Sébastien Fournier is a researcher affiliated with the University of Aix-Marseille, focusing on natural language processing, multimodal data analysis, and agent-based systems. He has contributed to projects like ANR GUIDANCE, ADNvideo, CoPains, and PhysSocial, emphasizing dialogue-assisted information access, video fingerprinting, persuasive health agents, and psychophysiological foundations of social behavior. Research areas: Aspect-Based Sentiment Analysis, Contradiction Detection in Reviews, Multimodal Data, Recommendation Systems Projects: ANR GUIDANCE (Workpackage 3 Leader), ADNvideo (2014-2016), CoPains (2019-2022), PhysSocial (2018-2021) His work extends to evaluating interactions in serious crisis management games, with supervision of PhD students like Ismail Badache and Adrian-Gabriel Chifu. He collaborates with institutions including LIS, LSIS, and ILCB (Institute of Language, Communication and the Brain).
Natasa Miskov-Zivanov is an Assistant Professor at the University of Pittsburgh where she leads the MeLoDy Lab (Mechanistic, Logical, and Dynamic Modeling). She holds a PhD in Electrical and Computer Engineering from Carnegie Mellon University and conducts interdisciplinary research at the intersection of computational methods and biological systems. Her education includes: PhD in Electrical and Computer Engineering, Carnegie Mellon University (2009) MS in Electrical and Computer Engineering, Carnegie Mellon University (2005) BS in Electrical Engineering and Computer Science, University of Novi Sad (2003) Her research focuses on developing computational frameworks and tools for biological systems modeling. Primary interests include: Automated knowledge extraction from biomedical literature Dynamic network modeling of cellular signaling pathways Development of standardized knowledge representation formats (BioRECIPE) Hybrid modeling approaches for complex biological systems Applications in cancer systems biology and immunology Her publications demonstrate consistent focus on computational biology methods development, with recent work emphasizing: Context-aware knowledge selection systems Automated model assembly from literature Biomedical text mining frameworks Hybrid multi-resolution modeling Standards for executable biological models She leads several funded research initiatives including DARPA's Big Mechanism program (AIMCancer W911NF-17-1-0135) and University of Pittsburgh-supported projects. Her lab develops open-source tools like CLARINET, ACCORDION, and VIOLIN that facilitate biological network modeling and knowledge extraction.
Anjali Adukia is an assistant professor at the University of Chicago Harris School of Public Policy and the founder and director of the MiiE Lab (Messages, Identity, and Inclusion in Education). She is a faculty research fellow at the National Bureau of Economic Research (NBER) in the Economics of Education and Children and Families groups, a research fellow at the IZA Institute of Labor Economics, a non-resident fellow at the Center for Global Development, and an affiliate of the Bureau for Research and Economic Analysis of Development (BREAD). Dr. Adukia earned her doctoral degree from Harvard University Graduate School of Education with a focus on the economics of education, along with master's degrees in international education policy and higher education from Harvard. She completed her undergraduate studies in molecular and integrative physiology at the University of Illinois at Urbana-Champaign. Her interdisciplinary background bridges the natural sciences with social science research methods. Her research explores how to reduce inequalities so children from historically disadvantaged backgrounds have equal opportunities to develop their potential. She examines factors influencing educational decisions and the role of institutions in improving child outcomes, particularly at the intersection of education and health. Adukia's work draws on large-scale data, often using artificial intelligence methods to expand social science tools and data sources. Her research spans educational infrastructure, representation in children's literature, restorative justice practices, and urban-rural educational disparities. Her publications reveal consistent themes in educational equity, with particular focus on how school infrastructure (like sanitation facilities), representation in educational materials, and disciplinary practices impact student outcomes. She employs innovative computational methods to analyze large datasets, including applying AI tools to measure representation in children's books and examining textbook content across different educational systems. NSF CAREER Award in economics (2024-2029) SREE Early Career Award (2023) William T. Grant Foundation Scholar Award (2018-2023) NAEd/Spencer Postdoctoral Fellowship (2018) APPAM PhD Dissertation Award (2014) AEFP Jean Flanigan Outstanding Dissertation Award (2015) 2021 Google Customer Award for Education Dr. Adukia serves on the editorial boards of Education Finance and Policy, Journal of Research on Educational Effectiveness, and Journal of Social Computing (IEEE). She organizes the annual AI in Social Sciences conference at the University of Chicago and continues to work with international non-governmental organizations including UNICEF and Manav Sadhna in Gujarat, India. Her research has been featured in major media outlets including The Economist, Wall Street Journal, Washington Post, and NPR.
