جست‌وجوی استاد و پژوهشگر

Bin Chenمشاهده پروفایل

دانشیار

• Computational Biology
• Bioinformatics
• Machine Learning
• +۶ مورد دیگر

Bin Chen is an Associate Professor at Michigan State University with joint appointments in the Genetics & Genome Sciences Program and Department of Computer Science and Engineering . His research combines multi-omics data , electronic medical records , and advanced machine learning to develop novel therapeutic approaches. Key affiliations : Genetics & Genome Sciences Program Computer Science and Engineering Department NIH BDMA Study Section Research focus : OMICS-driven drug discovery Biomarker identification Translational bioinformatics Virtual screening platforms Single-cell & spatial transcriptomics His lab actively develops machine learning models like transfer learning and deep reinforcement learning to analyze bulk/single-cell transcriptomics and EMR/EHR data. The team has made significant contributions to COVID-19 research, diffuse midline glioma , and Alzheimer's disease through computational drug repurposing and biomarker discovery . Selected scientific awards include: NIH R01 Diversity Supplement (2021) Early Career Research Excellence Award (2021) Best Paper Award at KDD Health Day (2022) NIH BDMA Study Section Membership (2025) The lab has trained numerous students and postdocs who have transitioned to academic and industry positions. Current funding includes NIH R01 grants , NCATS Translator program , and MSU-Spectrum Health Alliance collaborations.

• Machine Learning
• Signal Processing
• Remote Sensing
• +۴ مورد دیگر

Wei Xue is an active academic researcher affiliated with Tsinghua University's Department of Computer Science and Technology. Their work spans multiple disciplines, including Machine Learning , Signal Processing , Medical Imaging , and Natural Language Processing . Key research areas include adversarial robustness in DNNs for remote sensing, hierarchical speaker representation learning for speech extraction, and multi-view fuzzy classification for brain network analysis. Recent publications focus on imbalanced data classification, spectrum sensing in cognitive radio, and innovative applications in soft robotics and medical diagnostics. Collaborations include institutions like Tsinghua University, Jiangnan University, and Hong Kong Baptist University, with frequent contributions to journals such as IEEE Transactions on Geoscience and Remote Sensing and Neural Networks .

• AI Ethics
• Human-Computer Interaction
• Accessibility Technology
• +۳ مورد دیگر

Aditya Vashistha is an Assistant Professor at Cornell Tech, part of Cornell University. His research focuses on AI ethics, accessibility technology, and technology's role in global development. He holds a PhD from the University of Washington (2019) and has published extensively in top venues like CHI and CSCW. Key research areas include: Ethical AI deployment in healthcare and social contexts Accessibility for disabled communities on social media Addressing algorithmic bias in LLMs and moderation systems Technology solutions for low-resource regions Recent work examines equitable AI systems for marginalized groups, cultural nuances in AI, and combating misinformation in developing regions. His projects often collaborate with community health workers and frontline workers to create context-aware solutions. Publications analyze trends in: Global viral content dynamics on WhatsApp Intersection of ableism and AI moderation AI's role in wage advocacy for home care workers Awards: No explicit awards listed in the provided data. Labs/Teams: Engaged with interdisciplinary teams at Cornell Tech and global collaborators in India/Asia Pacific regions.

Melissa Zeynep Ertemمشاهده پروفایل

استادیار

• Data Analytics in Healthcare Systems
• Epidemic Disease Modelling
• Network Optimization
• +۳ مورد دیگر

Melissa Zeynep Ertem is an Assistant Professor at the School of Systems Science and Industrial Engineering, Binghamton University. Her work focuses on data analytics in healthcare systems, epidemic disease modeling, network optimization, and public health optimization. Prior roles include Adjunct Professor at the University of Southern California's Marshall School of Business and a postdoctoral fellowship at the University of Texas at Austin. She holds a PhD in Industrial and Systems Engineering from Texas A&M University and a BS in Industrial Engineering from Middle East Technical University, Turkey, with a minor in Mathematics. Her research bridges systems science and public health, addressing challenges in pandemic policy analysis, healthcare resource allocation, and disease spread modeling. Key research interests include optimizing healthcare systems through data-driven decision support, modeling infectious disease transmission dynamics, and leveraging social network analysis for public health interventions. Her recent work examines school reopening policies' impacts on SARS-CoV-2 spread, climate-driven influenza patterns, and misinformation effects on youth health. Publications span journals like Nature Medicine , PLOS Computational Biology , and Journal of Global Optimization , with a focus on practical solutions for complex health crises. Ongoing projects explore pandemic virtue signaling in healthcare cultures and machine learning applications for long-COVID prediction. Her interdisciplinary background enables collaborations across engineering, public health, and data sciences. Lab activities focus on developing computational tools for real-world health system challenges, emphasizing equity and scalability.

