Dacheng Xiu is the Joseph Sondheimer Professor of Econometrics and Statistics at the Booth School of Business , University of Chicago, and an Affiliated Faculty in the Department of Statistics. He serves as a Research Associate at the National Bureau of Economic Research and holds editorial roles at journals like Journal of Business & Economic Statistics and Journal of Financial Econometrics . PhD and MA in Applied Mathematics from Princeton University BS in Mathematics from University of Science and Technology of China His research focuses on statistical methodologies for financial data , including risk measurement , portfolio management , and empirical asset pricing using high-frequency data and machine learning . Recent work analyzes text data and large language models for economic forecasting. Editorial leadership includes Co-Editor and Associate Editor roles at top journals like Journal of Finance and Annals of Statistics . His lab ( Risk Lab ) specializes in systemic risk assessment through transaction-level data analysis. 2024 Dimensional Fund Advisors Prize 2023 GSU-RFS FinTech Conference Best Paper Award 2022 Society for Financial Econometrics Fellow 2018 Swiss Finance Institute Outstanding Paper Award
Dr Mahir Arzoky is a Lecturer in the Department of Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. He holds a PhD from Brunel University London (2015) and has extensive research experience in artificial intelligence and software engineering. His research focuses on: Artificial Intelligence and Intelligent Data Analysis Search Based Software Engineering (SBSE) Clustering algorithms and heuristic search methods Software refactoring and quality assessment Data mining applications in healthcare and education Analysis of his 15 most recent publications (2018-2022) reveals strong interdisciplinary work bridging computer science with healthcare (diabetes patient modeling, medical imaging) and education (chatbot design, algorithm visualization). His technical focus centers on clustering optimization, refactoring impact analysis, and explainable AI, with frequent use of empirical validation methods. Key collaborations include researchers like Stephen Swift, Steve Counsell, and Giuseppe Destefanis. Dr Arzoky has secured significant research funding through EPSRC grants including: AQUATIC project (EP/M024083/1): Assessing Test Suite Quality in Industrial Code FIAR-NET (EP/N011627/1): Fault Analyses in Industry and Academic Research Network His professional network includes active collaborations across computer science, healthcare informatics, and educational technology domains, with recent work extending into transformer models for healthcare SQL conversion and graph partitioning for software modularization.
Dr Virginia Newcombe is an Honorary Consultant in the Department of Medicine, Division of Anaesthesia, at the University of Cambridge’s School of Clinical Medicine, based at the Wolfson Brain Imaging Centre. She is also an active Principal Investigator within Cambridge Neuroscience, contributing to the Brains and Machines and Lifelong Brain Development and Brain Ageing research themes. Education and Training: While specific degrees are not listed in the provided text, Dr Newcombe’s extensive peer-reviewed output and honorary consultant status indicate advanced clinical and research training in medicine, neuroimaging and neurotrauma. Research Focus: Her programme centres on translating advanced magnetic resonance imaging into clinically actionable biomarkers for traumatic brain injury (TBI). Key themes include: Prediction of short- and long-term outcomes after mild, moderate and severe TBI. Influence of acute management strategies (Emergency Department and Neuro-critical Care) on patient trajectories. Multimodal integration of MRI, blood-based biomarkers, neuropsychological testing and machine-learning approaches. Neuroinflammatory and neurodegenerative sequelae of TBI and COVID-19. Publication Trends: Across >60 publications (2013-2025), her work spans high-impact journals such as Brain , JAMA Neurology , Neurosurgery , Critical Care and Neuroimage . The corpus reveals a rapid acceleration of output post-2020, with particular emphasis on large-scale collaborative studies (CENTER-TBI, Cambridge NeuroCOVID), methodological harmonisation of multi-centre MRI data, and the integration of blood biomarkers with advanced neuroimaging to improve prognostic accuracy. Scientific Awards and Recognition: Although no explicit awards are listed, her leadership roles in international consortia, frequent keynote-level publications and invitations to co-author NINDS/NICE guidance documents indicate significant peer recognition. Collaborations & Funding: Dr Newcombe collaborates closely with Cambridge colleagues including Prof David Menon, Dr Guy Williams, Prof Peter Hutchinson, Dr Marta Correia and Dr Adel Helmy. She is also a key member of the CENTER-TBI, TRACK-TBI and Cambridge NeuroCOVID initiatives, securing multi-million-pound grants from NIHR, EU Horizon 2020 and UK research councils. Laboratory & Teams: She leads a translational neuroimaging group embedded within the Wolfson Brain Imaging Centre, equipped with 3 T and 7 T MRI, state-of-the-art post-processing pipelines and dedicated Emergency Department/ICU recruitment infrastructure. The team currently welcomes doctoral applications and hosts post-doctoral researchers, clinical research fellows and imaging analysts.
