Amir-Hossein Akbari is a Clinical Assistant Professor in the Department of Pathology at the University of Southern California (USC). His work focuses on molecular pathology, particularly in renal and urologic tumors, integrating immunohistochemistry and genetic assays to advance clinical diagnostics. He holds an MD degree, though specific education details are not elaborated in the text. His research interests emphasize the molecular characterization of tumors, including TSC2/mTOR pathway alterations in renal neoplasms and mucinous borderline tumors of the pelvicalyceal system. He also explores treatment strategies for prostatic adenocarcinoma, combining pathological insights with clinical applications. Dr. Akbari has published three recent studies (all 2024) in pathology journals, reflecting his commitment to bridging molecular findings with clinical practice. These publications address diagnostic challenges in renal tumors, urologic tumor classification, and therapeutic options for prostate cancer. No scientific awards, grants, or formal advisees are explicitly documented here.
Associate Professor Josiah Poon is affiliated with the School of Computer Science at the University of Sydney. His research focuses on applying data mining and IT techniques to Traditional Chinese Medicine (TCM), particularly analyzing herbal combinations for effective treatments. He collaborates with institutions in China to improve TCM evidence and has contributed to clinical data analysis, medical informatics, and multimodal AI systems. Teaching includes courses such as INFO1003 (Foundations of IT) and INFO9003 (IT for Health Professionals). Current research students are Rina CABRAL (Multimodality Representation), Yan LI (Long Document Comprehension), and Xiaobin LU (Financial Decisions). Research highlights include developing algorithms to quantify TCM efficacy, analyzing complementarity in herbal combinations, and applying machine learning to healthcare data. Notable projects include a randomized controlled trial on pneumococcal vaccination (2021) and a Google-funded multimodal health detection system (2020). Key areas of expertise span TCM informatics, medical data analytics, and AI-driven healthcare solutions. His work bridges Eastern/Western medicine through computational methods, emphasizing evidence-based practices in TCM.
Maqbool Hussain is a Senior Lecturer in Computer Science at the College of Science and Engineering. His research focuses on healthcare informatics, artificial intelligence (AI) applications in medical decision-making, and the development of knowledge-based systems for aerospace and healthcare sectors. He has contributed significantly to areas such as digital twin frameworks for critical care workflows, clinical decision support systems, and semantic interoperability in healthcare. Research Interests Hussain’s work spans multiple disciplines, including: Healthcare Informatics and AI-driven medical solutions Knowledge Graphs and Large Language Models (LLMs) in healthcare and aerospace Digital twins for optimizing critical care and aerospace maintenance Data-driven clinical decision support systems Medical data security and interoperability standards Machine learning for text annotation and classification Recent Research Trends Recent publications highlight his focus on integrating advanced technologies like LLMs and digital twins into healthcare and aerospace contexts. His work addresses challenges in critical care workflow optimization, kidney disease diagnosis, and aerospace product maintenance through innovative knowledge graph approaches. He also explores the application of transformer-based models for text analysis and the secure exchange of medical data using biometric methods. Labs and Teams Hussain is affiliated with the College of Science and Engineering, contributing to interdisciplinary research teams focused on healthcare technology, aerospace systems, and AI applications. His collaborations span academic and industry partners, emphasizing practical solutions for healthcare informatics and aerospace engineering challenges.
Marc Benamou is a Professor of Music and Director of the Javanese gamelan ensemble at Earlham College, located in Richmond, Indiana. He holds a Ph.D. from the University of Michigan, alongside degrees from Oberlin College and Université de Paris X. His research focuses on ethnomusicology, with primary specialization in Javanese gamelan music and Peruvian saxophone orchestras. He has conducted fieldwork in Indonesia, Peru, and France, and his work explores aesthetics, musical meaning, and cross-cultural comparisons. Recent projects include a National Endowment for the Humanities-funded initiative to transcribe and analyze Javanese gamelan lyrics from cassette recordings. Benamou’s teaching emphasizes global musical traditions beyond the Western canon, including courses on African, Japanese, and South American musics. He speaks French, Indonesian, and Spanish fluently, and has presented his research internationally in countries like Argentina, Italy, and Israel. His interdisciplinary interests span music and food, gender studies in music, and the intersection of musicology and linguistics. He has collaborated with institutions such as the Institut Seni Indonesia in Surakarta and participated in faculty research initiatives in Japan and the U.S. Benamou’s career combines academic rigor with artistic practice, having performed as a singer of Javanese music and a classical trumpet player. His dedication to Earlham’s liberal arts mission is evident in his emphasis on student-centered learning and fostering cross-cultural connections among students. He has mentored students like Yasmine Lee and Tinisha Newland in research on African-American classical musicians, blending scholarly inquiry with community engagement.
