Roshanak Nateghi is an Associate Professor in the College of Engineering at Purdue University, specializing in Industrial and Environmental Ecology Engineering. Her research focuses on climate change resilience, infrastructure systems, and data-driven modeling of urban energy-water interactions. Climate Change Adaptation Infrastructure Resilience Urban Systems Analysis Machine Learning Applications Her recent work explores post-disaster urban recovery, cooling demand optimization in heatwaves, and climate-induced shifts in energy-water nexus dynamics. She employs interdisciplinary methods combining statistical learning and physics-based models. Scientific awards and recognitions are not explicitly listed in the provided text, but her leadership in critical infrastructure resilience research is evident through numerous publications and grants. She serves as an academic advisor and collaborates with interdisciplinary teams on climate risk analytics.
William Alves is an Associate Professor of Music in the Department of Humanities, Social Sciences, and the Arts (HSA) at Harvey Mudd College in Claremont, California. He is a composer, video artist, and scholar with deep expertise in ethnomusicology, particularly Indonesian gamelan, computer music, visual music, and alternate tuning systems. Alves co-directs MicroFest, Southern California’s annual festival of microtonal music, and directs the American Gamelan and Electronic Music ensembles at the Claremont Colleges. Associate Professor of Music, Harvey Mudd College Department of Humanities, Social Sciences, and the Arts (HSA) Director, American Gamelan Ensemble Director, Electronic Music Ensemble Co-Director, MicroFest Festival of Microtonal Music His research and creative work explore the intersections of music, technology, and global cultural traditions. He is particularly known for his work in world music pedagogy, having authored the widely adopted textbook Music of the Peoples of the World , now in its third edition, and for his biography of composer Lou Harrison. His compositions span gamelan, electronic music, and multimedia works, often blending Western and non-Western traditions. Alves’s publications and creative output reflect a strong interdisciplinary focus, with articles in journals such as Perspectives of New Music , Computer Music Journal , and SEAMUS Journal . His recent works explore microtonality, electroacoustic composition, visual music, and cross-cultural musical synthesis. The themes across his articles and compositions include global musical traditions, technological innovation in sound, and the blending of visual and auditory art forms. His scholarly and artistic contributions have been recognized through a Senior Fulbright Scholarship in Indonesia (1993–1994), where he studied and taught traditional music. He has also been active in performance, participating in Javanese and Balinese gamelan ensembles and West African drumming groups. Senior Fulbright Scholar, Indonesia (1993–1994) Co-author, Biography of Lou Harrison Author, Music of the Peoples of the World (3rd ed.) Published recordings: The Terrain of Possibilities , Imbal-Imbalan , Mystic Canyon , Guitars and Gamelan Video works: Celestial Dance (published by Kinetica Video Library) Alves has advised and mentored students through ensemble direction and coursework, though specific names of advisees are not listed. He has taught a wide range of courses including Music of the Peoples of the World , Electronic Music , Film Music , and Music Since 1900 . He has also contributed to academic discourse through publications and festival leadership. There is no mention of formal research grants, but his Fulbright award indicates significant recognition and funding support in the past. He is affiliated with the Society for Ethnomusicology and has led or participated in various musical ensembles and festivals, contributing to a vibrant interdisciplinary arts community at the Claremont Colleges. His work continues to bridge academic scholarship with artistic practice, fostering innovative approaches to music and culture.
Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.
Aleksey Polunchenko is an Associate Professor in the Department of Mathematics and Statistics at Binghamton University . His research focuses on mathematical statistics , particularly sequential change-point detection with applications in financial surveillance, anomaly detection, and statistical process control. He has made significant contributions to the analysis of the Shiryaev-Roberts procedure and related methods, including their asymptotic properties, robustness, and performance evaluation. Education : PhD, University of Southern California His recent publications explore the quasi-stationary distributions , first exit times , and asymptotic optimality of change-point detection algorithms, with applications in real-time financial monitoring and cybersecurity. While no scientific awards are listed, his work has been cited in multi-sensor systems and distributed detection frameworks. Email : aleksey@binghamton.edu
Lisbet Tarp is an Associate Professor in Art History at the School of Communication and Culture, Aarhus University. Her academic work bridges traditional art historical scholarship with digital methodologies and interdisciplinary research, particularly in the fields of painting, materiality, and conservation. She is actively engaged in several high-impact research projects exploring the intersections of art, science, and technology. Research Interests: Digital Art History and computational analysis of paintings Materiality and technique in historical and contemporary painting Conservation science and hidden layers in artworks Mathematics and geometry in visual art Early modern court culture and ceremonial representation Interdisciplinary practices between art and anatomy Her recent publications reflect a strong trend toward integrating digital tools into art historical inquiry, with a focus on uncovering the material and technical dimensions of paintings. Projects such as Digital Art History: Rediscovering the Painting and ANAT: Anatomical Theater demonstrate her innovative approach to visual culture through scientific and digital lenses. Her work often involves collaborative, peer-reviewed publications and digital dissemination. Scientific Projects & Activities: ANAT: Anatomical Theater (2023–2029) – Investigating dissection as aesthetic practice in early modern and contemporary contexts Digital Art History: Rediscovering the Painting (2019–2022) – Using digital methods to analyze painting techniques and material composition MoCMa: Mobility Creates Masters (2017–2019) – Studying transnational influences in European art LUMEN Center (2015–2025) – Researching Lutheran theology and its impact on confessional societies and visual culture Lisbet Tarp has contributed extensively to academic discourse through peer-reviewed journals, anthologies, and digital publications. While no formal students or awards are listed, her leadership in major research initiatives underscores her scholarly influence. She employs digital platforms for both research and pedagogy, including student-organized seminars and open-access digital versions of her work.