• Network Analysis
• Social Networks
• Data Mining
• +۶ مورد دیگر

Michele Coscia is an Associate Professor in the Department of Data Science at the IT University of Copenhagen. He also serves as the Head of Programme for the BSc in Data Science. His research focuses on network analysis, social networks, data mining, and their applications in understanding human mobility, complex systems, economic development, and memetics. He has contributed to projects such as the Pioneer Centre for Artificial Intelligence and leads initiatives like ROMNET (Past social network reconstruction from material culture data) and Work2Vec (exploring deep learning in healthcare and work hours analysis). His research interests encompass interdisciplinary network science, including misinformation dynamics, ideological polarization, and the impact of social media systems. He has developed methodologies like the generalized Euclidean measure for multilayer networks and explored cultural data analytics through case studies like Italian music history. His work also addresses real-world challenges, such as quantifying the effects of violence on migration patterns and optimizing network sampling strategies for cost efficiency. Michele Coscia has received the Årets Forskningsmiljø 2022 award, recognizing his contributions to fostering outstanding research environments. He actively engages with media, discussing topics like misinformation and data visualization. As a principal investigator, he oversees projects funded by institutions such as the Villum Foundation and Danish National Research Foundation. His research spans academic collaborations across countries, reflecting his global network and commitment to advancing network theory and its applications.

Henry Kudzanai Dambanemuyaمشاهده پروفایل

عضو هیئت علمی

• Computational Social Science
• Network Science
• Social Computing
• +۶ مورد دیگر

Dr. Henry Kudzanai Dambanemuya is an Assistant Instructional Professor in the Masters in Computational Social Science (MACSS) program at the University of Chicago. His teaching focuses on computational methods, research design, and elective topics like collective intelligence and digital peacebuilding. He holds a multidisciplinary background spanning computer science, communication, and international peace studies, leveraging software engineering expertise from roles at Microsoft and other tech firms. Education B.A. in Computer Science and Conflict Studies (DePauw University) M.A. in International Peace Studies (University of Notre Dame) M.Sc. and Ph.D. in Technology and Social Behavior (Northwestern University) Research Interests His work integrates Big Data mining, machine learning, and network science to study collective intelligence in complex systems. Key areas include: - Crowdfunding dynamics and signaling mechanisms - Online discourse analysis and influence networks - Humanitarian aid monitoring via multilingual datasets (HumVI) - Stress detection using wearable biosensors (HealthSense) - Peace process implementation through network analysis Grants & Advising While specific grants aren't listed, his industry collaborations (RICS Software, Dataminr) and academic partnerships (ACM, IEEE) suggest active funding. He advises MACSS students on balancing academic and industry career paths. Labs & Teams Active in computational social science research communities, with ongoing collaborations at WebSci, CHI, and ICWSM conferences. Maintains a public research portal for current projects.

Alistair Windsorمشاهده پروفایل

دانشیار

• Dynamical Systems
• Ergodic Theory
• STEM Education
• +۴ مورد دیگر

Alistair Windsor is an Associate Professor of Mathematical Sciences at the University of Memphis, where he also serves as Director of the Institute for Intelligent Systems. His research bridges dynamical systems, ergodic theory, and natural language processing (NLP), with a focus on applications in STEM education and AI ethics. Notably, he collaborates with Kristopher Kyle on Verb Argument Constructions (VACs) analysis using the TAASSC tool, examining linguistic patterns in human vs. AI-generated texts. His work extends to machine learning and computer vision, including contributions to the CvT (Convolutional Vision Transformers) project on GitHub, which merges CNNs with Vision Transformers for improved image recognition. Research interests include computational linguistics, AI-driven education, and interdisciplinary projects like analyzing medical/financial advice quality in ChatGPT versus human experts. He actively publishes in venues addressing education, political linguistics, and healthcare literacy, emphasizing practical applications like improving teaching assistant feedback in CS courses. His technical expertise spans software testing methodologies and open-source tools for reproducibility in computational workflows. Windsor’s interdisciplinary approach integrates mathematical rigor with real-world societal challenges, from urban policy analysis to pandemic governance studies. He maintains an active GitHub presence, contributing to projects like CvT and tools for text coherence measurement in social media.

Hridoy Sankar Duttaمشاهده پروفایل

استادیار

• Cybersecurity Analytics
• Social Network Analysis
• Web Mining
• +۴ مورد دیگر

Hridoy Sankar Dutta is Lecturer (Assistant Professor) in Cyber Security at Deakin University's GIFT City Campus. His research develops data-driven methods to analyze cybersecurity threats, including modded Android applications, blackmarket services, and online collusion networks. Dutta's work combines social network analysis with web mining to detect artificially boosted entities and malicious coordination. He maintains open-source resources including YT-30M and YT-100K multilingual comment datasets. Current projects investigate Wikipedia backlink markets and YouTube diffusion dynamics. Honors include the University of Cambridge Wiseman Prize and DAAD AInet fellowship. Dutta actively contributes to cybersecurity conferences as program committee member and reviewer.