Servet Üztemur is a full-time Professor at Anadolu University , Faculty of Education, Department of Elementary Education, where he specializes in history education, social studies education, museum education, and epistemological beliefs. His research integrates educational psychology with social and cultural studies, emphasizing teacher training, curriculum development, and student cognition. His educational background is rooted in teacher education and pedagogy, aligning with his extensive work in developing scales and curricula for K-12 and higher education. His research interests span: History and Social Studies Education: Curriculum evaluation, museum integration, and historical thinking. Educational Psychology: Epistemological beliefs, student cognition, and learning approaches. Digital Well-being: Social media addiction, smartphone use, and psychological resilience among adolescents and young adults. Disaster Psychology: Post-earthquake mental health, trauma, and obsession-related behaviors. His most recent publications (2024–2025) reflect a strong focus on psychological constructs in education, particularly in relation to digital behavior, trauma, and emotional regulation. These studies often involve scale development, cross-cultural validation, and mediation/moderation analyses, indicating a robust methodological approach. Scientific Awards: While no specific awards are mentioned in the provided text, his high citation metrics (e.g., H-index: 49 WoS, 69 Scopus) and extensive publication record underscore his academic impact. Advising and Grants: He has supervised 3 thesis advisories and led or participated in 283 projects , reflecting his active role in graduate education and research leadership. Labs and Teams: While no specific lab name is provided, his affiliation with the Faculty of Education and involvement in large-scale projects suggest he works within interdisciplinary research teams focusing on educational innovation and psychological assessment.
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.
Jørgen Bruhn , Professor at the Faculty of Arts and Humanities , Linnaeus University , specializes in Intermediality , Ecocriticism , and Anthropocene Studies . He leads the Linnaeus University Center for Intermedial and Multimodal Studies and coordinates projects like Intermedial Ecocriticism: Transmediating the Anthropocene . His work bridges literary theory , film analysis , and environmental humanities , with recent focus on climate crisis narratives across media. Research : Intermedial Ecocriticism, Transmedia Storytelling, Anthropocene Representation Teaching : Intermediality, Ecocriticism, Climate Emergency Studies
Zhiru Ng is a Professor in the Department of Religious Studies at Pomona College, where she has been a faculty member since 2000. Her research and teaching focus on Chinese Buddhist history, art, and religious practices, particularly the cult of Dizang (Jizo) Bodhisattva and the interplay between texts and images in Buddhist traditions. Her academic background includes a Ph.D. from the University of Arizona, an M.A. from the University of Michigan, Ann Arbor, and a B.A. from the National University of Singapore. Ph.D., University of Arizona M.A., University of Michigan, Ann Arbor B.A., National University of Singapore Dr. Ng's research interests span Chinese Buddhist history, Buddhist art, Dizang Bodhisattva, cross-cultural Buddhist interactions, and modern Taiwanese Buddhism. She explores how Buddhist doctrines are materialized in art and ritual, and how religious diversity is navigated in Chinese intellectual history. Her work bridges textual analysis with visual and material culture, offering deep insights into the lived dimensions of East Asian Buddhism. The trend in her scholarly publications reflects a sustained engagement with medieval Chinese Buddhist cults, scriptural authority, healing practices, and the visual representation of doctrine. Her articles and book chapters examine the evolution of savior bodhisattvas, the integration of Indian Buddhist traditions in China, and the dynamics of religious diversity. She frequently contributes to major academic presses and journals in Buddhist and Asian studies. Her scientific awards and honors include: Outstanding Global Bhikṣunī Award, Taiwan (2016) Outstanding Women in Buddhism Award, Bangkok (2010) Visiting Research Fellow, University of Heidelberg (2012) Senior Fellow, Harvard University Center for the Study of World Religions (2003–04) Chiang Ching-kuo Foundation Scholar Grant (2008–09) Graves Award for Excellence in Teaching (2004–05) Dr. Ng has advised various academic projects and secured research grants from foundations such as the Chiang Ching-kuo Foundation and Harvard’s Center for the Study of World Religions. While no formal lab or research team is mentioned, her collaborative work with institutions like the Kuroda Institute and participation in international research projects indicate active scholarly networks. She teaches courses on East Asian religions, the Lotus Sutra, death and afterlife, and the life of the Buddha through art and text.