Alessandro Bevilacqua is an Assistant Professor at the Department of Computer Science and Engineering, University of Bologna. His research focuses on computer vision, medical imaging, and artificial intelligence in healthcare. He leads the Computer Vision Group, which develops advanced algorithms for tumor characterization, radiomics, and automated analysis of pathological images. His work integrates machine learning, quantitative imaging, and clinical applications to improve diagnostic accuracy in oncology. Bevilacqua’s research spans areas such as diffusion-weighted MRI analysis, multiplex immunohistochemistry quantification, and radiomic feature extraction. He collaborates with clinical teams to translate computational methods into practical diagnostic tools. His recent projects include developing AI models for prostate cancer detection, colorectal lesion classification, and predicting treatment responses using imaging biomarkers. Key technical contributions include novel metrics for tumor-peritumour interface analysis, automated workflows for whole-slide imaging, and reproducibility frameworks for radiomic studies. His methodologies address challenges in heterogeneity assessment, clinical significance prediction, and imaging protocol optimization. Academic activities include teaching computer science and engineering courses, mentoring students in AI-driven healthcare projects, and advising on collaborative research initiatives. He maintains an active presence in interdisciplinary research, bridging computational methods with clinical oncology, radiology, and molecular biology.
Prof. Dr.techn. Bernhard Hametner is a Lecturer at the Institute of Biomedical Engineering (E363) within Technische Universität Wien (TU Wien) . His research focuses on arterial pressure dynamics, cardiovascular physiology, and biomedical signal analysis with applications in clinical diagnostics and space medicine. He leads projects involving wearable medical devices, multisensor monitoring systems, and computational models of vascular systems. Key affiliations: TU Wien's Network Lab and collaborative EU projects like VascAgeNet Expertise in pulse wave analysis, vascular aging, and translational biomedical engineering Research Interests: His work spans arterial stiffness quantification, non-invasive cardiac output estimation, and developing methods to detect early cardiovascular dysfunction through waveform analysis. He has pioneered approaches using difference equations for modeling arterial wave reflections and contributed to understanding microgravity's impact on cardiovascular systems. Publications Highlight Trends: Recent work emphasizes clinical applications of wearable devices (2023), AI-driven medical recommendation systems (2022), and space physiology studies (2020-2022). Earlier research focused on computational modeling of vascular dynamics and validation of novel diagnostic methods. Advising & Education: Supervised 8 thesis students (2016-2021) in topics like biomedical signal analysis, machine learning in healthcare, and cardiovascular modeling. Active in training the next generation of biomedical engineers through TU Wien's graduate programs. Labs/Teams: Part of TU Wien's Network Lab, collaborating with international teams on projects like the EU's VascAgeNet initiative. Engaged in multidisciplinary teams combining engineering, medicine, and data science.
Maris Ozols is an Assistant Professor at the University of Amsterdam and a researcher at QuSoft, affiliated with the Algorithms and Complexity department at Centrum Wiskunde & Informatica (CWI). His primary research focuses on quantum algorithms and quantum information theory, with significant contributions to quantum complexity, quantum cryptography, and quantum state discrimination. His research interests span quantum algorithms, quantum information theory, quantum cryptography, quantum complexity, and theoretical computer science. Ozols has developed fundamental techniques in quantum query complexity, quantum state discrimination, and quantum cryptographic security models. His work often bridges theoretical computer science with quantum information physics, demonstrating practical implications for quantum computing architectures. His publication record shows consistent output in top venues including Communications in Mathematical Physics, Leibniz International Proceedings in Informatics, and Quantum journal. Recent work (2022-2025) focuses on quantum state discrimination, quantum circuit optimization, quantum machine learning, and cryptographic applications of quantum algorithms. His research demonstrates strong theoretical foundations with practical implications for quantum computing development. Leverhulme Early Career Fellow (University of Cambridge) Ozols has secured research funding through multiple Netherlands Organisation for Scientific Research (NWO) grants including the Quantum Software Consortium (QSC) and Quantum Computation with Bounded Space projects. His collaborative work spans international institutions including the University of Waterloo (where he earned his PhD), University of Cambridge, IBM Research, and various European quantum computing groups. He maintains active research groups in quantum algorithms at both QuSoft and CWI, with recent focus on quantum machine learning applications and quantum cryptographic protocols.