Hubert Kowalski is a Professor at the Faculty of Archaeology, University of Warsaw, specializing in Warsaw's cultural heritage with focus on the Vistula River archaeology, historical buildings like the Kazimierzowski Palace, and university museum systems. His academic profile combines active teaching duties (with published consultation hours) and interdisciplinary research bridging archaeology, history, and museum studies. Research interests center on urban archaeology of Warsaw across historical periods, particularly the Swedish Deluge era and 17th-century architecture. His work integrates underwater archaeology of the Vistula River, analysis of historical correspondence (including interwar period documents), and studies of academic heritage collections. Key methodologies involve interdisciplinary approaches combining material culture analysis with archival research, environmental history, and museum pedagogy to reconstruct Warsaw's layered historical identity. Analysis of his 2020-2025 publications reveals consistent focus on three interconnected themes: recovery of artifacts during Vistula River low-water events (e.g., 'Archaeological Kilometer of the Vistula'), documentation of university museums and academic heritage collections, and reinterpretation of Swedish Deluge impacts through newly discovered sources. His output demonstrates increasing methodological sophistication through hydrodynamic modeling applications while maintaining deep engagement with Polish cultural identity through material heritage. Scientific Awards: No awards documented in provided materials. Advising and grants: Text contains no references to graduate students supervised or external research funding secured, though extensive publication record suggests independent research leadership. His conference participation (e.g., 'Rome and Barbarians', 'Women’s Perspectives in the Nile Valley') indicates active scholarly networking. Labs and teams: Affiliation with University of Warsaw's Faculty of Archaeology is primary institutional context, with specific connections to museum studies initiatives and Vistula River research groups. The 'Archeologiczny kilometr Wisły' project represents his key collaborative framework for river archaeology.
Nan Jia is Professor of Strategic Management at the USC Marshall School of Business, where she holds a prominent position in the Management and Organization Department. With a PhD from the Rotman School of Management at the University of Toronto, she has established herself as a leading researcher at the intersection of artificial intelligence, strategic management, and political economy. Professor of Strategic Management, USC Marshall School of Business Department: Management and Organization Academic Focus: AI applications in management, corporate political strategy, business-governance relationships Editorial Roles: Associate Editor, Strategic Management Journal; Editorial Board Member, multiple leading journals Her research expertise spans corporate political strategy, business-governance relationships, and the applications of Artificial Intelligence technologies in management. Professor Jia investigates how AI tools can enhance employee creativity, the dynamics of human-AI collaboration in workplace settings, and the political strategies firms employ in different regulatory environments, particularly focusing on China-US business relations. Her work demonstrates that AI and human managers can form a complementary relationship where AI provides superior analytical content while human managers with strong people skills deliver that content effectively. Professor Jia's research portfolio shows a clear trajectory toward understanding the complex interactions between emerging technologies and traditional business practices. Her recent publications focus on AI's impact on creativity, fairness in performance evaluation, and the political economy of innovation, particularly examining how trade policies and government interventions affect corporate behavior. The Strategic Management Journal has featured her field experiments demonstrating how AI assistance combined with human managerial skills creates optimal workplace outcomes. Associate Editor, Strategic Management Journal Faculty Promotion, Marshall School of Business (2024-2025) Featured Research in Financial Times, South China Morning Post, and other major media outlets Editorial Board Member for multiple leading academic journals in strategic management Professor Jia actively mentors students and collaborates with researchers across disciplines. Her work with postdoctoral researcher Yidan Yin on AI-generated responses that make people feel 'heard' has received media attention. She teaches doctoral-level strategic management courses (MOR-603) and applied product management (MOR-531), emphasizing critical thinking and creative problem-solving skills. Her research has been supported by grants examining the impact of AI on workplace dynamics, political connections in international business, and innovation patterns under different regulatory regimes. Professor Jia's work bridges academic rigor with practical business applications, particularly in the rapidly evolving landscape of AI integration in management practices.
