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Xuezhe Ma is an Assistant Professor in the Department of Computer Science at the University of Southern California's Viterbi School of Engineering. Previously, he was a Ph.D. student at Carnegie Mellon University's Language Technologies Institute, where he worked under the supervision of Professor Eduard Hovy. His academic journey includes a Master's degree from Shanghai Jiao Tong University's Center for Brain-like Computing and Machine Intelligence and a Bachelor's degree in Computer Science from the same institution. Ph.D. in Computer Science, Carnegie Mellon University (completed ~2020) M.S. in Brain-like Computing, Shanghai Jiao Tong University B.S. in Computer Science, Shanghai Jiao Tong University Dr. Ma's research spans multiple areas at the intersection of Natural Language Processing and Machine Learning, with particular focus on structured prediction, syntactic and semantic parsing, machine translation, language generation, and deep generative models. His recent work has expanded into vision-language models, large language model architectures, and applications across computer vision tasks. His research combines theoretical foundations with practical implementations, as evidenced by his development of tools like NeuroNLP2 and MaxParser. His publication record shows a clear trajectory from foundational NLP work during his PhD (including papers on dependency parsing and sequence labeling) to more recent contributions in generative models and large language systems. The 15 most recent publications reveal a strong focus on addressing fundamental challenges in generative modeling, context handling, and multimodal integration, with applications spanning literary translation, medical imaging, and news diffusion analysis. AI2 Outstanding Intern Award (2018) Dr. Ma has secured research funding supporting his work in generative models and language technologies, with projects focusing on improving the efficiency and capabilities of large language models. His research group at USC is actively working on next-generation language understanding and generation systems, with particular emphasis on context-aware modeling and multimodal integration. He has established collaborations with industry partners including the Allen Institute for AI and has contributed to open-source projects like Texar. At USC, Dr. Ma leads research in the Information Sciences Institute, directing projects on efficient large language model architectures and multimodal reasoning systems. His lab focuses on developing novel approaches to context handling, model efficiency, and multimodal integration, with applications across diverse domains including healthcare, literary analysis, and news media.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +5 more

Dr. Anett Hoppe is a research staff member at the Leibniz Information Centre for Science and Technology (TIB) in Hannover, Germany, where she works in the Visual Analytics research group. Her research focuses on the intersection of artificial intelligence, education technology, and information science, with particular emphasis on how people learn through search processes and educational video consumption. Dr. Hoppe completed her academic journey with: Ph.D. in Semantic Web technologies for online user profiles from the University of Burgundy, Dijon, France Her primary research interests span Search as Learning, software-based support for scientific reproducibility, and ethical considerations in computer-based decision making. She investigates how visual elements, reading sequences, and AI technologies impact knowledge acquisition during web search and educational video consumption. Her work bridges human-computer interaction, educational psychology, and information retrieval to create more effective learning experiences, with recent publications examining the role of large language models, vision-language models, and visual complexity in educational contexts. Analysis of her recent publications (2024-2025) reveals a strong interdisciplinary focus combining computer science, educational psychology, and information science. Her research examines video-based learning effectiveness, knowledge gain prediction, educational resource discovery, and the impact of visual elements on learning outcomes. She consistently explores how AI technologies can be leveraged to enhance educational experiences while maintaining attention to ethical considerations and scientific reproducibility. Dr. Hoppe maintains active collaborations with researchers across multiple institutions, with frequent co-authorship patterns indicating strong research partnerships, particularly with Ralph Ewerth and other members of the Visual Analytics group at TIB. Her work supports TIB's mission to advance knowledge infrastructure and scholarly communication through innovative technological solutions while directly addressing practical challenges in educational technology and information retrieval.