Dr. Clifton van der Linden is an Associate Professor of Political Science at McMaster University, where he serves as Director of the Digital Society Lab and Academic Director of the Master of Public Policy in Digital Society program. He is also a Visiting Fellow at the Oxford Internet Institute, exploring the interplay between digital technologies and democratic processes. PhD in Political Science (University of Toronto, 2019) MA in Journalism (Western University, 2005) Bachelor of Arts in Economics and Political Science (McMaster University, 2004) His research centers on how digital technologies like artificial intelligence reshape democratic participation, political behavior, and public opinion. He specializes in voting advice applications (e.g., Vox Pop Labs ), electoral politics, and the ethical implications of data-driven governance. Dr. van der Linden’s scholarly output includes 15 recent articles spanning public health policy, political methodology, and transnational integration. His work has been featured in journals like Philosophy & Technology and European Union Politics , with themes ranging from pandemic behavioral analysis to Brexit trade-offs. Adel S. Sedra Distinguished Graduate Award (University of Toronto) Clarkson Laureateship for Public Service (Massey College) Arch Alumni Award (McMaster University) Toronto Region Board of Trade's Entrepreneur of the Year As a serial entrepreneur, Dr. van der Linden has founded multiple tech ventures, including Vox Pop Labs , creator of Vote Compass —a tool used in over 50 elections worldwide. He advises governments on technology policy and frequently contributes to media discussions on elections.
Cresantus Biamba is a Senior Lecturer at the University of Gävle, specializing in Educational Science. His research bridges education theory with technological advancements, focusing on teacher training, sustainability in education, and inclusive pedagogy. Researcher at University of Gävle (Education, Educational Science) Research interests include: Education for Sustainable Development (ESD) in global contexts Teacher education reform and policy analysis Inclusive classroom practices in the Global South Technological integration in educational systems Curriculum development for post-pandemic resilience Publication trends reveal interdisciplinary work combining AI, cloud computing, and IoT applications with educational challenges, particularly in African institutions. His articles address security optimization, healthcare technology, and sustainability frameworks. Academic activities involve collaborations with researchers in cybersecurity, AI, and energy systems, though specific grants or mentoring roles are not explicitly documented here.
Dr. Sinan Tankut Gülhan is an Assistant Professor at the University of Zielona Góra's Institute of Sociology in Poland, where he applies a multidisciplinary approach to urban sociology. With expertise spanning Turkish urbanization processes, comparative urban history, and digital transformation in urban contexts, he bridges theoretical frameworks with practical applications in urban planning and policy. His research interests focus on the intersection of urban sociology and digital transformation, examining algorithmic decision-making in urban planning, digital inequality, housing market dynamics, 'smart city' initiatives, and the impact of digital platforms on urban mobility. Drawing from Henri Lefebvre's spatial theory, he analyzes how urban spaces are produced through political, economic, and social processes, with particular attention to Istanbul's historical development. Dr. Gülhan has expanded his methodological approach from qualitative to quantitative and computational techniques, utilizing statistical analysis (RStudio, SPSS), data science applications (Python, machine learning), digital research methods (web scraping, text analysis), and spatial analysis (QGIS). His publications reveal a consistent focus on urban political economy, historical urban development, and the evolving relationship between state power and urban space. Actively engaged in public sociology, he collaborates with community organizations, policymakers, and media outlets, organizing workshops for planners and advising municipal governments on technology implementation. His work on the 1960 Istanbul Housing Census visualization demonstrates his commitment to making historical urban data accessible for contemporary urban challenges.