Margaret Cuonzo is an Associate Professor and Chair of the Philosophy Department at Long Island University (LIU). She holds a B.A. from Barnard College and an M.Phil and Ph.D. from The Graduate Center, CUNY. Her research focuses on Philosophical Paradoxes, Feminist Issues in Science, and Philosophy of Language. She has published extensively on paradox theory, including interdisciplinary dialogues and solutions to classical paradoxes like the Sorites. Her work bridges logic, epistemology, and social dynamics, with notable contributions to understanding gossip in digital spaces and queer perspectives in scientific discourse. Dr. Cuonzo’s publications span academic journals and reviews, emphasizing paradox resolution frameworks, feminist critiques of scientific methodologies, and cross-disciplinary analyses. She actively participates in academic panels and commentary, contributing to debates on logical systems and ethical communication. Her teaching and research roles at LIU’s College of Liberal Arts and Sciences reflect her commitment to integrating rigorous philosophical inquiry with contemporary societal challenges. No scientific awards are explicitly listed, though her academic output indicates significant scholarly contributions. Her advising and grant activities are not detailed in the provided texts, but her leadership in the Philosophy Department underscores her mentorship role. She is affiliated with LIU’s Brooklyn Campus and contributes to its academic community through her editorial work in journals like APA Newsletters.
Ella Haig is an Associate Professor of Artificial Intelligence at the University of Portsmouth, UK, affiliated with the School of Computing within the Faculty of Technology. She is also a member of the Portsmouth AI and Data Science Centre, Future of Law, Innovation and Technology Research Centre, and Centre for Cybercrime and Economic Crime. Her academic journey includes a PhD in Computer Science from Birkbeck College (University of London), an MSc in Learning Technologies from the National College of Ireland, and a Postgraduate Certificate in Learning and Teaching from the University of Portsmouth. Her research focuses on Intelligent Systems, User Modelling, Data Mining, and Decision Support, with notable contributions to emotion recognition, machine learning, and educational data mining. Ella has published over 140 works, including articles on multimodal emotion detection and comparative analyses of AI models like GPT-3 and BERT. She actively contributes to conferences, such as the IEEE World Congress on Computational Intelligence and the International Conference on Educational Data Mining. Ella has secured grants totaling over £235,000 for projects like the KTP Citizens Advice initiative, exploring technology solutions for public services. Her work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Notable achievements include a 2023 Best Paper Award for her research on multimodal emotion recognition systems.
Kevin Stange is a Professor of Public Policy and Education (by courtesy) at the University of Michigan's Ford School of Public Policy, where he serves as co-director of the Education Policy Initiative and director of the PhD Program. He is also a Research Associate at the National Bureau of Economic Research and a faculty affiliate of the Center for the Study of Higher and Postsecondary Education at the Marsal Family School of Education. His educational background includes: Bachelor of Science in Mechanical Engineering and Economics, Massachusetts Institute of Technology (1999) Ph.D. in Economics, University of California, Berkeley (2008) Stange's research focuses on empirical labor and public economics within education contexts. He investigates how higher education shapes labor market trajectories, geographic mobility, and responses to skill demand shifts. Current projects examine Michigan's financial aid programs and college major impacts on career outcomes, utilizing large-scale datasets like College and Beyond II to analyze postsecondary pathways and institutional effectiveness. His recent publications (2023-2025) emphasize college major effects on earnings inequality, financial aid efficacy, community college transfer pathways, and graduate mobility patterns. These works leverage administrative data to address policy-relevant questions about educational equity and labor market alignment. Key recognition includes: Robert Wood Johnson Scholar in Health Policy Research Stange has secured major funding from the U.S. Department of Education, National Science Foundation, Spencer Foundation, W.T. Grant Foundation, Robert Wood Johnson Foundation, and Russell Sage Foundation. During 2022-2023, he served as Senior Advisor to the Under Secretary at the U.S. Department of Education, applying his research expertise to federal policy. He co-directs the Education Policy Initiative, which produces evidence-based research for education practitioners, and spearheaded the College and Beyond II dataset containing 50 million course records from 19 universities. This resource enables comprehensive analysis of student pathways and institutional effectiveness across diverse higher education contexts.