Kamesh Madduri is an Associate Professor in the Department of Computer Science and Engineering at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His research focuses on graph analytics, parallel algorithms, and high-performance computing for large-scale data analysis. NSF CAREER Award (2013) His work contributes to the development of scalable graph partitioning algorithms, extreme-scale sparse data analytics, and heterogeneous computing frameworks. Recent projects include multilayer network analysis (NetSplicer) and GPU-accelerated graph processing (Jet). Key research areas include network science, computational biology, and distributed-memory graph algorithms. His publications highlight applications in genomic workflows, advertising keyphrase recommendation (Graphite/BroadGen), and large-scale hydrology data management. Collaborative Research: CCRI (2021-2023) SHF: Medium: NetSplicer (2020-2024) PPoSS: Extreme-scale Sparse Data Analytics (2018-2022) XPS: Genomic Workflows Acceleration (2014-2020) EAGER: SME Manufacturing Integration (2024-2026)
Dr. Gillian Pink is a Senior Researcher at the Voltaire Foundation , University of Oxford, specializing in the digitization and analysis of Voltaire's marginalia , notebooks , and working manuscripts . Her research spans French Enlightenment literature , manuscript studies , and book history . Deputy General Editor of the Digital Voltaire project Member of Société des études voltairiennes Associated with Équipe Écritures et Lumières (ITEM, Paris) Her work integrates digital humanities with traditional textual criticism , focusing on the genesis of literary texts and authorial reading practices . Recent publications and conference papers analyze Voltaire's annotation systems , textual reuse , and collaborative manuscript production . She contributes to critical editions of Voltaire's posthumous works and marginalia .
Tiago Manuel Ribeiro Gomes is an Assistant Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho, Portugal. He is also a Senior Researcher at Centro ALGORITMI and a member of both the IE R&D Group and the ESRG R&D Lab. Holding a Ph.D. in Electronics and Computers Engineering, his research focuses on embedded real-time systems, computer architectures, and hardware/software co-design for IoT devices. Academic Degree: Ph.D. in Electronics and Computers Engineering Current Position: Assistant Professor, School of Engineering, University of Minho Gomes has led extensive research in IoT systems over 15 years, particularly in hardware acceleration for automotive LiDAR sensors, secure embedded systems, and efficient OS frameworks for low-end devices. His work includes the EU-funded CROSSCON project and spans hardware-assisted security, dynamic binary translation, and wireless sensor networks. Recent publications highlight his expertise in automotive sensor technology, with articles like FOG-Zip for LiDAR compression, SecureQNN for TinyML security, and Hardware-Assisted Range Image Generation for LiDAR processing. His work bridges IoT, embedded systems, and cybersecurity, focusing on real-time performance and hardware-software co-design. Projects include the development of reliable/secure automotive sensor solutions and EU project CROSSCON. He contributes to open-source frameworks like UTango for IoT security and investigates heterogeneous fault tolerance architectures using Arm/RISC-V processors. Labs: IE R&D Group, ESRG R&D Lab Education: Ph.D. in Electronics and Computers Engineering, Master’s in Telecommunications Engineering (both from University of Minho)