Andrew Johnمشاهده پروفایل

استاد

• Macroeconomics
• Ethics and Corporate Social Responsibility
• Economics of Language
• +۳ مورد دیگر

Andrew John is a Professor of Economics at Melbourne Business School (MBS), part of The University of Melbourne. He holds dual roles in research and leadership, having served as Associate Dean (Faculty) and Acting Deputy Dean (Academic). With over 30 years of experience, he has taught at institutions including INSEAD and the University of Virginia, specializing in macroeconomics, ethics, and language economics. His research explores topics like consumer boycotts, language evolution, and environmental policy, with publications in top-tier journals such as American Economic Review and Journal of Marketing . John received his Ph.D. from Yale University and a B.A. from Trinity College Dublin. His teaching focuses on MBA programs, including courses like Managerial Ethics & Social Responsibility and Global Business Economics . He won the MBS Teaching Excellence Award for his work in the Senior Executive MBA Program. His research spans macroeconomic coordination failures, language economics, and environmental sustainability, often bridging theory with practical business applications. John has also led executive education programs and consulted across Asia-Pacific and Europe through his firm, AJK Consulting (2002–2008). Key affiliations include leadership roles in MBS research centers like the Centre for Business Analytics and Centre for Social Purpose Organisations. His work emphasizes interdisciplinary approaches, integrating economic theory with real-world challenges in ethics, language dynamics, and environmental policy.

Antonio Paños Alvarezمشاهده پروفایل

دانشیار

• Business Management
• Information Technology Strategy
• Eco-innovation
• +۴ مورد دیگر

Antonio Paños Alvarez is an Associate Professor at the Department of Business Organization and Finance within the Faculty of Economics and Business at the University of Murcia. His research focuses on business management, information technology strategy, eco-innovation, and competitive advantage in regional industries. He holds a Doctorate from the University of Murcia (2007) with a thesis on information technologies as competitive advantage sources. Key research interests include strategic relevance of IT in enterprises, eco-innovation case studies, document management systems, and technology adoption in SMEs. His work emphasizes empirical analysis of business processes, strategic partnerships, and organizational learning cultures. He has contributed to over 20 publications since 1996, with recent focus on Murcian enterprise innovation and sustainability. He is affiliated with the ITO research group (Organizational Technological Innovation) and previously contributed to Universidad-Empresa 91 groups. His work bridges academic research with practical business challenges, particularly in regional economic contexts.

• Plant Microbiology
• Biotechnology
• Corporate Communication
• +۳ مورد دیگر

Dr. Magdalena Rajewska is an Assistant Professor at the Intercollegiate Faculty of Biotechnology of the University of Gdańsk and the Medical University of Gdańsk (MUG), affiliated with the Department of Plant Microbiology at the University of Gdańsk’s Institute of Biotechnology. Her work bridges biotechnological research with interdisciplinary studies in corporate communication and risk management. Her research interests span plant microbiology, biotechnology applications, and the intersection of corporate identity with social network analysis. She explores how communication frameworks influence innovation ecosystems, risk perception in complex systems, and organizational dynamics through actor-network theory. Notable thematic focuses include corporate social responsibility (CSR), language’s role in knowledge management, and the discursive aspects of entrepreneurship and creativity. Publications highlight trends in digital storytelling, stakeholder management in modern libraries, and the metaphorical dimensions of business discourse. Her work frequently integrates neuroscience perspectives with organizational studies, emphasizing cognitive science principles in decision-making processes. No scientific awards or advisory roles are explicitly listed in the provided materials. While no grants or labs are detailed, her contributions reflect a multidisciplinary approach to biotechnology and corporate communication challenges.

Stefan Heimمشاهده پروفایل

استاد

• Neuroanatomy
• Language Processing
• Cognitive Neuroscience
• +۱ مورد دیگر

Prof. Dr. Stefan Heim leads the Neuroanatomy of Language working group at Research Center Jülich's Institute of Neuroscience and Medicine (INM-1). His research bridges cognitive neuroscience and computational approaches to language processing. Research Focus His work investigates the structural and functional organization of language networks in the brain, combining neuroanatomical approaches with advanced computational methods. Current projects explore machine learning applications in neuroscience and computational linguistics. Publication Trends Recent publications focus on machine learning innovations including large language models, efficient training techniques, and applications in scientific domains like plasma physics and renewable energy.

