جست‌وجوی استاد و پژوهشگر

Daniela Strenkertمشاهده پروفایل

استادیار

• Plant Biology
• Systems Biology
• Molecular Biology
• +۱۲ مورد دیگر

Daniela Strenkert is an Assistant Professor at Michigan State University, affiliated with the MSU-DOE Plant Research Laboratory, Plant Biology Department, Molecular Plant Sciences Program, BioMolecular Science Gateway, and Cell & Molecular Biology Program. Her research focuses on systems biology approaches to understand gene regulation in photosynthetic organisms. Ph.D., University of Kaiserslautern, Germany Her lab investigates photosynthetic performance through multi-omics analysis of chromatin structure, transcriptomes, proteomes, and metabolomes in Chlamydomonas reinhardtii . Key areas include environmental acclimation, histone modification mapping (GreENCODE project), and regulatory RNA characterization. Recent publications emphasize computational modeling of photosynthetic protein interactions, metal homeostasis under stress, and chloroplast protein import mechanisms. Articles span 2025-2010, with 15 most recent from 2025-2022. Her work integrates genome-wide datasets to decode algal regulatory programs under climate change-relevant stressors. She teaches BS 161: Cells and Molecules and maintains a lab at 106 Plant Biology Lab. Contact: strenke2@msu.edu .

Chu (Ivy) Dangمشاهده پروفایل

استادیار

• quantitative marketing
• economics of information
• consumer search
• +۹ مورد دیگر

Professor Chu (Ivy) Dang is an Assistant Professor of Marketing at the Business School of The University of Hong Kong, where she has been teaching since 2020. Her research focuses on the economics of information in quantitative marketing, examining how consumers search for information, how this information influences their choices, and the information provision strategies of firms in digital environments. Business School, The University of Hong Kong Assistant Professor of Marketing Specializes in consumer behavior in digital contexts Professor Dang received her Ph.D. in Marketing from The Chinese University of Hong Kong, where she also earned an M.S. in Economics. Her undergraduate degree is a B.S. in Applied Physics from Beijing Jiaotong University. Prior to her business studies, she spent two years conducting research in quantum information at RB Liu Lab as a Hong Kong PhD Fellowship Scheme (HKPFS) candidate in physics. Her research spans multiple dimensions of consumer behavior in digital environments, with particular emphasis on consumer search behavior and information economics. She investigates how consumers acquire and process information in online contexts, with applications to social media marketing where she examines the effects of Marketer-Generated Content (MGC), User-Generated Content (UGC), and increasingly, AI-Generated Content (AIGC). Her work on emerging trends in live-commerce and influencer marketing has provided new insights into how these formats reshape consumer decision processes. Analysis of her publications reveals a consistent focus on empirical methods to study information economics, with increasing attention to social media dynamics and emerging e-commerce formats. Professor Dang has secured significant research funding as Principal Investigator, including a General Research Fund grant (#17506824) and an Early Career Scheme grant (#27504221) from the Hong Kong Research Grants Council. She also leads projects funded by the HKU Business School Shenzhen Research Institutes and the HKU Seed Fund for Research. She recently co-organized the 14th Consumer Search and Switching Costs Workshop in Hong Kong in June 2025, demonstrating her leadership in this specialized research area. Her research has been published in top-tier journals including Journal of Marketing Research, Information Systems Research, and Marketing Science. Her teaching portfolio includes Social Media Marketing at both undergraduate and Master's levels, where she brings her cutting-edge research insights into the classroom to prepare students for the rapidly evolving digital marketing landscape. In her personal time, Professor Dang enjoys running, hiking, and spending time with her family.

Christos Makrisمشاهده پروفایل

دانشیار

• Data Structures
• Information Retrieval
• Data Mining
• +۵ مورد دیگر

Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.

