic reviews on the educational potential of video games and developed frameworks for designing educational mobile video games. His research consistently emphasizes practical implementation strategies for educators, with a growing focus on AI applications in educational settings. Rito actively supervises numerous graduate students across various programs, particularly in Arts, Multimedia, and Education fields. He has led and participated in multiple research projects including "dEweB - Digital Era: WEB 3.0 and beyond," "Smart City Kids Lab," and "Eco-sensors4Health." His work demonstrates a commitment to applying technology innovations in real educational settings through practical implementation and teacher training.

Ray Drainvilleمشاهده پروفایل

مدرس

• Digital Media
• Visual Culture
• Iconography
• +۳ مورد دیگر

Dr. Ray Drainville is a lecturer at the University of Waterloo, specializing in digital media and visual culture. His research explores the intersection of iconography, social media image analysis, and machine learning applications. With nearly two decades of industry experience in web development and graphic design, he brings practical insights to his teaching on contemporary digital visual culture. PhD in Visual Culture from Manchester School of Art, Manchester Metropolitan University (2018) MA in Information Studies from University of Sheffield (1996) MA in History of Art from Princeton University (1995) BA in History of Art from New College (1992) Dr. Drainville's research interests include digital media, visual culture, iconography, media theory, and hermeneutics. His work increasingly examines linguistic and visual dogwhistles in political contexts, memetic superposition, and algorithmic iconography. He has published in journals such as AI & Society , Studies In Communication Sciences , and Hyperallergic , often combining historical art analysis with contemporary digital platforms. He teaches courses including: GBDA 101 Introduction to Digital Media Design GBDA 203 Introduction to Digital Culture GBDA 228 Digital Imaging of Online Applications GBDA 301 Global Digital Project 1 GBDA 401 Cross-Cultural Digital Business GBDA 402 Capstone Course: Cross-Cultural Digital Business ARTS 290 Theories of Media

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

XU Jingjun Davidمشاهده پروفایل

استاد

• Human-computer interaction
• Artificial Intelligence
• Recommendation systems
• +۵ مورد دیگر

Professor David Xu is a distinguished faculty member in the Department of Information Systems at City University of Hong Kong, where he has served as Professor since 2023 after progressing from Associate Professor (2017-2023). Prior to joining CityU, he held academic positions at Wichita State University from 2011-2017, culminating in the Bomhoff Endowed Professor of Business title in 2017. His educational background includes a PhD in Management Information Systems from the University of British Columbia (2011), an MPhil in Information Systems from City University of Hong Kong, and a First-class honors BBA in Business Administration from Lingnan University. As Programme Leader for both BBA Information Management and Bachelor's Degree in Information Systems programs since 2018, he plays a significant administrative role in curriculum development. Professor Xu's research spans human-computer interaction, artificial intelligence applications, and technology adoption across diverse domains. With over 90 publications including 40+ journal papers in top-tier venues like MIS Quarterly and Information Systems Research, his work demonstrates exceptional scholarly impact. His Google Scholar metrics (3,300+ citations, h-index of 22) reflect substantial influence in the field. His recent publications reveal a strategic focus on AI ethics, information cocoon mitigation in social media, healthcare applications of AI, and digital transformation effects on business. The work spans theoretical contributions and practical implementations, with increasing emphasis on societal impacts of technology. AIS Early Career Award (2018) AIS Distinguished Member – Cum Laude (2020) Multiple teaching excellence awards (2021, 2024, 2025) ICIS and ISR Best Associate Editor Awards (2020-2021) Numerous paper award nominations across major conferences Professor Xu has secured significant research funding including NSFC, RGC GRF, and CityU Strategic Research Grants totaling millions in funding. His current projects address critical issues like AI beauty filters, depression treatment systems, and information cocoon mitigation. As Senior Editor for Information Systems Journal and Associate Editor for Information Systems Research, he shapes the field's scholarly discourse while supervising DBA and PhD students across multiple programs.

Michael Sirivianosمشاهده پروفایل

دانشیار

• Cybersecurity
• Social Media Analysis
• Disinformation Detection
• +۵ مورد دیگر

Michael Sirivianos is an Associate Professor at the Cyprus University of Technology (CUT), where he serves as Dean of the School of Engineering and Technology. He holds a PhD in Computer Science from Duke University (2010) and leads research in cybersecurity, disinformation detection, and social media analysis. He coordinates multiple EU-funded projects including ReCRED (Horizon 2020) and ENCASE (Marie Curie RISE), securing over €3M in research funding. Research Focus His work spans: Cybersafety : Detection of cyberbullying, hate speech, and inappropriate content targeting children Trust Systems : Device-centric authentication and blockchain applications Disinformation Analysis : Graph-based detection of fake news and state-sponsored manipulation Scalable Systems : Distributed databases and network infrastructure Achievements & Recognition Best Paper Award (2019) for work on state-sponsored disinformation Distinguished Paper (2018) for fringe web community analysis Spotlight Session recognition (2020) for child protection research Featured in NYT, Washington Post, and Wired for YouTube content analysis Leadership Co-directs the Network Systems Research Lab, serves on the Board of CYENS Centre of Excellence, and coordinates the Fact-check Cyprus Centre against Disinformation.

• Statistical Analysis
• Stochastic Processes
• Applied Statistics
• +۸ مورد دیگر

Prof. Dr. Kumru Didem Atalay is a distinguished academic at Başkent University, specializing in Industrial Engineering . With a PhD in Statistics from Ankara University (2007), she has made significant contributions to Operations Research , Fuzzy Logic , and Decision Support Systems . Her work bridges statistical analysis with real-world applications in healthcare logistics, pandemic response, and manufacturing optimization. Education: PhD (2007), MS (2000), BS (1998) in Statistics from Ankara University Current Role: Professor in Industrial Engineering at Başkent University Her research focuses on stochastic processes , fuzzy modeling , and healthcare operations , particularly in pandemic-era service quality and microchannel manufacturing. She has developed innovative methods for project scheduling , risk analysis , and multi-criteria decision-making . Recent publications examine Covid-19's impact on education quality and fuzzy linear programming for project scheduling . She applies intuitionistic fuzzy models to optimize manufacturing systems and hesitant fuzzy regression for pandemic death count estimation. Scientific recognition includes a Runner-up Prize at the 15th ICMSEM (2021) and a Bronze Medal at ISIF21 (1970). She supervises advanced research on topics like multi-trip home healthcare routing and fuzzy quality function deployment .