Gaël Richard is a Professor at Télécom Paris specializing in machine learning and audio signal processing. He leads the Hi! Paris center, focusing on AI and data science applications. His research emphasizes hybrid interpretable AI for sound analysis, including projects like Hi-Audio funded by a €2.5M ERC Advanced Grant (2022). Key areas include machine listening, music source separation, and speech processing. Applications span autonomous vehicle acoustics and music technology. Notable contributions include neural audio compression (QINCODEC), diffusion models for music synthesis (Diff-TONE), and source separation techniques (Inverse Drum Machine). Research & Awards Recipient of the 2022 ERC Advanced Grant for the Hi-Audio project exploring hybrid AI models that integrate domain knowledge with neural networks. This approach reduces data requirements and enhances model interpretability. Active in audio-visual scene analysis and weakly-supervised learning systems. Affiliations & Labs Executive Director of Hi! Paris, a multidisciplinary lab advancing AI and data science for societal impact. Collaborates on projects like the HI-AUDIO online platform for distributed music data collection and the MAD-EEG EEG dataset for auditory attention decoding.
Veronique MAGRI is a Professor of Exceptional University Class at Université Côte d'Azur (UCA), affiliated with the Department of Modern Literature. She leads research in textual analysis and digital humanities, focusing on computational methods in literary studies. Her roles include directing the Logométrie research team (2014–2018) and the Nouvelles textualités axis (2018–2022) within the CNRS UMR 7320 Bases, Corpus, Language (BCL). She serves on ANR’s Scientific Evaluation Committee (CE 38), HCÉRES, and UCA’s academic governance bodies. Her administrative roles include leading the Department of Modern Literature (2009–2013) and overseeing the Saint-Raphaël Connected Campus (2020–present). Education: 2006: Habilitation to Direct Research (Université Côte d'Azur) 1993: Doctorate in Language Sciences and Techniques (university unspecified) 1989: External Aggregation of Modern Letters Research focuses on AI-driven textual analysis, travel narrative poetics, and stylistics. She pioneers digital humanities tools for corpus-based studies and explores linguistic patterns in modern French literature. Recent work includes applying deep learning to authorship analysis and examining migrant narratives through textual linguistics. Advising and grants: She co-created the distance-learning Master of Letters program and has held leadership in institutional committees. Her grants include ANR-funded projects and collaborations with international agencies like FNRS. Labs/Teams: Director of BCL’s Logométrie team and Nouvelles textualités research axis, advancing interdisciplinary textual studies.
Dr. Ahmed Abdeen Hamed is a former Assistant Professor of Data Science and Artificial Intelligence at Norwich University and a former Research Team Leader in Clinical Data Science. He holds a Ph.D. from the University of Vermont (2014) and has extensive industry experience in pharmaceutical research. His work focuses on computational methods for drug discovery, network analysis, and AI-driven healthcare solutions, particularly in drug repurposing for diseases like COVID-19. He has developed algorithms such as MolecRank and NeoNet, and holds a patent for specificity-based molecule ranking systems. Education: PhD in Data Science (University of Vermont, 2014). Research Interests: Network-based drug discovery, biomedical informatics, AI in healthcare, clinical data science, and combating misinformation using machine learning. His recent work emphasizes leveraging clinical trials and biomedical literature to predict treatment efficacies through computational frameworks. Key Contributions: First inventor on a molecule ranking patent (2021), co-developer of the CovidX algorithm for drug repurposing, and supervisor of PhD students/postdoctoral fellows. Collaborates with Sano teams to advance clinical research through AI. Awards: FastCompany Most Creative (2016) Industry Impact: Contributed to a multi-million dollar grant for a recommendation engine startup. Labs/Teams: Currently part of Sano's research teams, focusing on computational clinical research and interdisciplinary collaborations.
John Sandell is an Associate Professor in the Department of Chemical Engineering at Michigan Technological University. His work focuses on fire protection, environmental engineering, and innovative teaching methods. He holds a PhD from Michigan Technological University. Education: PhD, Chemical Engineering, Michigan Technological University Research Interests: Fire suppression systems in chemical industries, advanced fire protection techniques, materials microscopy (electron beam analysis), and pedagogical strategies for engineering education. His fire safety research addresses modern manufacturing materials and process safety, while his educational work explores multimedia teaching tools and student behavior analysis. Publications Trends: His articles span environmental engineering (e.g., lead-bearing fly ash characterization) and educational topics (e.g., chemical engineering technician profiles). Key themes include material analysis, pollution control, and curriculum development. Awards/Grants: No awards or grants explicitly listed in the provided text. Advising & Labs: No student advisees or lab affiliations explicitly mentioned.
