Paul Kieffaber is an affiliated researcher in the Department of Data Science at William & Mary's College of Arts & Sciences. His work focuses on electrophysiological studies of cognitive processes, particularly aging-related changes in neural mechanisms. Research emphasizes error detection, executive control, and neurocognitive decline using EEG/ERP methodologies. Key areas include: Neural correlates of cognitive aging ERP analysis of error processing Neuroplasticity in aging populations EEG-based neurometric assessment development Recent publications explore theta/gamma oscillations in memory processes (2024), error-related negativity dynamics (2023), and auditory ERP components in schizophrenia (2023). Current research integrates computational neuroscience methods with traditional EEG analysis to understand age-related cognitive changes. No current students/awards listed in provided texts.
Giacomo Fiumara is an Associate Professor at the University of Messina, Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences. He holds academic rank since October 2021. Previously, he served as a Permanent Researcher (2008–2021) and secondary school teacher (1997–2008). He earned a Doctorate in Physics (1993) and a Degree in Physics (1989), both from the University of Messina. He is an associate member of the Accademia Peloritana dei Pericolanti and qualified as an associate professor in INF/01 and ING-INF/05 sectors. His research focuses on social network analysis, network science, data science, criminal networks, knowledge representation, bioinformatics, and computational modeling. He has supervised over 170 theses and advised PhD students in Mathematics and Computational Sciences. Key collaborations include work with Prof. Pasquale De Meo on criminal networks and complex systems, and international projects with institutions in the US, UK, China, and Australia. Teaching includes courses on Algorithms, Data Structures, Bioinformatics, and Machine Learning across Computer Science, Engineering, and Medical programs since 2000. He also contributed to international programs at Lviv Polytechnic, Birzeit University, Cluj-Napoca, and Murcia. His editorial roles include Associate Editor of IEEE Access and Academic Editor of Complexity. He holds a patent for predictive analysis of criminal organizations' social structures and has received FFABR research funding. Key awards include FFABR funding (2017) and recognition in the FFABR Unime 2020 II edition. He organized conferences like Crimenet 2014 and participated in high-profile events such as the 2022 Complex Networks conference in Palermo, presenting on quantum walks for criminal network analysis.
Céline Clauzel is a Professor of Geography at the University of Paris 1 Panthéon-Sorbonne and a member of the Laboratory for Social Dynamics and Space Recomposition (LADYSS). She holds a Junior membership in the University Institute of France (IUF, 2023). Her research focuses on spatial modeling of ecological networks, biodiversity management, and human-wildlife interactions, with a geographic emphasis on France, China, and urban environments. Research Projects: Co-leader of the COOLSCHOOLS project (2022–2025) and leader of the INTERFACE project (2022–2023). Key roles in TRAMARE, REAUMUR, and ecological transparency studies for transportation networks. Administrative Roles: Member of LabEx DynamiTe Steering Committee, Scientific Council of the Foundation for Research on Biodiversity (FRB), and elected member of LADYSS laboratory council. Her work bridges ecology and urban planning, emphasizing decision-support tools for biodiversity management. Recent studies explore urban green spaces, wildlife corridors, and citizen science applications in biodiversity monitoring. Awards: Junior IUF membership (2023). Supervises doctoral students focusing on topics like railway permeability, school biodiversity engagement, and connectivity modeling in urban environments. Collaborates with institutions like SNCF, CDC Biodiversité, and the Morvan Regional Natural Park. Active in interdisciplinary initiatives, including co-creating platforms for researchers and practitioners to address ecological challenges in infrastructure and urban development.
Zhen Liu is an Assistant Professor at the School of Data Science, CUHK-Shenzhen. His research focuses on generative models, 3D representations, and the synergy of spatial and semantic understanding in AI systems. With a PhD from Mila and Université de Montréal, he develops foundational methods for physics simulation, 3D assembly, and semantic reasoning in neural networks. His work bridges machine learning with applications in computer vision and graphics, emphasizing: Generative architectures for 3D content creation Diffusion model alignment techniques Efficient parameter finetuning strategies Dr. Liu mentors students in AI research and contributes to advancing 3D generative modeling paradigms.