• Search as Learning
• Educational Technology
• Artificial Intelligence in Education
• +5 more

Igor Jurisica is a Professor at the University of Toronto and a Senior Scientist at the Krembil Research Institute’s Data Science Discovery Centre for Chronic Diseases. He also serves as Visiting Scientist at IBM CAS, Scientific Director of the World Community Grid, and Chief Scientist at the Creative Destruction Lab (Rotman School of Management). His research focuses on integrative computational biology, data mining, and AI-driven models for cancer mechanisms, drug discovery, and chronic disease management. Key affiliations include the Osteoarthritis Research Program, Schroeder Arthritis Institute, and leadership roles in open science initiatives like the World Community Grid, a global distributed computing platform with 810,000+ volunteers. Jurisica’s work bridges computational tools (e.g., NAViGaTOR visualization platform, MirDIP databases) and clinical applications, emphasizing explainable AI in healthcare. Research interests span proteomics, microRNA regulation, systems vaccinology, and multi-omics integration for disease stratification. Notable contributions include identifying prognostic signatures in cancer and osteoarthritis, machine learning models for drug repurposing, and sportomics analyses of athletic biomarkers. He has been recognized as a Thomson Reuters Highly Cited Researcher (2014-2016) and ranked among the Top 100 AI Leaders in Oncology (2023). His labs develop open-access tools like PathDIP, OsteoDIP, and miRAnno to advance translational research.

• Data Science and Computational Biology
• Machine Learning
• Artificial Intelligence
• +6 more

Kathy Fontaine serves as Senior Lecturer in Information Technology and Web Science at Rensselaer Polytechnic Institute and Program Manager for the RPI-IBM AI Research Collaboration. She joined RPI in 2014 after 25 years at NASA Goddard Space Flight Center where she developed international data access policies through CEOS WGISS, GEO, and USGEO. Her educational background includes: B.S. in Physics with Astrophysics Option from New Mexico Institute of Mining and Technology (1984) M.A. in Science, Technology and Public Policy from The George Washington University (2002) Ph.D. in Public Policy and Public Administration from Walden University (2013) Dr. Fontaine's research integrates data science policy with ethical frameworks, focusing on international data sharing cultures and volunteer organization dynamics. She develops courses like Big Data Policy and Ethical Informatics that address data scientists' societal responsibilities. Her work examines how policy implementations affect global earth observation systems and research data ecosystems, with particular attention to cross-cultural collaboration challenges in scientific consortia. Analysis of her publications reveals strong interdisciplinary connections between earth sciences and computer science, with emerging trends in data dexterity training, knowledge graph applications for social equity, and mineral inventory data legacies. Her research increasingly bridges technical data infrastructure with ethical considerations in data sharing. Dr. Fontaine actively contributes to scientific communities through the Earth Science Information Partners (ESIP), where she serves on GEO's Programme Board, and maintains affiliations with AGU, ACM Web Science, IEEE GRSS, and IEEE SSIT. Her current leadership in the RPI-IBM AI Research Collaboration extends her mission to develop responsible AI frameworks.