Professor Imogen Tyler is a leading sociologist at Lancaster University , renowned for her groundbreaking work on stigma, social abjection, and resistance . As a Fellow of the Academy of Social Sciences and recipient of the Stanford-Elsevier Top 2% Scientist ranking, Tyler's research spans social inequality, race, citizenship, and historical sociology , with a focus on neoliberalism's impact. Her influential books, Revolting Subjects (2013) and Stigma: The Machinery of Inequality (2020), have become essential texts in global sociology curricula. Key Research Themes : Stigma as structural power, anti-racist education, waste colonialism, welfare state critique, and community-aligned research methods. Recent Projects : Hard Times: Poverty and Protest in Britain and Elemental Inequalities: Struggles for Life Against State-Sanctioned Killing . Tyler's scholarly output reveals consistent engagement with neoliberal governance, racialised poverty, and creative resistance across two decades. Her scientific accolades include the Lancaster University Research Award (2014), Philip Leverhulme Prize (2015), and recognition for her Stigma Machine research (2020s). She actively collaborates with public institutions and community groups , exemplified by her work with Lancaster Black History Group and Lancaster Museums Service , which earned a Decolonizing Award (2023) runner-up distinction. Academic Leadership : Serves on the European Research Council Advisory Board (2024-), Academy of Social Sciences Council (2022-), and multiple UK research councils. Public Engagement : Developed KS2 Teaching Resources on 18th-century Black Lancastrians, produced Stigma Conversations Podcast , and created Connected Sociologies Video Lectures with 9k+ views.
Alex Coad is Professor at Waseda University’s Graduate School of Business and Finance, Faculty of Commerce, Tokyo. A 2007 PhD graduate of Université Paris 1 Panthéon-Sorbonne, he specialises in industrial dynamics, entrepreneurship and applied econometrics, with field-leading work on high-growth firms, innovation policy and firm survival. Education PhD student, Université Paris 1 Panthéon-Sorbonne, 2004-2007 Research Interests Coad’s research straddles three tightly linked domains: (i) the life-cycle of firms—how they start, grow, innovate and exit; (ii) the identification and support of high-growth enterprises (gazelles, scale-ups) and their role in job creation and productivity; and (iii) the econometric evaluation of innovation and entrepreneurship policies, including post-crisis resilience after COVID-19. He employs large micro-data panels, quasi-experimental designs and, more recently, machine-learning techniques to uncover robust empirical regularities. Publication Landscape Across 119 Scopus-indexed papers (h-index 44) and 17 000+ Google-Scholar citations (h-index 59), Coad’s recent output reveals three dominant streams: (1) policy-oriented studies on European high-growth firms and scale-ups; (2) COVID-related analyses of firm vulnerability, investment expectations and recovery paths; and (3) methodological contributions linking random-forest prediction to gazelle identification. His work consistently blends rigorous econometrics with actionable policy insight. Honours & Awards 2021 Waseda Research Award Teaching & Doctoral Supervision At Waseda he teaches graduate courses in Firm Growth & Innovation, Econometrics, Time-Series Analysis, Data-Science for Management and Japan Industry Studies, and supervises research seminars for the MSc in Finance. No individual student names are listed in the supplied material. Grants & Teams Coad leads or co-leads large EU-funded micro-data projects on productivity, innovation and COVID resilience, often involving cross-country research consortia; specific grant numbers or budgets are not disclosed in the text.