Sarah CHAN Hian Mayمشاهده پروفایل

پژوهشگر ارشد

• Environmental Psychology
• Computational Social Science
• Urban Sustainability
• +۴ مورد دیگر

Sarah CHAN Hian May is a Research Fellow at the Lee Kuan Yew Centre for Innovative Cities (LKYCIC), Singapore University of Technology and Design (SUTD), under the Chan Heng Chee Research Fellowship. She holds a Ph.D. in Interdisciplinary Studies from Nanyang Technological University (NTU) and a B.A. (Hons) in Economics from NTU. Her research focuses on environmental psychology, exploring human-environment interactions across natural, built, and virtual domains. Key themes include urban sustainability, virtual reality applications, and behavioral change mechanisms to bridge environmental and technological challenges. Education Ph.D., Interdisciplinary Graduate Programme, Nanyang Technological University (2022) B.A. (Hons) in Economics, Nanyang Technological University (2017) Research Projects She collaborates with Dr. Neo Harvey on the 'Leveraging Shared Experience of Urban Heat' project, addressing climate resilience in Singapore. Her work integrates computational methods to analyze digital self-expression, emotions, and landscape perceptions. Recent studies include the impact of virtual nature on stress reduction and pro-environmental attitudes through metaverse interventions. Grants & Collaborations Recipient of Chan Heng Chee Research Fellowship Active collaborations with institutions like NTU's School of Social Sciences and interdisciplinary teams at LKYCIC Lab & Team Involvement Contributes to urban resilience and computational social science research teams, focusing on data-driven solutions for environmental and social challenges.

Hailiang Chenمشاهده پروفایل

استاد

• Artificial Intelligence
• FinTech
• Social Media
• +۸ مورد دیگر

Hailiang Chen serves as Professor in Innovation and Information Management, Assistant Dean (Taught Postgraduate), and Director of the Artificial Intelligence Research Institute at HKU Business School, The University of Hong Kong. His academic journey includes a PhD and MS from Purdue University and a BM from Tsinghua University. Doctoral Degree: Management Information Systems, Purdue University Master Degree: Economics, Purdue University Bachelor Degree: Information Management and Information Systems, Tsinghua University Professor Chen's research spans artificial intelligence, FinTech, social media analytics, and platform economics, with significant contributions to understanding how digital interactions shape financial markets and consumer behavior. His work frequently examines the intersection of technology adoption and economic outcomes, particularly in cryptocurrency markets, live-stream commerce, and venture capital decision-making. His research methodology combines large-scale data analysis with experimental designs to uncover causal relationships in digital ecosystems. His publications in elite journals like Journal of Financial Economics and Management Science demonstrate consistent impact, with multiple ESI Highly Cited Papers. Current projects include Gov-RAG for e-government services and comparative studies of AI search tools. His research has received continuous funding from Hong Kong's Research Grants Council for five consecutive years (2019-2023). Faculty Outstanding Researcher Award, HKU Business School (2022-23) INFORMS ISS Sandra A. Slaughter Early Career Award (2022) Association for Information Systems Early Career Award (2019) Three ESI Highly Cited Papers (Top 1% in field) Professor Chen actively contributes to academic service as Associate Editor for Journal of Management Information Systems and MIS Quarterly , and serves as Program Chair for the International Conference on Smart Finance. His industry collaborations include Alibaba, HSBC, and China Construction Bank, bridging academic research with real-world business applications in AI implementation and digital transformation.

Elizabeth Clareمشاهده پروفایل

دانشیار

• Environmental DNA
• Biodiversity Monitoring
• Response of Species to Habitat Change
• +۴ مورد دیگر

Elizabeth Clare is an Associate Professor in the Department of Biology at York University, affiliated with the Faculty of Science. Her research focuses on developing novel technologies to monitor biodiversity and assess ecosystem responses to environmental change, particularly using environmental DNA (eDNA). She pioneered airborne DNA sampling to study terrestrial biodiversity at continental scales and has contributed to BIOSCAN, a global biodiversity program. Research Themes: Biodiversity monitoring, species interactions, environmental change resilience, bat biology, tropical ecosystems. Technological Innovations: Airborne eDNA, iDNA from leeches, and mobile lab sequencing in remote locations. Her work has been featured in Science , Nature , and media outlets like Wired and NPR . She teaches courses in evolution, ecology, and conservation biology, emphasizing critical thinking and applied research. Recent grants include NSERC and Genome Canada funding for airborne DNA projects. Clare collaborates globally, with fieldwork in Belize, South America, and Southeast Asia. Her lab's 'airDNA' technology has revolutionized biodiversity surveys, leveraging existing air-quality networks for ecological insights. She advises students on projects like urban bat ecology and BIOSCAN applications. Awards include election to the Royal Society of Canada (2023) and recognition for teaching innovations like the BioAudio podcast. Her lab also develops open-access tools, such as 3D-printable eDNA filters.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Min Peng is a Professor at Wuhan University's School of Computer Science. His research focuses on artificial intelligence, machine learning, natural language processing, and knowledge graphs. He has collaborated extensively with institutions like Hefei University of Technology and the University of Chinese Academy of Sciences. His work bridges theoretical advancements in AI with practical applications in finance, social media analysis, and network optimization. Recent contributions include neural-symbolic reasoning frameworks, contrastive learning for knowledge graphs, and financial benchmarking with large language models. Research interests emphasize scalable machine learning models for complex reasoning tasks, explainable AI, and domain-specific applications in finance and social networks. Over 100 publications span venues like WWW, ACL, and NeurIPS, highlighting interdisciplinary impact. Notable projects include SymAgent (neural-symbolic agent frameworks), PIXIU (financial LLM benchmark), and DTC (commonsense machine comprehension). Key technical trends include integrating large language models with structured data, temporal knowledge graph reasoning, and transfer learning across domains. His work often addresses real-world challenges in data efficiency, interpretability, and cross-domain scalability. Current efforts explore financial LLMs, agent-based reasoning systems, and multimodal applications. While no specific grants or awards are listed in the provided data, his prolific publication record indicates sustained research excellence. Collaboration networks include teams in computer science, electrical engineering, and finance disciplines.