Daanika Gordon is an Associate Professor of Sociology at Tufts University, with a secondary appointment in Studies in Race, Colonialism, and Diaspora. Her research explores the intersection of racial inequality, urban governance, and policing through organizational and interactional lenses. PhD, University of Wisconsin–Madison (2018) MS, University of Wisconsin–Madison (2013) BA, Development Studies & Sociology, UC Berkeley (2009) Her work connects theories of race and racism with urban political economy and organizational behavior, focusing on how: Policing functions as a tool for urban governance Racial inequalities emerge from race-neutral policies Segregation is dynamically produced through relational processes Recent publications analyze police funding debates, data science applications in policing, and the bureaucratic dissociation of race. Her groundbreaking 2022 book Policing the Racial Divide won the 2023 Edwin H. Sutherland Book Award. She teaches sociology of race, criminal legal systems, and research design while serving on the advisory committee for the Tufts University Prison Initiative. Her research has been funded by: Institute for Citizens & Scholars Bernstein Faculty Fellowship Neubauer Faculty Fellowship National Science Foundation
Prof. Valentina Boeva is an Assistant Professor at the Department of Computer Science, ETH Zürich, specializing in biomedical informatics. Her research focuses on integrating machine learning and computational methods to address challenges in genomics, oncology, and precision medicine. She holds a position in the Professur für Biomedizininformatik (Biomedical Informatics) and is based at CAB G32.2, Universitätstrasse 6, Zürich, Switzerland. Her work emphasizes applications such as cancer biomarker discovery, tumor heterogeneity analysis, and epigenetic profiling. She teaches courses including Machine Learning Seminar, Data Science Lab, and Machine Learning for Genomics. Her research group develops computational tools like CDState and UniversalEPI to decode complex biological systems. She actively publishes in top-tier journals, with recent work on exosome-driven diagnostics and chromatin interaction modeling. Her scientific contributions span methodologies for single-cell data analysis, survival modeling, and drug response prediction. She collaborates across disciplines to bridge computational science with clinical applications in cancer research.
Mengni Chen is a Tenure Track Assistant Professor at the Department of Sociology , University of Copenhagen , affiliated with the Faculty of Social Sciences . She holds a PhD from the University of Hong Kong and previously worked as a research scientist at institutions including the University of Cologne (Germany), Catholic University of Louvain (Belgium), and Vienna University of Economics and Business (Austria). Her research focuses on marriage/family dynamics, gender inequality, intergenerational relationships, socioeconomic development, and population dynamics. She teaches courses such as 'Population and Society,' 'Social Problems,' 'Family Sociology of a Changing Society,' and 'Advanced Quantitative Data Analysis.' Recent Research Highlights: - Analyzes late parenthood trends in East Asia. - Explores intergenerational emotional dynamics in aging Chinese families. - Investigates gender equality in household labor via Hong Kong case studies. - Examines spatial-temporal suicide determinants in China. - Compares life expectancy between Hong Kong and Japan. Professional Contributions: - Authored/edited 27 peer-reviewed publications since 2015. - Research spans sociology, demography, public health, and policy analysis. - Collaborations with international institutions in Europe, Asia, and beyond. - Active in policy-relevant demographic studies addressing societal challenges.
Marko Lovric is an Assistant Professor at Wageningen University & Research's Department of Forest and Nature Conservation Policy. He holds a PhD in forest policy from the University of Freiburg, Germany. His expertise spans forest policy, environmental governance, data analysis, and AI applications in forestry. He has 17 years of research experience, focusing on European ecosystem services, bioeconomy transitions, forest certification, and international forest policy formulation. Education: PhD in Forest Policy (University of Freiburg), prior roles include senior researcher at the European Forest Institute and assistant at the University of Zagreb's Faculty of Forestry. Research Interests: Marko’s work addresses forest policy implementation, ecosystem service valuation, bioeconomy modeling, and international trade dynamics. He employs quantitative methods, big data, and network analysis to explore governance innovations and sustainable forest management strategies. Projects: He coordinated the H2020 SINCERE project on forest ecosystem services and the Horizon Europe project on forest research ecosystems. Current projects include INTERCEDE, focusing on future forest incomes and ecosystem services. Teaching: Involves MSc courses in forest policy, including internships and thesis supervision in forest conservation policy. Labs/Teams: Active in Wageningen’s Forest and Nature Conservation Policy group, contributing to interdisciplinary projects on governance and bioeconomy transitions.