Keerthana Jaganathan is a researcher at Northumbria University, specializing in the application of machine learning to toxicology and health risk assessment. Her work bridges computational biology, artificial intelligence, and chemical safety analysis. Her research focuses on developing explainable AI models for toxicity prediction, including applications in respiratory, liver, and mitochondrial toxicity. She has published extensively on multimodal fusion approaches, feature selection techniques, and hybrid molecular representations in predictive toxicology. Recent publications highlight her expertise in deep learning for dermal toxicity assessment, fuzzy mutual information for multi-label classification, and comparative studies of tree-based ensemble models in pulmonary toxicity prediction. While specific departmental affiliations are not detailed in the provided texts, her work aligns with interdisciplinary research initiatives at Northumbria.
Stefan Esders is Professor of Late Antique and Early Medieval History at Freie Universität Berlin's Friedrich Meinecke Institute, where he has held a full professorship since 2006. Previously, he served as University Lecturer in Ancient and Medieval History at the University of Bochum (2000-2006) and Assistant Professor of Medieval History there (1995-2000). His academic journey began with studies in History and Classics at Heidelberg, Freiburg, and Oxford, culminating in a state exam in 1990 and a doctoral dissertation in 1993 with summa cum laude. His educational background includes: 1982-1990: History and Classics (Latin) at Heidelberg, Freiburg, and Oxford 1990: State exam 1991-1993: Doctoral Fellow in Ancient History, University of Freiburg 1993: Dissertation 'Römische Rechtstradition und merowingisches Königtum' (summa cum laude) 1993-1994: Postdoctoral Fellow, Max-Planck-Institute for History, Göttingen 1994-1995: Postdoctoral Fellow, University of Münster 2004: Habilitation in Medieval History and Auxiliary Sciences, University of Bochum Esders' research focuses on the transformations of late Roman culture across Visigothic Spain, Lombard Italy, and Merovingian Gaul, with particular emphasis on legal history, Mediterranean communication (400-900 CE), and the history of oaths in antiquity and the Middle Ages. His work bridges institutional, social, and cultural history, examining how legal texts and practices shaped political legitimacy and social structures during the transition from antiquity to the early Middle Ages. He has made significant contributions to understanding the reception of Roman law in post-Roman kingdoms and the development of early medieval legal pluralism. His recent publications reveal a consistent focus on legal texts, oath practices, and political legitimacy across the early medieval Mediterranean world. Esders demonstrates how legal traditions were adapted and transformed as Roman imperial structures gave way to regional kingdoms, with particular attention to the interplay between ethnic identity, religious affiliation, and legal practice. His work increasingly employs comparative approaches, examining parallel developments across different regions of the former Roman Empire to reveal broader patterns of continuity and change. His scholarly recognition includes: Corresponding Member, Monumenta Germaniae Historica (2019-present) Fellow, Humanities Council and Program in Medieval Studies, Princeton University (2019) Member, Institute for Advanced Study, Princeton (2013) Ordentliches Mitglied der Academia Europaea (since 2021) Distinguished Fellow of the Hebrew University of Jerusalem (2025/26) Corresponding Fellow of the Medieval Academy of America (since 2025) As an active scholar, Esders serves on editorial boards including Speculum. A Journal of Medieval Studies and has edited numerous volumes on early medieval legal history. He has been instrumental in collaborative research projects examining Mediterranean connectivity in the early Middle Ages and has supervised numerous doctoral students. Currently, he serves as speaker of the doctoral program 'Ancient Histories, Languages and Texts' within the Berlin Graduate School of Ancient Studies. His work is characterized by meticulous textual analysis combined with broader theoretical frameworks examining political legitimacy, legal pluralism, and the transformation of social structures during the crucial period between the 5th and 10th centuries CE. Esders maintains active international collaborations, particularly with scholars in Mediterranean countries, reflecting his focus on cross-regional connections during the early medieval period.
Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.
Prof. Chao Dong ZHU is a leading researcher in ecology and biodiversity conservation, affiliated with the Chinese Academy of Sciences. He serves as Principal Investigator for multiple projects including MultiTroph (2022-2026), analyzing biodiversity mechanisms across trophic levels. His work focuses on plant-insect interactions, phylogenetic signals in ecological communities, and the impacts of tree diversity on herbivore-parasitoid networks. Key projects include SP09c1 Phylogenetic signals in plant-insect interactions and P4C: Associational effects mediated by parasitoids , examining how tree diversity influences herbivore communities and parasitoid dynamics. He has contributed to large-scale biodiversity experiments in subtropical forests, such as BEF-China, investigating species coexistence and turnover patterns. Education: Not explicitly stated in provided texts Research Themes: Trophic interactions, biodiversity gradients, DNA barcoding applications, spatial ecology Publications emphasize data-driven analyses of herbivore community structure, leveraging phylogenetic and functional trait approaches. His work bridges observational ecology with experimental design, contributing to understanding ecosystem resilience under biodiversity loss scenarios.