Francisco Benitaمشاهده پروفایل

مدرس

• Data Science & Analytics
• Optimisation & Decision Science
• Economics & Public Policy
• +۱ مورد دیگر

Francisco Benita is an Adjunct Lecturer at the Engineering Systems and Design (ESD) Pillar of Singapore University of Technology and Design (SUTD). He holds a PhD in Engineering Sciences from Monterrey Tech (2016) and an MSc in Industrial Economics from Universidad Autónoma de Nuevo León (2012). Prior to SUTD, he was a postdoctoral fellow at SUTD’s Architecture and Sustainable Design Pillar and a Senior Advisor at the ITESM-BMGI Lean Six Sigma Program. His research focuses on urban systems, optimization, data science, and their intersections with economics and public policy. Key areas include transportation networks, spatial livability indices, and pandemic impacts on urban environments. Benita’s interdisciplinary work spans fields like sustainable urban design, carbon emissions modeling, and global trade dynamics. Recent publications highlight trends in transportation innovation (e.g., ride-sharing impacts, aircraft routing frameworks), climate-resilient urban planning (e.g., walkway thermal comfort), and pandemic analysis. His projects often integrate quantitative methods with real-world data, emphasizing actionable insights for policymakers and urban planners. Though no scientific awards are explicitly mentioned, his extensive international collaborations—including research visits to TU Berlin, Vrije Universiteit Brussel, and Supélec—reflect his global academic engagement. Students and grants are not listed in the provided texts. Benita’s work is anchored in labs/teams within SUTD’s ESD Pillar, though specific lab affiliations are not detailed. His research bridges theoretical optimization with practical urban challenges, contributing to both academic discourse and applied solutions in smart cities.

Ranjit Lallمشاهده پروفایل

دانشیار

• International Political Economy
• Political Economy of International Cooperation
• Technological Change
• +۴ مورد دیگر

Ranjit Lall is an Associate Professor of International Political Economy at the University of Oxford's Department of Politics and International Relations, and a Fellow of St John's College. His research focuses on international cooperation, development, technological change, and methodological innovations in machine learning and missing data analysis. He holds a PhD from Harvard University and a BA from Oxford, and has been recognized with the Merze Tate Award and Leamer-Rosenthal Prize for his work. Education : PhD in Government (Harvard University), BA in Philosophy, Politics, and Economics (University of Oxford) Affiliations : St John's College Fellow, Oxford's International Relations Network His research explores how international institutions function, leveraging computational tools like MIDASpy for missing data imputation. Key interests include civil society influence on global governance, accountability mechanisms, and the political economy of technological change. He previously worked at the Bank of England and Financial Times before academia. Recent Research Trends : Articles emphasize institutional performance metrics, pandemic-era voting behavior, and AI governance frameworks. His work bridges theoretical political science with practical computational methods. Awards : 2020 Leamer-Rosenthal Prize, 2018 Merze Tate Award Advising : Supervises six graduate students in international relations and political economy Lall collaborates on open-source projects such as the MIDAS software for data imputation and actively contributes to debates on transparent social science research practices.

