جست‌وجوی استاد و پژوهشگر

Toine Bogersمشاهده پروفایل

دانشیار

• Recommender Systems
• Information Retrieval
• Data Science
• +۳ مورد دیگر

Toine Bogers is an Associate Professor at the IT University of Copenhagen within the department of Data Science Networks, Data, and Society. His research focuses on recommender systems, information retrieval, and human resources technology. Key areas include multistakeholder evaluation frameworks, algorithmic fairness in recruitment, and social media-driven recommendation communities. Research Projects FAIRMATCH : Investigates fairness in job recommendation systems funded by Innovation Fund Denmark (2024–2027). Pioneer Centre for Artificial Intelligence : Co-Investigator in a national initiative exploring AI ethics and applications (2021–2034). Key Research Themes Bogers explores how AI impacts human decision-making in domains like hiring, cultural heritage preservation, and casual leisure search. His work emphasizes multistakeholder evaluation methods to address ethical challenges in algorithmic systems. Recent studies analyze human recommendation communities on Reddit and the impact of large language models on known-item retrieval. Collaborations & Datasets Active collaborations include CHIIR (Conference on Human Information Interaction and Retrieval) and CLEF (Cross-Language Evaluation Forum). He has contributed datasets on data storytelling effects, video game re-finding behaviors, and social book search interactions, emphasizing reproducibility in IR research. Professional Contributions Organizes workshops such as RecSys in HR (Recommender Systems for Human Resources) and chairs the CHIIR impact assessment initiative. His work bridges academic research with practical applications in HR tech and AI governance.

Sascha Hunoldمشاهده پروفایل

دانشیار

• Parallel Computing
• High-Performance Computing (HPC)
• MPI Collective Communication
• +۴ مورد دیگر

Sascha Hunold is an Associate Professor at TU Wien, affiliated with the Department of Parallel Computing within the Faculty of Informatics. He holds roles as Vice Dean of Academic Affairs for Informatics Bachelor programs and Curriculum Coordinator for the Master's program in High-Performance Computing. His research focuses on parallel computing, MPI optimization, scheduling algorithms, and reproducible HPC experiments. Education: Habilitation (venia docendi) in Computer Science from TU Wien, PhD in Computer Science from the University of Bayreuth, and MSc in Computer Science from Martin Luther University Halle-Wittenberg. Research interests include MPI collective communication performance, HPC benchmarking, algorithm selection, and task scheduling. He has contributed to tools like ReproMPI and Scheduling.jl. Key awards include Best Paper awards at IEEE CLUSTER 2020 and EuroMPI/Asia 2014, and recognition for reproducible research methodologies. His work emphasizes practical applications of parallel computing in large-scale systems. Teaching responsibilities include courses on parallel algorithms, scientific programming with Python, and HPC project supervision. Active in program committees for major conferences like IPDPS and SC.

• Parallel Algorithms
• Parallel Computing
• High-Performance Computing (HPC)
• +۴ مورد دیگر

Prof. Jesper Larsson Träff is a Full Professor and Head of the Research Unit in Parallel Computing at Technische Universität Wien (TU Wien). His academic role is centered within the Department of Computer Engineering. He holds an MSc and PhD, and has contributed extensively to the field of parallel computing through his research and leadership in international projects. His research focuses on parallel algorithms, scheduling, and optimization of the Message Passing Interface (MPI), with emphasis on high-performance computing (HPC) systems and distributed architectures. Key projects include the Process Mapping initiative (2019–2024), Autotune (2021–2025), and contributions to Exascale Programming Models. He has also led efforts in evaluating MPI performance tools and their reproducibility challenges. Research Areas: Parallel Algorithms, MPI Optimization, HPC, Process Mapping, Collective Communication, and Memory Models. Notable Achievements: Awarded the Best Paper at EuroMPI 2014 and recognized by the Innovation Radar for his work on PGAS-based MPI interoperability in 2018. Teaching: Teaches courses such as Advanced Multiprocessor Programming, Bachelor/Master Thesis supervision, and seminars in Computer Engineering and Theoretical Computer Science. Prof. Träff’s advising includes students researching topics like lock-free data structures, MPI datatype optimization, and task scheduling. His grants span Austrian and EU funding bodies, addressing challenges in exascale computing and reproducible experimental research. He is affiliated with the Vienna Mapping and Sparse Quadratic Assignment (Vienna Mapping) project and actively contributes to international workshops and conferences.

• Epidemiology
• Mathematical Biology
• Infectious Disease Modeling
• +۶ مورد دیگر

Roslyn I. Hickson is a Researcher at James Cook University, specializing in mathematical biology and epidemiology. Her work bridges computational methods with public health challenges, focusing on infectious diseases like malaria, dengue, and tuberculosis. Key collaborations with institutions such as the University of Melbourne, Burnet Institute, and Australian National University. Active in interdisciplinary research, including One Health and behavioral disease transmission models. Roslyn's research centers on modeling disease dynamics, integrating factors like population heterogeneity, stigma, and environmental variables. Her studies address zoonotic spillover risks, optimal intervention strategies, and reproducibility in epidemic modeling. Recent publications highlight trends in computational epidemiology, particularly for diseases with complex transmission cycles (e.g., P. vivax malaria, Japanese Encephalitis) and societal impacts (e.g., stigma-driven mental health trends). She employs machine learning and spatial modeling for pathogen prediction. Her contributions include frameworks for health worker allocation, tuberculosis control cost-effectiveness, and Wolbachia's role in dengue suppression, reflecting a broad application of mathematical models to global health security.