Professor Tomoji Kishi is a distinguished faculty member at Waseda University's School of Creative Science and Engineering, where he has been serving since 2009. Previously, he held academic positions at Japan Advanced Institute of Science and Technology (2003-2009) following a 21-year career at NEC Corporation (1982-2003). He earned his Ph.D. in Information Science from Japan Advanced Institute of Science and Technology in 2002, building upon his earlier engineering graduate studies at Kyoto University. Professor Kishi's research focuses on software engineering, particularly in software product line development, model checking, formal verification, and aspect-oriented modeling. His work bridges theoretical formal methods with practical applications in embedded systems, automotive software, and IoT technologies. He has made significant contributions to scalability challenges in model checking for configurable systems and has pioneered approaches to variability management and approximate modeling techniques. His publication record demonstrates remarkable consistency and evolution, with 42 papers and 153 citations according to Scopus data (h-index: 7), spanning from foundational work in software architecture in the 1990s to cutting-edge research on AI-enhanced verification methods in 2025. His recent work shows increasing application of machine learning techniques to traditional formal methods problems, particularly in the context of highly configurable systems and IoT applications. ITS Standardization Activity Merit Prize (2022) from Society of Automotive Engineers of Japan IPSJ/ITSCJ Standardization Contribution Award (2017) IPSJ/ITSCJ Project Editor Award (2016 and 2013) Information Processing Society of Japan Society Activity Contribution Award (2010) IPA/SEC Journal Best Paper Award (2007) Information Processing Society of Japan Yamashita Memorial Research Award (1998) Professor Kishi has led multiple JSPS-funded research projects, including recent work on 'variability management methods prioritizing usability through variability mining' (2020-2023) and 'utility-first modeling method' (2017-2020). His industry collaborations, particularly with automotive systems developers, demonstrate the practical impact of his research. He maintains active membership in major professional societies including IEEE Computer Society, ACM, and the Information Processing Society of Japan.
Satoru Hayamizu is a Professor at Waseda University 's Green Computing Systems Research Organization , with a career spanning over four decades. His research focuses on Audio-Visual Speech Recognition , Machine Learning , and Medical Informatics , as evidenced by 126 publications and an h-index of 18. Education: The University of Tokyo (PhD in Mechanical Engineering) Prior affiliations: Gifu University (2002-), National Institute of Advanced Industrial Science and Technology (1981-2001) Research Interests include: Audio-visual speech recognition with sparse representation and DNN techniques Development of low-cost CNN-based road condition detection systems Swallowing function evaluation using acoustic and image processing Human behavior analysis for service operation estimation Research Trends reveal consistent work in multimodal signal processing (2006-2024), deep learning applications (2012-2024), and medical diagnostic systems (2006-2017). His publications show integration of sparsity modeling (2012-2021), industrial equipment diagnostics (2018-2021), and social impact technologies (2013-2024). Research Projects funded by Japan Society for the Promotion of Science include: Swallowing timing estimation (2018-2021) Multimodal silent speech recognition (2016-2020) ICT-based piano learning systems (2013-2016) Keyword display mechanisms (2010-2012) Labs & Collaborations include partnerships with Satoshi Tamura (co-author on 12+ papers), Hidekazu Fukai , and Chiyomi Miyajima . His work bridges academic research and industrial applications , particularly in manufacturing AI (2024 book) and Timor-Leste infrastructure monitoring.
Federico D'Asaro is a researcher and PhD student at Politecnico di Torino, affiliated with the Department of Control and Computer Science (DAUIN) and the Computer Graphics & Vision Group (CGVG). He works as an external lecturer and teaching assistant for the Applied Data Science Project course in the Data Science and Engineering program. His research focuses on Vision-Language Models (VLMs), particularly addressing the Modality Gap in multimodal feature spaces and their applications in downstream tasks like semantic segmentation and speech emotion recognition. Education: Master's degree in Data Science and Engineering (2021), currently pursuing PhD in Computer and Systems Engineering (39th cycle, 2023-2026). His research at the intersection of Natural Language Processing and Computer Vision investigates how reducing the Modality Gap improves crossmodal performance. Recent work applies Large Speech Models (LSMs) to cross-lingual emotion recognition and non-verbal vocalization tasks. He collaborates with researchers like Andrea Bottino, Giuseppe Rizzo, and Juan José Márquez Villacis on projects involving multimodal deep learning and feature extraction. The trends in his publications highlight expertise in multimodal learning (Vision-Language Models, speech-text alignment), deep learning for segmentation and emotion recognition, and crossmodal adaptation in speech processing. His 2025 work focuses on contrastive alignment and non-verbal vocalization, while 2024 studies explore transfer learning of speech models across languages. Teaching Contributions External lecturer for Applied Data Science Project (2025/26) Course collaborator for Applied Data Science Project (2024/25) Federico is part of the Computer Graphics & Vision Group (CGVG) , contributing to interdisciplinary projects that bridge Computer Vision , Natural Language Processing , and Speech Emotion Recognition . His work emphasizes practical applications of multimodal models in real-world scenarios.