• Sensory Impairment
• Ageing and Cultural Inclusion
• Accessible and Inclusive Technology
• +۷ مورد دیگر

Simon Hayhoe is a Reader in Education at the University of Exeter's School of Education and an Associate of the Scottish Sensory Centre, University of Edinburgh. His work focuses on sensory impairment, ageing, inclusive technologies, and participatory research methodologies. He has held roles at the University of Bath (2016-2023), Canterbury Christ Church University, and Sharjah Women’s College, UAE. His research has been supported by a Horizon 2020 grant and a Fulbright Fellowship, among others. Education: PhD in Education (University of Birmingham, 2006), PGCE in Secondary Technology (University of Bath, 1997), MEd (University of Leicester, 1995), BA in Technical Communication (Coventry Polytechnic, 1993). His research interests include sensory impairment philosophies, accessible museum technologies, and inclusive education policies. Notable projects include the ARCHES initiative on cultural heritage accessibility and the Sound Pad Project, which co-created inclusive technologies with marginalized communities. He has delivered keynotes at institutions like MIT, Harvard, and the Metropolitan Museum of Art, and serves on editorial boards for journals such as British Journal of Visual Impairment and Discover Global Issues . His awards include the Fulbright Scholarship and fellowships from the British Computer Society and Metropolitan Museum of Art.

Priya Narasimhanمشاهده پروفایل

استاد

• Dependable Distributed Systems
• Fault-Tolerance
• Embedded Systems
• +۵ مورد دیگر

Priya Narasimhan is a Professor of Electrical & Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. Her research focuses on dependable distributed systems, fault-tolerance, embedded systems, mobile systems, and sports technology. She leads the Intel Science and Technology Center in Embedded Computing (ISTC-EC) and founded YinzCam, a CMU spin-off providing mobile live streaming to sports venues. She holds multiple awards, including the Sloan Fellowship and NSF CAREER Award. Education: Ph.D. and M.S. in Electrical & Computer Engineering from UC Santa Barbara. Notable roles include former CTO of Eternal Systems, Director of Intel Labs Pittsburgh, and Director of CMU's CyLab Mobility Research Center. Research spans failure diagnosis in distributed systems, live upgrades, mobile cloud computing, football technology, assistive tech for the blind (Trinetra), and civic tech (iBurgh). Over 30+ students advised across Ph.D., M.S., and undergraduate programs. Active in entrepreneurship, teaching (courses like 18-349 Embedded Systems), and industry collaborations.

Ajita Rattaniمشاهده پروفایل

استادیار

• Biometrics
• Deepfake Detection
• Facial Recognition
• +۶ مورد دیگر

Ajita Rattani is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, affiliated with Discovery Park. Her research focuses on biometrics, AI fairness, deepfake detection, and machine learning applications in health and security. She holds a Ph.D. in Computer Science and Engineering, with expertise in facial recognition, ocular biometrics, and multimodal authentication systems. Research Interests: Her work addresses algorithmic fairness in facial attribute classification, robustness of biometric systems against adversarial attacks, and developing lightweight models for on-device authentication. She also explores applications of machine learning in health informatics, such as BMI prediction from facial images and analyzing social determinants of health. Publications Trends: Recent work emphasizes bias mitigation in AI systems (e.g., gender/racial fairness), deepfake detection through fusion of audio-visual cues, and advancing ocular biometric recognition under challenging conditions. Notable contributions include frameworks like CodeIT for data-efficient deepfake detection and PatchBMI-Net for lightweight BMI prediction. Advising & Grants: Leads research projects funded by NSF SaTC grants (e.g., probing fairness in ocular biometrics). Active in organizing competitions like VISOB 2.0 for mobile ocular biometrics evaluation. Her lab develops practical solutions for real-world challenges in biometrics and AI ethics. Labs/Teams: Involved in interdisciplinary teams addressing transdisciplinary collaboration challenges and applying AI to disaster detection (wildfires, droughts) using satellite and sensor data fusion.