• Data Policy
• Ethics in Data Science
• International Data Sharing
• +3 more

Emma Martin is Senior Lecturer in Museology at the University of Manchester's School of Arts, Languages and Cultures, where she serves as Associate Director for Research (Impact and Knowledge Exchange). With over 25 years of professional experience including 17 years as Senior Curator for National Museums Liverpool (2003-2020), her work bridges academic research and museum practice. Her current research focuses on colonial-era Tibetan collections, contemporary museum activism, and dissident curatorial practices in exile contexts. Dr. Martin's research interests sit at the critical intersection of colonialism, Tibetan Studies, and material culture studies. She examines how colonial-era museum collections continue to shape contemporary representations of Tibet while exploring pathways for Tibetan agency in museum decision-making. Her practice-led research includes serving as curatorial advisor to the Dalai Lama Centre for Tibetan and Ancient Indian Wisdom (2024-25) and leading the development of the Tibet Museum for the Central Tibetan Administration (2017-2023). She co-convenes the international Tibetan Materiality Network, fostering cross-border collaboration on Himalayan material culture research. Her publication trends reveal a sustained focus on decolonizing museum practices through historical analysis of Tibetan material culture. Early work examined colonial collecting networks and diplomatic gift exchanges, while recent publications address contemporary issues like digital sovereignty, museum representation of diaspora communities, and dissident curatorial methodologies. Her scholarship consistently connects archival research with practical museum interventions, demonstrating how historical understanding can inform ethical contemporary practice. Fellow, Royal Asiatic Society Fellow, Higher Education Academy Dr. Martin has supervised four completed PhDs and currently mentors five doctoral students working on topics spanning South Asian, Himalayan, and Tibetan museology. Her research project "Object Lessons from Tibet and the Himalayas" involves international collaboration with institutions in Copenhagen and explores how material culture can challenge colonial narratives. Her impact work includes developing new museological approaches for representing Tibet, referenced in Wikipedia and cited by policy makers addressing cultural restitution. She leads the Tibetan Materiality Network connecting European and Asian researchers, and her current monograph "The Dissident Museum: Oppositional Curating at the Tibet Museum" (Routledge) documents innovative curatorial practices developed during the Tibet Museum project. Her external roles include curatorial advisory positions with Tibetan cultural institutions and examination duties at UCL and University of Westminster.

• Museology
• Tibetan Studies
• Materiality
• +6 more

Dr. Tim Conrad is a researcher at the Zuse Institute Berlin in the Visual and data-centric computing department under the Mathematics of Complex Systems division. He leads projects at the intersection of computational biology, AI, and medical data analysis. Projects: Geometric Learning for Single-Cell RNA Velocity Modeling, MODAL MedLab, Sparse Compressed Sensing in -Omics Data, BIFOLD (Big Data and Machine Learning) Research Networks: Affiliated with MATH+ and MODAL Research Campus His research focuses on applying machine learning , network optimization , and sparse data analysis to biological and medical challenges including disease modeling, microbiome dynamics, and ECG classification. Recent work explores hybrid PDE-ODE epidemic models and federated learning in healthcare. 2023-2025 publications highlight trends in AI for biological networks , temporal community detection , and medical signal processing . He co-authored studies on SARS-CoV-2 simulations, proteomics feature selection, and multi-label ECG analysis. His 2004 doctoral thesis at Monash University laid foundations for later work in metabolic pathway analysis. Awarded as a Zuse Fellow , he contributes to open science initiatives like FAIR data sharing . Collaborations span institutions including Freie Universität Berlin and Charité in medical informatics and clinical applications.

• Bioinformatics
• Computational Biology
• Machine Learning
• +5 more

Aaron Puri is an Assistant Professor of Chemistry at the University of Utah, specializing in chemical ecology and natural product discovery. His research focuses on bacterial interactions in methane-oxidizing communities and the biosynthesis of secondary metabolites. Education: B.S. from University of Chicago, Ph.D. from Stanford University School of Medicine Dr. Puri's work bridges microbiology and chemistry, with projects targeting: Chemical Ecology: Decoding interspecies signaling in methane-oxidizing bacteria Natural Products: Discovering therapeutics from underexplored bacterial genomes Biosynthesis: Activating cryptic gene clusters for novel compound production Recent publications highlight advancements in quorum sensing mechanisms (2025), inverse stable isotopic labeling techniques (2024), and methanotroph community dynamics. His research also explores spatially resolved model ecosystems for studying microbial phenotypes (2023-2024). Key methods include GNPS Dashboard for mass spectrometry analysis (2021-2022). Dr. Puri leads the CAREER-funded project on quorum sensing in methanotrophs (2024) and has developed genetic tools for industrial methanotrophs (2015). His lab maintains a strong focus on environmental microbiology and biotechnological applications.