Gesa van den Broek is an Assistant Professor at Utrecht University's Faculty of Social and Behavioural Sciences , specializing in Education and Learning: Development in Interaction . Her research focuses on instructional design, cognitive psychology, and memory studies, particularly in foreign language pedagogy and higher education research. Areas of Expertise: Instructional Design, Cognitive Psychology, Memory Studies, Foreign Language Pedagogy Research Themes: Dynamics of Youth (DoY), Game Research, Higher Education Research Her recent work investigates retrieval practice mechanisms, stepwise worked examples, and multimedia learning effects. She actively collaborates on educational technology tools like ET_cam_home and participates in public engagement activities, including media contributions to Dutch outlets like Volkskrant and Trouw.
Silvia Cascianelli is an AI and Computer Vision Researcher at the University of Modena and Reggio Emilia (UNIMORE). She actively contributes to the computer vision and document analysis communities through research, conference organization, and academic mentorship. She serves as Area Chair for major computer vision conferences including CVPR2025, BMVC2025, and ECCV2024, demonstrating her standing in the field. Her research focuses on several key areas within computer vision and document analysis: Image Generation : Developing efficient and lightweight methods for image generation with desired characteristics, particularly using diffusion models Handwriting Imitation : Creating algorithms for generating images of text with specific content and handwriting styles, along with evaluation methods Document Understanding : Extracting information from 2D and 3D document images, ranging from modern documents to historical artifacts like carbonized Roman papyri Dr. Cascianelli's work shows a clear progression toward more sophisticated generative models and evaluation frameworks, with recent publications focusing on diffusion models for handwritten text generation, efficient token reduction for multimodal tasks, and innovative approaches to historical document analysis. Her research bridges theoretical advancements with practical applications across diverse document types. Her scientific contributions have been recognized through invitations to serve as Area Chair for top-tier computer vision conferences (CVPR, ECCV, BMVC) and opportunities to organize specialized workshops including VisionDocs at ICCV, AI4DH at ECCV, and ADAPDA at ICDAR. Area Chair at CVPR2025 Area Chair at BMVC2025 Area Chair at ECCV2024 Organizer of VisionDocs Workshop at ICCV2025 Organizer of AI for Digital Humanities Workshop at ECCV2024 Organizer of ADAPDA Workshop at ICDAR2024 Dr. Cascianelli actively mentors the next generation of researchers: Vittorio Pippi - PhD Student at UniMoRe (National PhD program in AI) Fabio Quattrini - PhD Student at UniMoRe (ICT program) Carmine Zaccagnino - Research Intern at UniMoRe (formerly MSc student) Kostantina Nikolaidou - PhD Student at Luleå University of Technology Pau Torras Coloma - PhD Student at Computer Vision Center, Universitat Autònoma de Barcelona Bram Vanherle - CV Engineer at Colruyt Group Smart Innovation (formerly PhD student) She is actively involved in several research initiatives including the AI Governance Lab where she serves as a lecturer, and collaborates with institutions worldwide. Her current projects focus on advancing diffusion models for image generation, improving handwritten text recognition systems, and developing novel methods for document understanding across historical and contemporary contexts.
Grzegorz Chrupała is an Associate Professor at the Department of Cognitive Science and Artificial Intelligence , Tilburg University, where he leads research in computational approaches to multimodal communication. Previously, he was a postdoctoral researcher at Saarland University's Spoken Language Systems group and earned his PhD from Dublin City University's School of Computing. His research bridges biological and artificial computation , focusing on enabling machines to learn language from multimodal data (speech, gestures, visual-auditory stimuli) as children do naturally. This involves developing and interpreting deep learning architectures, analyzing emergent representations, and advancing speech technology for under-resourced languages. Key themes include Visually grounded speech modeling Feature attribution and model interpretability Human-inspired learning paradigms BlackboxNLP workshop leadership His recent publications examine speech model reliability , lexical tone encoding , and contextual dependencies in NLP systems. He mentors a team of PhD candidates and alumni working on topics like user-centric interpretability, bioacoustics, and disentangled speech representations. He also serves on the board of the Dutch Open Speech Technology Foundation, chairs Interspeech 2025 tutorials, and contributes as an Action Editor for TACL.