Daniele Toninelli is an Associate Professor of Economic Statistics (SECS-S/03) at the University of Bergamo's Department of Economics, where he also serves as Director of the 'Data Analyst for Strategic Decisions' program, Internship Manager for the department, and member of the School of Economics and Management's Joint Teacher-Student Commission. His educational background includes a PhD in Marketing for Business Strategies (University of Bergamo, 2009), Master's in Statistics for Market Research (University of Milan-Bicocca, 2004), and Degree in Statistical and Economic Sciences (University of Milan-Bicocca, 2003). Toninelli's research focuses on: Survey and web survey methodology design and optimization Integration of big data for economic and social indicators Development of price indexes and composite indicators Social media analytics for economic measurement His work bridges statistical theory with applications in labor markets, sustainability metrics, and environmental data analysis. Teaching activities encompass undergraduate and graduate courses including Economic Statistics, Quantitative Methods for Business Data Analysis, Advanced Business Statistics, and specialized 'Data Skills' modules covering visualization, survey methods, and SAS certification preparation. International research collaborations include visiting positions at Statistics Canada (2008-2013), University of Ottawa (2012-2013), VŠB-Technical University of Ostrava (2012-2013), RECSM at Universitat Pompeu Fabra (2014), and guest lectures at University of Ljubljana (2018). He previously served on the management committee of the WEBDATANET network (COST Action IS1004). Professional experience includes roles at PiTre Milan, IBM Semea/Celestica, and Multiplex Arcadia, applying statistical expertise in industrial settings.
David Sasseville is a Post-Doc researcher in Comparative Linguistics (Hittitology) at Philipps University Marburg, specializing in Anatolian languages with particular focus on Luwian, Lycian, and Lydian. A French-Canadian from the Gaspésie peninsula of Québec, he completed his undergraduate studies in Ancient Greek, Latin, and Historical Linguistics at Concordia University in Montreal before pursuing two Master's degrees at Marburg University: one in Indo-European Linguistics focused on the Anatolian branch, and another in Ancient Greek Philology. His research centers on the linguistic structure and historical development of Anatolian languages, with special emphasis on verbal morphology, phonology, and syntax. Through meticulous philological analysis combined with comparative linguistic methods, Sasseville bridges traditional philology with modern linguistic theory to reconstruct earlier stages of these languages and their relationship to Proto-Indo-European. Sasseville's scholarly output demonstrates consistent advancement in understanding Anatolian languages through careful examination of fragmentary texts. His 2021 monograph Anatolian Verbal Stem Formation: Luwian, Lycian and Lydian provides a comprehensive classification of verbal stem classes across these languages. His more recent work includes studies on Luwian dative-locative endings, Lydian o-vocalism, Palaic texts from Hattusa, and the identification of new languages in Hittite archives. He actively collaborates with international scholars including Susanne Görke (with whom he's preparing a new edition of Palaic texts from Hattusa), Elisabeth Rieken, Ilya Yakubovich, and Annick Payne across multiple institutions. His work on the eDiAna digital dictionary project has involved supervising academic internships for doctoral student Oscar Billing from Uppsala University and MA student Jonas Döll from Philipps University Marburg. Sasseville teaches a diverse range of courses including Hieroglyphic Luwian, Cuneiform Luwian, Palaic, Historical Grammar of Sanskrit, Hittite Reading for Beginners, Latin Linguistics, Lycian Varieties, and Introduction to Historical Linguistics, reflecting his broad expertise across ancient languages and linguistic theory.