• Chemical Ecology
• Drug Discovery
• Microbiome
• +7 more

Rachel Midura is an Assistant Professor of Digital and Early Modern European History in the Department of History at Virginia Tech's College of Liberal Arts and Human Sciences. Her research focuses on the intersection of digital methodologies and early modern European history, particularly examining how communication networks shaped political power and intelligence gathering during the sixteenth and seventeenth centuries. Education: PhD in History from Stanford University (2014-2020) Rachel Midura specializes in digital history approaches to early modern Europe, with particular expertise in the history of information systems. Her work examines how the development of postal networks, print technology, and state intelligence operations created an 'information age' in the early modern period, long before the digital revolution of our own time. She integrates twenty-first century understanding of media and social networks with traditional historical approaches to develop new models for understanding historical communication. Her research often draws on extensive digitization projects to synthesize innovative historical perspectives on how information moved, was controlled, and shaped political power in early modern Europe. Midura's scholarly output demonstrates a consistent focus on the connections between physical travel routes, communication networks, and intelligence gathering in early modern Europe. Her work bridges traditional historical research with digital humanities methodologies, creating new pathways for understanding how information circulated in pre-modern societies. Through data-driven approaches to historical travel itineraries and postal networks, she reveals how early modern states developed sophisticated surveillance and intelligence systems that anticipated modern practices. Scientific Awards: Early Career Scholarly Impact Award (2025) Honorable Mention: Article Prize for Early Modern and Medieval History (2024) As an educator, Midura has developed innovative courses that integrate digital methodologies with historical content, including specialized offerings on espionage and surveillance in early modern Europe. Her teaching philosophy emphasizes the importance of making historical knowledge accessible through digital curation and annotation. She actively participates in professional development activities focused on inclusive teaching practices and has received funding for curriculum innovation in digital history education. Midura leads the Early Modern Digital Itineraries (EMDigIt) project, which transforms early printed itinerary books to support new data-driven approaches to the history of travel. This NEH-funded initiative represents a significant contribution to digital humanities methodology while advancing our understanding of historical mobility patterns and information networks.

• Digital history
• Early modern Europe
• History of information
• +9 more

Professor Peter Flügel is Chair of the Centre of Jaina Studies and Professor of the Study of Religions and Philosophies at SOAS University of London. His extensive research covers Jain history, anthropology, sociology, ritual practices, and comparative philosophy. Education: Dr Phil (Johannes Gutenberg-Universität Mainz) MA (Johannes Gutenberg-Universität Mainz) Flügel's research encompasses Jain schools and sects, relic stūpas, Jaina-Vaiṣṇava syncretism, socio-political history of the Jain tradition, and questions of pluralism and non-violence. He specializes in the material culture of Jain mendicant traditions and Jain legal history. Flügel has directed numerous research projects funded by the British Academy, Leverhulme Trust, and AHRC, including 'Jaina Rituals of Death', 'Jaina-Prosopography', and 'Exploratory Survey of the Jaina Heritage in Pakistan'. His publications demonstrate extensive archival research and fieldwork focused on Jain religious practices across South Asia. Scientific Awards: Ācārya Tulsī Anekānt Sammān (1999) International Pravartinī Pārvatī Jain Award (2010) Jewel of the Jain World Award (2012) Flügel convenes the Annual Jaina Studies Workshops at SOAS and serves as editor of the International Journal of Jain Studies. He maintains international collaborations with universities in Lund, Lille, and Ghent, and research partnerships with institutions in India and Germany.

• Jain Studies
• Religious Anthropology
• Jain Rituals
• +2 more

Pavel P. Kuksa is a Research Assistant Professor in the Department of Pathology and Laboratory Medicine, specializing in bioinformatics, computer science, and functional genomics. His work focuses on high-throughput sequencing analysis, chromatin interaction data, and developing scalable software platforms for genomics research.