Professor Peta Mitchell is a leading scholar in digital media and geographies at Queensland University of Technology (QUT), where she holds a Professorship in the School of Communication and the Digital Media Research Centre (DMRC). She leads the Urban Media and Digital Geographies Research Group and serves as Director of Research Training for QUT's Faculty of Creative Industries, Education, and Social Justice. In 2023, Professor Mitchell was appointed to serve a three-year term on the Australian Research Council's College of Experts, recognizing her significant contributions to research in digital media and geographies. Professor Mitchell earned her Doctor of Philosophy from the University of Queensland. Her academic journey has established her as a prominent voice in the interdisciplinary field bridging geography, media studies, and digital culture. She has received prestigious fellowships including a Vice Chancellor's Research Fellowship from QUT (2014-2018) and a visiting fellowship from the Institute for Advanced Studies in the Humanities at the University of Edinburgh (2009). Professor Mitchell's research explores the complex connections among space, place, society, and the digital. Her work focuses on digital and media geographies, everyday digital and data cultures, digital inclusion, and network contagion. She has made significant contributions to understanding how digital technologies reshape our relationship with space and place, particularly in urban environments. Her research examines how location-aware technologies influence social dynamics, cultural practices, and power relations, with particular attention to issues of inclusion, privacy, and justice in digital contexts. Professor Mitchell has investigated how digital media practices shape experiences of belonging, particularly among marginalized communities, and how geospatial data is produced, circulated, and contested in contemporary society. Her extensive publication record reveals a trajectory of increasingly interdisciplinary work that bridges humanities, social sciences, and spatial sciences. Recent publications show a growing focus on the intersection of digital technologies with environmental concerns, multispecies justice, and urban governance. Professor Mitchell's work has evolved to address emerging challenges related to generative AI, smart city technologies, and the ethical implications of location-aware applications. Her research consistently engages with questions of power, equity, and social justice in digital spaces, making significant contributions to both theoretical frameworks and practical applications in the field. Vice Chancellor's Research Fellowship, Queensland University of Technology (2014-2018) Faculty research fellowship, Centre for Critical and Cultural Studies, University of Queensland Visiting fellowship, Institute for Advanced Studies in the Humanities (IASH), University of Edinburgh (2009) Professor Mitchell has successfully supervised numerous doctoral students whose research explores diverse aspects of digital media and geographies. Her current and former students have investigated topics including smart urban governance, digital privacy, diaspora media practices, digital inclusion, and the cultural dimensions of location-based technologies. She has secured substantial research funding through competitive grants, including multiple ARC Discovery and Linkage Projects. Her current projects include "Generative AI and the Future of Academic Writing and Publishing" (2025-2028) and "Promoting Low-Income Parents' Digital Media Literacies" (2025-2028), demonstrating her ongoing commitment to addressing pressing contemporary issues at the intersection of technology, society, and space. As leader of the Urban Media and Digital Geographies Research Group within QUT's Digital Media Research Centre, Professor Mitchell fosters interdisciplinary collaboration among researchers examining how digital technologies reshape urban spaces and social relations. Her research group brings together scholars from geography, communication, design, computer science, and the humanities to investigate the spatial dimensions of digital culture. The group's work has particular relevance for understanding the implications of smart city technologies, location-aware applications, and digital inclusion initiatives in contemporary urban contexts.
Melih Kandemir is an Associate Professor at the Department of Mathematics and Computer Science, Southern Denmark University. He also serves as Research Group Leader at the Bosch Center for Artificial Intelligence (2018–2021) and held a previous role as Assistant Professor at Ozyegin University (2017–2018). His research focuses on machine learning, Bayesian methods, reinforcement learning, and uncertainty quantification. **Education**: PhD in Computer Science from Aalto University (2013), specializing in 'Learning Mental States from Biosignals'. **Research Interests**: Machine Learning, Bayesian Inference, Reinforcement Learning, Deep Neural Networks, Stochastic Processes. His work emphasizes theoretical foundations and practical applications in domains like medical imaging, control systems, and robotics. **Awards**: Two Best Paper Awards (2017). **Grants & Projects**: Includes the Carlsberg Young Researcher Fellowship (2022–2026), Novo Nordisk Foundation grants (2021–2024), and DFF-funded research on PAC-Bayesian reinforcement learning (2025–2027). **Labs/Teams**: Leads research on Bayesian deep learning and reinforcement learning within the Bosch Center for AI and SDU's interdisciplinary groups.