Yijing Liمشاهده پروفایل

مدرس ارشد

• Urban Crime Analysis
• Geographic Information Systems (GIS)
• Counter-Terrorism Strategies
• +۳ مورد دیگر

Dr. Yijing Li is a Senior Lecturer in Urban Informatics at King’s College London, Department of Informatics. She joined King’s in 2018 and previously held roles at the University of Warwick and China Executive Leadership Academy Pudong. Her research focuses on spatial analysis of urban crime, counter-terrorism strategies, climate change impacts on crime, and risk management using big data. She holds a PhD in Geography of Crime from the University of Cambridge and an MSc in Urban Ecology from Peking University. Her work integrates theories from sociology, criminology, and economics with quantitative and qualitative methods. Key research areas include crime patterns during pandemic lockdowns, One Belt One Road security strategies, and environmental sustainability assessments. She has authored over 30 publications, including studies on London’s crime dynamics, spatial disparities in crime data, and vegetation change modeling using remote sensing. Dr. Li is affiliated with the Centre for Urban Science and Progress (CUSP) London and the Computing Education Research Centre (CERC). She has supervised interdisciplinary projects on employability in data science programs and collaborated with organizations like Transport for London and Westminster City Council. Her recent work examines health resilience in European countries post-pandemic and employs Bayesian models to analyze crime patterns during lockdowns.

Erica R.H. Fuchsمشاهده پروفایل

استاد

• Technology Policy
• Global Manufacturing
• Innovation Policy
• +۳ مورد دیگر

Erica R.H. Fuchs is the Kavčić-Moura Professor in the Department of Engineering and Public Policy at Carnegie Mellon University (CMU), directing the Critical Technology Initiative (CTI). She holds courtesy faculty positions in Materials Science and Engineering and the Heinz College. Her research focuses on emerging technology development, commercialization, and global manufacturing, with emphasis on national policy implications. Fuchs leads interdisciplinary efforts at CTI to advance critical technology assessment frameworks, ensuring smart investments and policies for national security and economic competitiveness. Formerly, she directed the Manufacturing Futures Initiative, now an endowed institute at CMU. Education: She earned a Ph.D. (2006), M.Sc. (2003), and B.Sc. (1999) in Engineering Systems, Technology Policy, and Materials Science from MIT. Post-MIT, she was a UNIDO fellow in Beijing. Research Interests: Global innovation policy, technology commercialization pathways, and the intersection of technology with economic and security objectives. She authored influential works like the 2021 report *Securing America’s Future*, advocating for a National Technology Strategy to align multi-objective outcomes (security, equity, prosperity). Key Contributions: Catalyzed the National Network for Critical Technology Assessment, mobilizing 13+ universities to address technology gaps. Testified in Congress on supply chain resilience, EV battery policies, and semiconductor strategies. Advises entities like the National Semiconductor Technology Center and MIT’s Institute for Data, Systems, and Society. Affiliations: National Bureau of Economic Research (Research Associate), National Institute of Standards and Technology (NSTC Board), and Brookings Institution panelist. Her work is frequently cited in *Axios*, *Bloomberg*, and the *New York Times*.

Dewei Yiمشاهده پروفایل

مدرس ارشد

• Computer Vision
• AI-enabled Healthcare
• Hybrid Intelligent Systems
• +۱۶ مورد دیگر

Dewei Yi is a Senior Lecturer (Associate Professor) in the Department of Computing Science, School of Natural and Computing Sciences at the University of Aberdeen, UK. He holds a PhD from Loughborough University and is an active researcher in AI, computer vision, and intelligent systems. He serves as Director of the MSc AI and MSc Robotics and AI programmes. Research Interests: His research spans AI-enabled healthcare, medical image processing, intelligent vehicles, robotics, precision agriculture, remote sensing, and applied machine learning. He focuses on hybrid intelligent systems, personalised AI, federated learning, fairness, and explainability. Recent Publication Trends: His latest work includes medical image quality evaluation using contrastive learning, federated learning for diabetic retinopathy, UAV-based solar panel inspection, vascular image analysis, and emotion recognition from ECG data, reflecting a strong trend toward healthcare and intelligent systems with real-world impact. Scientific Awards: Fellow of the Higher Education Academy (FHEA) Outstanding Reviewer, Transportation Research Part C (TRC) Advising and Grants: Dr Yi supervises multiple PhD students in AI, computer vision, and machine learning. His graduated PhDs include Debinal Bakyavathi Rajan, Sami Hamid Al Sulaimani, and Adinath Abhimanyu Ghadage. He has secured significant funding as PI and Co-PI, including a £408K Smartawl 5.0 project and a £794K Cancer Research UK grant (Co-PI). Labs and Teams: He leads research in AI for healthcare and intelligent vehicles, collaborating with institutions like University of Warwick, Loughborough University, and industry partners such as AVL Powertrain Ltd. His work is supported by interdisciplinary teams focusing on embedded AI, medical applications, and sustainable technologies.