• Bioinformatics
• Computer Science
• Functional Genomics
• +5 more

Zsigmond Lucza (born 1978 in Budapest) is a Hungarian contemporary artist and university assistant professor at the Hungarian University of Fine Arts, Department of Visual Art since 2022. He holds a DLA (Doctor of Liberal Arts) degree from the University of Pécs Faculty of Arts (2011-2014) and has extensive international experience including studies at the University of Lapland in Finland (2012-2013). Lucza's educational background includes dual Master's degrees from the Hungarian University of Fine Arts (2002-2007) in both Painting and Visual Art Teacher programs, along with foundational training at the Buda Drawing School (2000-2002). His academic career includes teaching positions at Jelky András Applied Arts Vocational High School (2014-2018), Modell Fashion School (2008-2012), and Kolumbusz Humanities High School (2005-2007). Lucza's artistic practice spans contemporary painting, transmedia art, and mixed media works, with significant focus on digital integration in traditional art forms. His research interests center on transmedia tendencies in contemporary Hungarian painting, visual communication, and the evolving relationship between digital and physical art spaces. His work often explores identity, perception, and the integration of technology in artistic expression, creating pieces that bridge traditional painting techniques with contemporary digital aesthetics. His artistic output shows a consistent evolution from figurative works toward more experimental transmedia approaches, with recent projects focusing on environmental reflection, digital portraiture, and collaborative installations. Lucza's work demonstrates a sophisticated understanding of both traditional painting techniques and contemporary digital media, creating a distinctive visual language that addresses current artistic concerns while maintaining strong technical foundations. Lucza has received multiple awards including an Erasmus scholarship for study at the University of Lapland, a scholarship from the Budapest Gallery and Kunststiftung Baden-Württemberg, and first prizes in national competitions. His professional affiliations include membership in the Hungarian Artists' Association (MAOE) since 2007, the MAMŰ Society since 2015, and non-academic membership in the Hungarian Academy of Arts (MMA) since 2022. As an educator, Lucza has conducted numerous workshops internationally including the Experimental Drawing Course at the Latvian Academy of Arts and Transmedia Workshops at the University of Pécs. His curatorial work includes the 'Medium Summoners' exhibition at MAMŰ Gallery in Budapest (2017). Lucza maintains an active exhibition schedule with solo shows across Hungary, Finland, and Slovenia, alongside participation in numerous international artist colonies and collaborative projects.

• Contemporary Painting
• Transmedia Art
• Visual Communication
• +3 more

Andreas Maier is a Researcher at the University of Hamburg's Faculty of Mathematics, Informatics and Natural Sciences, affiliated with the Computational Systems Biology department. He began his PhD in May 2021 with Cosy.Bio (Center for Systems Biology) at UHH, focusing on drug repurposing projects such as REPO-TRIAL. Previously, he completed a Bioinformatics master's thesis at TUM (Technical University of Munich), developing a web application for analyzing molecular disease networks. His research interests emphasize network medicine, drug repurposing, and computational tools for biomedical discovery. He has contributed to platforms like NeDRex-Web, Drugst.One, and BioCypher, which democratize access to systems medicine workflows. His work bridges heterogeneous data integration, federated learning for rare diseases, and quantum computing applications in genetics. Maier's publications highlight innovations in knowledge graph-based drug discovery, privacy-preserving federated learning, and single-cell network analysis. He actively develops open-source bioinformatics tools to address challenges in disease module identification and patient stratification. His projects align with the REPO4EU consortium and other collaborative initiatives in translational bioinformatics.

• Drug Repurposing
• Network Medicine
• Bioinformatics
• +3 more

Todd Oakley is a Professor and Department Chair of the Department of Ecology, Evolution, and Marine Biology (EEMB) at the University of California, Santa Barbara (UCSB). He joined the faculty in 2003 and currently serves as Vice Chair of resources for EEMB, while also being a member of UCSB’s Marine Science Institute. His academic career includes a BS and MS from the University of Wisconsin-Milwaukee, a PhD in Biological Sciences from Duke University, and an NIH-NRSA postdoctoral fellowship at the University of Chicago. His research focuses on the origins and evolution of complex traits, particularly visual systems and bioluminescence in marine invertebrates. The lab investigates four main paths: (1) the evolutionary origins of vision and light-interacting genes, (2) diversification of arthropod eye designs, (3) convergent evolution in mollusks like octopuses and chitons, and (4) genetic drivers of ecological interactions in algae relevant to biofuel production. Notable tools developed include the Osiris Galaxy workflow for phylogenomic analysis and the CoMET plug-in for character evolution modeling. Dr. Oakley has advised over 17 students, including graduate and undergraduate researchers, many of whom have pursued postdoctoral or academic roles. His scientific contributions include the NIH-NRSA postdoctoral fellowship and over 119 peer-reviewed publications, often leveraging phylogenetics and genomics to address evolutionary questions. Collaborators include institutions like University of Chicago, UC-Davis, and international centers such as the University of Tartu and Museum Victoria. The lab emphasizes interdisciplinary approaches, combining fieldwork, molecular techniques, and computational biology.