Olga Vitek is a Professor at Northeastern University's Khoury College of Computer Sciences, with affiliated faculty status in the Department of Chemistry and Chemical Biology. Her research bridges statistical science and machine learning with mass spectrometry-based proteomics and systems biology, focusing on developing open-source software tools like MSstats and Cardinal for quantitative proteomic analyses and imaging. Education: PhD in Statistics (Purdue University), Postdoc at the Ruedi Aebersold Lab (Institute for Systems Biology) Leadership: Director of the Barnett Institute for Chemical and Biological Analysis Her work emphasizes: Statistical experimental design Signal detection in complex mass spectrometry data Causal inference in biomolecular networks Reproducible computational infrastructure Recent publications highlight advancements in quantitative proteomics , mass spectrometry imaging , and causal modeling , with applications spanning cancer research, immunology, and clinical diagnostics. Notable trends include deep learning integration for image analysis and open-source tool development for scalable, transparent workflows. Scientific accolades: Elected Fellow of the American Statistical Association 2021 Gilbert S. Omenn Computational Proteomics Award NSF CAREER award Chan-Zuckerberg Essential Open-source Software award Senior Member, International Society for Computational Biology
Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.
Dr. Paul Henderson is a Lecturer in Machine Learning at the School of Computing Science, University of Glasgow. He holds a BA in Mathematics (University of Cambridge, 2009), an MSc in Informatics (University of Edinburgh, 2010), and a PhD in Computer Vision (University of Edinburgh, 2018). His research focuses on generative AI, probabilistic machine learning, and minimally-supervised approaches to 3D computer vision, with applications in healthcare, computer graphics, and physical sciences. Education: PhD in Computer Vision (University of Edinburgh, 2018) MSc in Informatics (University of Edinburgh, 2010) BA in Mathematics (University of Cambridge, 2009) His work spans generative models, medical imaging, and robotics. Notable contributions include datasets like Flat’n’Fold and techniques in diffusion models for text-to-image retrieval. He has received grants including the Royal Society Research Grant (2022-2023) and the Vesuvius Challenge Autosegmentation Prize (2025). He supervises PhD students in topics such as medical image segmentation and generative AI. Teaching: CS5002 Advanced Programming, CS4061/CS5014 Machine Learning.
Christine ABDALLA MIKHAEIL is an Assistant Professor in the Department of Management of Information Systems at IÉSEG School of Management in France. She holds dual Ph.D. degrees in Business Administration with a focus on Information Technology from the University of Paris Dauphine (France) and Georgia State University (USA), alongside advanced degrees in Business Consulting and Administration from Paris Dauphine. Her research focuses on collective action dynamics in social media, cybersecurity and privacy challenges, artificial intelligence applications, and disinformation propagation. Recent work explores the adoption of privacy-enhancing technologies (PETs), paradoxes in hybrid work visibility, and data adequacy in qualitative IS research. She has published in leading journals such as Information Systems Journal and Information and Organization . Her articles reflect a strong emphasis on understanding socio-technical systems through interdisciplinary lenses, combining behavioral theories with digital technology analysis. No specific awards or grant details are mentioned in her profile. She currently advises no formally listed students.
Rongxing Lu is an Adjunct Professor at the Faculty of Computer Science, University of New Brunswick (UNB), Canada, since August 2016. Previously, he held positions at Nanyang Technological University (NTU), Singapore (2012–2016) and the University of Waterloo, Canada (PhD in 2012). His research focuses on applied cryptography, privacy enhancing technologies, and IoT-big data security. He has over 7,500 citations and received prestigious awards like the Governor General’s Gold Medal (2012) and the IEEE ComSoc Asia Pacific Outstanding Young Researcher Award (2013). He is an IEEE senior member and serves on editorial boards of journals like IEEE Network. **Education**: PhD in Electrical & Computer Engineering, University of Waterloo (2012), awarded Governor General’s Gold Medal Postdoctoral Fellow at University of Waterloo (2012–2013) **Research Interests**: Developing cryptographic protocols for IoT and big data systems Privacy-preserving techniques for distributed systems Secure communication in 5G/6G networks and vehicular systems **Awards and Recognition**: Recipient of multiple best paper awards in IEEE conferences 2016–2017 Excellence in Teaching Award at UNB **Editorial and Leadership Roles**: Symposium co-chair at IEEE Globecom’16 Secretary of IEEE ComSoc CIS-TC Organized special issues on fog computing security (Elsevier) and big data security (IEEE IoT Journal) **Key Contributions**: Pioneered privacy-aware data reporting schemes for vehicular networks Designed lightweight IoT authentication protocols Advanced secure machine learning frameworks with privacy guarantees