Andrea Oberhuber is a Professor in the Department of French-Language Literatures at the University of Montreal's Faculty of Arts and Sciences. She has been teaching at the university since June 2001, specializing in French and Quebec literature from the 19th to 21st centuries, with particular expertise in women's writing, photoliterature, and historical avant-garde movements including Futurism, Dada, and Surrealism. Her educational background includes studies in Romance and German philology at the University of Innsbruck and the University of Paris IV-Sorbonne. Her doctoral thesis focused on women's chansons in France from 1968-1993 and was published in 1995 by Erich Schmidt Verlag in Berlin. Following her doctorate, she was a postdoctoral fellow at the Institut für Romanistik (University of Innsbruck) and served as a lecturer at the Centre d'études canadiennes before joining the University of Montreal faculty. Professor Oberhuber's research spans women's writing across three centuries of French and Quebec literature, photoliterature, intermediality, gender studies, and cultural transfer. She has pioneered work on the intersection of literature and visual arts, particularly in surrealist contexts, and more recently has explored themes of 'care' in literature from 1870-1945. Her scholarship often examines how women writers have navigated and transformed literary traditions through collaborative practices and innovative forms of expression. Her extensive publication record reveals a consistent focus on women's literary contributions, particularly in avant-garde movements. The most recent works show an evolution toward examining collaborative practices among women artists, the materiality of the book as artistic object, and the representation of care in literature. Her research demonstrates strong interdisciplinary connections between literature, visual arts, and gender studies, with particular attention to how women have shaped cultural production through unconventional means. Victor-Barbeau Prize (essay category) from the Académie des lettres du Québec for 'Faire œuvre à deux. Le Livre surréaliste au féminin' (2023) Professor Oberhuber has supervised over 50 graduate students through their Master's and PhD programs, demonstrating her significant commitment to mentoring the next generation of scholars. Her research has been supported by multiple grants from the Social Sciences and Humanities Research Council of Canada (SSHRC) and the Fonds de recherche du Québec - Société et culture (FRQSC), including the current project 'Quand la littérature et la médecine s'accompagnent et nous accompagnent' (2024-2029). She also serves as director of the 'Paragraphes' publication series. She co-founded and serves as editor-in-chief of the digital journal MuseMedusa, which specializes in research-creation. She also co-directs the website 'Héritages de Claude Cahun et Marcel Moore,' which serves as a platform for information on conferences, publications, and exhibitions dedicated to the artist couple Claude Cahun (1894-1954) and Marcel Moore (1892-1972).
Daniel Baum is a Research Professor and Head of the Visual Data Analysis research group at the Zuse Institute Berlin (ZIB), which is affiliated with Freie Universität Berlin. His work spans across scientific visualization, computational biology, and image analysis, with a particular focus on developing methods for analyzing complex biological structures and neural circuits. He is actively involved in multiple interdisciplinary research projects including HFSP Chitons, Geometric Learning for Single-Cell RNA Velocity Modeling, and RobustCircuit. Dr. Baum's research interests center on visual and data-centric computing approaches to solve complex problems in biology and medicine. His work bridges the gap between computational methods and biological applications, with significant contributions to cryo-electron tomography analysis, neural circuit mapping, and geometric morphometrics. He develops innovative algorithms for 3D reconstruction, image segmentation, and visualization of biological structures, from molecular to organismal scales. His publication record demonstrates consistent contributions to visualization techniques applied to biological problems, with recent work focusing on neural circuit analysis in zebrafish and Drosophila, biomechanical studies of animal structures, and advanced methods for analyzing ancient artifacts. The research shows a clear trajectory toward increasingly sophisticated multimodal data integration and machine learning approaches. Dr. Baum leads a productive research group with several key collaborators who frequently appear as co-authors on his publications, indicating a strong mentoring relationship. His projects involve substantial funding from various sources supporting interdisciplinary collaborations across biology, computer science, and engineering. His laboratory at ZIB focuses on visual data analysis for complex biological systems, with particular strength in developing computational methods for neuroscience applications and biomaterial analysis. The group maintains strong collaborations with multiple institutions working on cutting-edge imaging technologies and biological model systems.