• Speech Processing
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Murat Saraçlar is a full professor at the Electrical and Electronic Engineering Department of Boğaziçi University. He holds a B.S. from Bilkent University (1994), and M.S.E. and Ph.D. degrees from Johns Hopkins University (1997, 2001). Before joining Boğaziçi in 2005, he worked at AT&T Labs Research (2000–2005). He has held visiting positions at Google (2011–2012) and IBM T.J. Watson Research Center (2012–2013). Affiliations: Editorial roles include IEEE Transactions on Audio, Speech, and Language Processing (Senior Area Editor), and Computer Speech & Language (Editorial Board). Research Interests: Speech Processing, Natural Language Processing, Machine Learning, and Artificial Intelligence. His work focuses on speech recognition, keyword search, and medical signal analysis. Over 100 publications span journals like IEEE/ACM Transactions on Audio, Speech, and Language Processing. Awards include TÜBA-GEBİP Young Scientist Award (2009) and IBM Faculty Award (2010). Recent articles emphasize multimodal systems, unsupervised learning, and medical diagnostics. His contributions bridge theoretical advancements with practical applications in healthcare and communication systems.

Edward Hurcombeمشاهده پروفایل

مدرس ارشد

• Journalism
• Internet Culture
• Digital Platforms
• +۳ مورد دیگر

Edward Hurcombe is a Senior Lecturer and ARC DECRA Fellow in the School of Media & Communication at RMIT University, Australia. His academic work focuses on the evolving relationship between journalism, digital platforms, and social media ecosystems. Based at RMIT's City Campus, he actively contributes to research and teaching in media and communication studies while supervising Masters and PhD students. Dr. Hurcombe's research centers on how news and journalistic practice are transforming in relation to the technologies, economies, and user cultures of social media platforms. He investigates both the challenges and possibilities emerging from these transformations, including tackling malicious actors on platforms and identifying new forms of socially-positive digital journalism. His current ARC DECRA project (DE250100115) specifically examines how journalist influencers ("newsfluencers") are reshaping news to reach and build trust with young adult audiences. His scholarly output reveals a strong focus on social news, disinformation dynamics, platform regulation, and the institutional impacts of algorithmic distribution on news media. His research often employs computational methods to analyze large-scale social media data, particularly focusing on Facebook and Twitter. Dr. Hurcombe's work demonstrates how digital platforms are not merely threats to journalism but are also driving innovative forms of news production that challenge traditional journalistic boundaries and norms. ARC DECRA Fellowship supporting research on journalist influencers Extensive publications in leading journals including Digital Journalism and New Media & Society Highly cited research on conspiracy theory dissemination during the COVID-19 pandemic Policy-relevant work on platform regulation and news media bargaining As an active supervisor, Dr. Hurcombe welcomes Masters Research and PhD students, with current projects including "AI in Saudi newsrooms: navigating new technology in journalism practice." His collaborative work with scholars like Axel Bruns and David Angus has significantly advanced understanding of social media's role in contemporary journalism and information ecosystems.

Susan Brownمشاهده پروفایل

استاد

• Digital Humanities
• Victorian Literature
• Feminist Theory
• +۳ مورد دیگر

Susan Brown is a Professor at the University of Guelph, holding a Canada Research Chair (Tier 1) in Collaborative Digital Scholarship. She is affiliated with the College of Arts and the School of Theatre, English, and Creative Writing. Her research focuses on digital humanities, critical infrastructure studies, Victorian literature, and feminist theory, particularly through her leadership of the Orlando Project, a pioneering interdisciplinary initiative. She has received significant grants from the Social Sciences and Humanities Research Council of Canada and the Canadian Foundation for Innovation. Her work bridges feminist literary history with digital innovation, emphasizing collaborative knowledge production and inclusive digital infrastructure. Brown has contributed to university administration, including roles on the Senate Awards Committee, Board of Governors, and editorial boards of journals like Victorian Review and KULA . She has also served on national and international advisory boards, including Compute Canada and the Digital Research Alliance of Canada. Research interests include feminist digital methodologies, semantic technologies, and the intersection of technology with literary studies. Awards include the Society for Digital Humanities Outstanding Achievement Award (2006) and the T-REX Best New Tool Prize (2008). She has taught extensively in Victorian studies, gender theory, and digital humanities, receiving a teaching award in 1999 for integrating digital methods. Brown founded the DH@Guelph Summer Workshops and co-created the Culture and Technology Studies program. Grants and projects include funding for the Humanities Interdisciplinary Collaboration Lab (THINC Lab) and the Canadian Writing Research Collaboratory (CWRC). Her recent work explores metadata ontologies, linked open data, and the ethical dimensions of digital cultural heritage.