Dhanya Sridhar is an Assistant Professor at the Department of Computer Science and Operations Research (DIRO) of the University of Montreal and a core academic member of Mila - Quebec Artificial Intelligence Institute. She holds a Canada CIFAR AI Chair and co-leads the IVADO R3AI working group on safe and aligned AI. PhD from University of California Santa Cruz Postdoctoral research at Columbia University Data Science Institute Her research focuses on integrating causality and machine learning to build AI systems that are robust to distribution shifts, capable of efficient task adaptation, and aligned with human knowledge. Recent work includes causal effects of social interactions on US election participation and causal modeling in geriatric-oncology patient outcomes. Current research themes: Causal representation learning Temporal causal inference Counterfactual modeling Causal abstraction in large models Responsible AI development Scientific awards: Canada CIFAR AI Chair Major grants: NSERC Discovery Grant (PVX20965-RGP) 2023-2029 NSERC DGECR Grant 2023-2025 Multiple MITACS Acceleration Quebec grants Advising: PhD students: Philippe Brouillard, Shruti Joshi, Mizu Nishikawa-Toomey, Tom Marty, Cristian Manta
Nicole Mitchell Gantt is a Professor of Composition & Computer Technologies at the University of Virginia , celebrated for her pioneering work in Afrofuturism , Experimental Jazz , and Intercultural Collaboration . Her career spans over two decades as a flutist, composer, and educator , blending science fiction narratives with Black cultural legacy . United States Artist Fellow (2020) Doris Duke Artist Award (2012) Herb Alpert Award in the Arts (2011) Downbeat Magazine/Critics Poll Top Flutist (2010–2022) Her research and creative practice explores: Mythological and ancestral storytelling in sound Integration of Octavia Butler’s Earthseed philosophy Human-computer musical dialogue via systems like VIVO Reimagining social structures through speculative composition Expanding the Association for the Advancement of Creative Musicians (AACM) legacy Key projects include: Mandorla Awakening II: Emerging Worlds (2017) - MCA Chicago commission EarthSeed (2020) - Octavia Butler-inspired sonic manifesto Medusae (2022) - Human-AI improvisation experiment Bamako*Chicago Sound System (2024) - Malian-American sonic fusion
Juan-Manuel Torres Moreno is an Associate Professor (Maître de Conférences HDR HC) at the University of Avignon (UAPV), where he conducts research in Natural Language Processing at the Laboratoire Informatique d'Avignon (LIA). His academic position includes the HDR (Habilitation à Diriger des Recherches), a post-doctoral qualification in France that enables supervision of PhD students. His primary research interests focus on Natural Language Processing, with particular emphasis on automatic text summarization, sentence generation, and phrase compression algorithms. His work spans both theoretical and applied aspects of NLP, incorporating machine learning techniques and artificial intelligence approaches. His research has significant applications in multilingual processing, text mining, and information extraction systems. Torres Moreno's publication record demonstrates a consistent trajectory in advancing text summarization techniques, with recent work exploring cross-lingual approaches, multimedia content processing, and deep learning applications. His research often bridges the gap between theoretical linguistic concepts and practical implementation, with publications spanning from fundamental NLP algorithms to applied systems for video summarization, speech processing, and multilingual document analysis. He actively collaborates with researchers across multiple institutions including École Polytechnique de Montréal (with 50 joint publications), Laboratoire Informatique d'Avignon (83 publications), and Universidad Nacional Autónoma de México. His work appears in reputable journals such as Computer Speech and Language, Data and Knowledge Engineering, and Pattern Recognition Letters. Within the Laboratoire Informatique d'Avignon, Torres Moreno contributes to the Language Processing research theme, working with colleagues on projects related to multilingual information access, opinion mining, and text analysis. His research group has participated in several evaluation campaigns including DEFT (Défi Fouille de Textes) challenges, focusing on information retrieval and sentiment analysis tasks.
Dr. QUAN Chen is an Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), holding this position since May 2025 after serving as Assistant Professor (2019-2025) and Research Assistant Professor at the University of Hong Kong (2012-2018). A Shenzhen high-level overseas talent, he earned his PhD from the University of Hong Kong and conducts cutting-edge research in electronic design automation. His academic credentials include: Ph.D. from The University of Hong Kong (2010) Master's degree from The University of Hong Kong (2007) Bachelor's degree from Sun Yat-Sen University (2005) Dr. Chen's research pioneers advanced EDA algorithms for large-scale analog/RF circuit simulation, post-Moore multi-physics analysis, and AI-assisted design technologies. His work addresses critical challenges in nanodevice modeling and quantum computing circuits, resulting in over 50 publications in top venues like IEEE TCAD and DAC, plus four Chinese patents. Analysis of his recent publications reveals dominant trends in exponential integrator methods for transient simulation, model order reduction techniques, and physics-informed machine learning for reliability analysis. His work bridges numerical mathematics with practical EDA applications across analog circuits, quantum hardware, and emerging memory technologies. Key recognitions include: Wu Wenjun Artificial Intelligence Science and Technology Award, Second Prize (2020) ICCAD Best Paper Award Nomination (2012) Dr. Chen actively recruits Postdoctoral Fellows, Research Assistants, and Graduate Students while leading major funded projects including NSFC key/general programs and Guangdong Provincial R&D initiatives. His industry partnerships with Huawei, Empyrean, and Guowei Group translate theoretical advances into real-world EDA solutions. He directs a specialized research group at SUSTech focused on computational methods for next-generation circuit design, fostering innovation in simulation algorithms and multi-physics analysis through academic-industry collaboration.