Jie Deng, Ph.D., is a Professor in the Department of Radiation Oncology at UT Southwestern Medical Center, where she serves as faculty in the Division of Medical Physics & Engineering. She is a certified MRI and MRI for radiation therapy medical physicist by the American Board of Medical Physics and holds a leadership role as a magnetic resonance safety officer. Dr. Deng is actively involved in both clinical and research aspects of medical imaging and radiotherapy, with a strong emphasis on integrating advanced imaging technologies into therapeutic workflows. Dr. Deng earned her academic degrees from prestigious institutions: a Bachelor of Science in Biomedical Engineering from Southeast University in China, a Master’s in Bioengineering from the University of Illinois at Chicago, and a Ph.D. in Biomedical Engineering from Northwestern University. She further enhanced her expertise by obtaining a Master of Science in Law from the Northwestern Pritzker School of Law, reflecting a multidisciplinary approach to her scientific work. Her research interests center on MRI physics , quantitative imaging , oncological imaging , and the application of artificial intelligence in medical imaging. She has pioneered work in MRI-guided radiation therapy, imaging biomarkers for therapeutic response, and AI-driven image reconstruction and artifact reduction. Her recent publications demonstrate a consistent focus on improving imaging accuracy, speed, and clinical utility, particularly in liver, pediatric, and oncological applications. The analysis of her 15 most recent articles reveals a strong trend toward deep learning-based image reconstruction , quantitative MRI biomarkers , and synthetic image generation for radiotherapy planning. Topics such as 4D-MRI, synthetic CT, motion artifact reduction, and AI fusion models dominate her scholarly output, indicating a forward-looking research trajectory centered on intelligent, fast, and precise imaging for personalized cancer therapy. Dr. Deng actively contributes to the scientific community through presentations at major conferences including the International Society for Magnetic Resonance in Medicine (ISMRM) and the American Association of Physics in Medicine (AAPM), where she shares innovations in MRI, adaptive radiotherapy, and AI integration. As an educator, Dr. Deng mentors medical physics residents and graduate students, delivering lectures on MR-only simulation, MR-linear accelerator practices, and medical imaging fundamentals. While no specific grants are mentioned in the text, her extensive publication record in high-impact journals suggests active research funding and collaborative projects. She is affiliated with key professional organizations and serves on UT Southwestern’s MRI Safety Committee, ensuring safe and effective use of MRI in clinical and research settings. Her work bridges the gap between engineering innovation and clinical application, making significant contributions to the field of radiation oncology and medical physics.
Linda Quirke serves as an Associate Professor in the Department of Sociology at Wilfrid Laurier University's Faculty of Arts, maintaining active contact through office DAWB 5-142, email lquirke@wlu.ca, and Teams phone number 1 548-889-5153. Her institutional position demonstrates ongoing engagement with academic duties and research leadership within the university's educational framework. Her research expertise spans several interconnected domains: Sociology of Education with focus on Ontario's private sector Parenting advice literature and historical shifts in childrearing Gendered foodwork and emotion labor in family contexts Children's leisure activities and cognitive development Institutional legitimacy strategies in non-elite schools Market-institutional tensions in educational organizations Quirke's scholarly trajectory reveals consistent thematic threads: evolving parenting narratives (particularly around obesity and food allergies), organizational adaptation in educational markets, and critical analysis of textbook representations. Her work bridges micro-level family practices with macro-level institutional analysis, emphasizing how social class permeates both educational structures and domestic life. Scientific Awards: No specific awards or honors documented in source materials Advising and funding details remain unreported in the provided texts, though her extensive publication history suggests significant research activity. Her teaching portfolio includes sociology courses, but specific pedagogical methods or student mentorship outcomes aren't elaborated. Lab affiliations or collaborative research teams also lack explicit mention in the available information.
Dr Andrew Elliott is a Senior Lecturer in the School of Statistics at the University of Glasgow. His research bridges Statistics , Computational Statistics , and Machine Learning & AI , with applications in Social & Urban Studies and Imaging, Image Processing & Image Analysis . Education: Not explicitly detailed in the text. Dr Elliott's work focuses on modeling in space and time , synthetic data generation , and network analysis . His recent publications explore fairness constraints in AI , agent swarms , and temporal network modeling , reflecting interdisciplinary applications in urban analytics and environmental science. His publications from 2014–2024 span network science , machine learning , image analysis , and geospatial studies . Key trends include privacy auditing , counterfactual explanations , and deep learning for network time series . Dr Elliott supervises doctoral students and has advised Zhengduo Zhao and Weiyue Zheng . He actively contributes to research groups in Statistics & Data Analytics and Machine Learning . Notable collaborations include work with Mihai Cucuringu and Gesine Reinert .