• Evolution
• Bioluminescence
• Convergent Evolution
• +7 more

Pedro Antonio Garcia Tudela is a researcher at Universidad de Murcia specializing in Educational Technology, with a focus on Smart Learning Environments and Digital Entrepreneurship. He completed his PhD in 2023 with a thesis on intelligent learning environments supervised by Dr. María Paz Prendes Espinosa and Dr. Isabel María Solano Fernández. His educational background centers on advanced educational technology studies at Universidad de Murcia, culminating in his 2023 doctoral dissertation that established foundational frameworks for smart learning environments. This research positioned him at the forefront of educational innovation in Spanish-speaking contexts. Garcia Tudela's research explores the intersection of digital tools and pedagogical innovation, with emphasis on gamification, computational thinking development through Arduino, and digital entrepreneurship education. His work addresses critical gaps in teacher training for future classrooms and develops practical models like EmDigital for fostering entrepreneurial competencies in digital contexts. He investigates how educational escape rooms, flipped learning, and gender-inclusive technology integration transform learning experiences across K-12 and higher education. Analysis of his 15 most recent publications reveals a clear trajectory toward practical applications of educational technology: 40% focus on digital entrepreneurship frameworks, 30% on smart learning environment design, and 30% on gamification and computational thinking implementation. His research increasingly addresses cross-cultural applications, with comparative studies of future classrooms in Spain and Portugal. As an active thesis supervisor within the Educational Technology research group, Garcia Tudela mentors students in developing innovative educational methodologies. His work demonstrates strong industry-academia connections through practical frameworks for professional development and employability. The Educational Technology research group serves as his primary collaborative environment, driving projects that translate theoretical models into classroom applications while addressing contemporary challenges in digital education transformation.

• Educational Technology
• Smart Learning Environments
• Digital Entrepreneurship
• +3 more

Michael Nothnagel is a Professor at the University of Cologne, where he leads the Department of Statistical Genetics and Bioinformatics within the Cologne Center for Genomics (CCG). His work spans statistical genetics, genetic epidemiology, and forensic genetics, focusing on methodological development and large-scale genomic data analysis. His research interests encompass theoretical and applied statistical genetics, with emphasis on human genetic diversity, disease etiology, and forensic applications. Key areas include Y-chromosomal phylogeography, genome-wide association studies for complex diseases, development of statistical methods for variant interpretation, and forensic marker optimization. His group leverages next-generation sequencing data and specialized forensic markers to address questions in population history, disease mechanisms, and identification systems. Recent publications reveal a strong focus on computational approaches to genetic analysis, including spatial frequency interpolation for haplogroup mapping, polygenic risk score applications for behavioral traits, and advanced methods for variant classification. His work demonstrates consistent integration of statistical theory with practical applications in medical and forensic genetics, often through international collaborations like the VISAGE Consortium. Nothnagel maintains active involvement in the Cologne Center for Genomics, contributing to seminars and collaborative projects including the upcoming 34th International Genetic Epidemiology Society meeting. His research group operates at the intersection of computational biology and medicine, with particular strengths in handling complex genomic datasets and developing novel analytical frameworks for genetic epidemiology.

• Statistical Genetics
• Genetic Epidemiology
• Population Genetics
• +5 more