• Clinical Microbiology
• Infectious Diseases
• Rapid Diagnostic Testing
• +۳ مورد دیگر

David Peaper is an Associate Professor of Laboratory Medicine at Yale School of Medicine, with dual roles as Director of the Clinical Microbiology Laboratory at Yale-New Haven Hospital and Director of the Virology Reference Laboratory at the West Haven VA Hospital. He completed his MD and PhD at Yale (2008 and 2007), followed by Clinical Pathology residency and Medical Microbiology fellowship at Yale-New Haven Hospital. Yale School of Medicine - Department of Laboratory Medicine Director, Clinical Microbiology Laboratory (YNHH) Director, Medical Microbiology Fellowship Program Director, Virology Reference Laboratory (VA Connecticut) Dr. Peaper’s research focuses on integrating basic and clinical sciences to advance pathogenesis understanding and improve infectious disease diagnostics. His work emphasizes rapid respiratory virus testing , Clostridioides difficile testing optimization, and antibiotic stewardship . Recent publications highlight applications of artificial intelligence in clinical microbiology and pandemic diagnostic capacity challenges. Co-authored 12+ peer-reviewed studies (2023-2025) Key collaborations with Marie-Louise Landry, Marwan Azar, Richard Martinello Active in clinical decision support systems for laboratory testing Contributions to Lyme disease diagnostics and fungal contamination studies

Brian Ballsun-Stantonمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Generative AI
• Natural Language Processing
• +۴ مورد دیگر

Dr Brian Ballsun-Stanton is a Solutions Architect (Digital Humanities) at Macquarie University's Faculty of Arts. He specializes in AI integration in higher education, leading initiatives such as the university's 'Guidance Note: Using Generative AI in Research' and winning the 2024 Faculty of Arts Educational Leadership Award. His work spans AI policy, pedagogy, and interdisciplinary applications across languages, security studies, and law. With over 15 years' experience as a data scientist, he has pioneered open-source tools like FAIMS Mobile for field research and led AUD$3.5M+ in grants focused on big data analysis of violent extremism and archaeological projects. Education: PhD in Philosophy of Data (not explicitly stated, inferred from biography). Research Interests: Generative AI ethics, digital humanities, social network analysis, and the intersection of technology with humanities scholarship. He focuses on AI-enhanced learning, critical evaluation of large language models, and FAIR data principles in epigraphy and archaeology. Articles Trends: Recent work emphasizes AI policy frameworks, generative AI applications in education, and computational methods in archaeology. Earlier publications explore far-right online ecosystems and social media analysis. Awards: 2018 DataApp Prize (environmental data transparency), 2024 Educational Leadership Award. Grants/Projects: Led projects on violent extremism (AUD$3.5M+), FAIMS Mobile development, and Roman Dalmatia military communities. Technical Director of FAIMS Project since 2013. Labs/Teams: Technical lead for the FAIMS Project, collaborating internationally on archaeological digital tools and open-source field data systems.

• Graphical Models
• Bayesian Nonparametrics
• Bayesian Variable Selection
• +۳ مورد دیگر

Yabo Niu is an Assistant Professor and Presidential Frontier Faculty in the Department of Mathematics at the University of Houston, with a joint appointment in the Department of Health Systems & Population Health Sciences within the Tilman J. Fertitta Family College of Medicine. They hold a Ph.D. in Statistics from Texas A&M University (2019) and a B.S. in Statistics from Nankai University, China (2013). Their research focuses on Bayesian statistical methods, including graphical models, nonparametric approaches, variable selection, and tree-based regression/classification techniques. Recent contributions include the 2024 JASA Reproducibility Award-winning paper on covariate-assisted Bayesian graph learning for heterogeneous data. Dr. Niu has developed novel methodologies in network modeling and hybrid estimation techniques (e.g., EPSOM-Hyb). Their work bridges statistical theory with applications in health systems, neuroscience, and genomics. In 2024, they introduced a new Bayesian Statistics course (MATH 6397) at the University of Houston. Education: Ph.D. in Statistics, Texas A&M University (2014–2019) B.S. in Statistics, Nankai University (2009–2013) Research Highlights: Developed robust high-dimensional network modeling frameworks Advanced Bayesian approaches for heterogeneous data integration Investigated astrocyte structural plasticity using machine learning Teaching: Bayesian Statistics course (Spring 2024) Current research emphasizes integrating omics data and advancing reproducible statistical practices. Dr. Niu’s group includes postdoctoral researchers like Ji Shi (jointly supervised with Demetrio Labate and Peng Zhao).

Danny Bøgsted Poulsenمشاهده پروفایل

دانشیار

• Formal Methods
• Model Checking
• Cyber-Physical Systems
• +۳ مورد دیگر

Danny Bøgsted Poulsen is an Associate Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on formal methods, model checking, and cyber-physical systems with applications in security analysis and programming languages. He contributes to projects like BEO-COVID (2020–2020) and IDEA4CPS (2011–2015), which explore decision support tools and foundational cyber-physical systems. His academic background includes advanced work in formal verification and statistical model checking. Key research interests include: Formal methods for string constraints and SMT solvers Statistical analysis of security-critical systems Modelling protocols like DTLS and attack-defense scenarios Applications of formal methods in education and public health Recent work highlights include developing SMTQuery for benchmark analysis, statistical evaluation of bit-flip vulnerabilities, and leveraging large language models for educational feedback. His research outputs span over 36 publications across journals and conferences, with active contributions to UPPAAL tool development and open datasets for reproducibility. Poulsen collaborates internationally on projects involving formal verification of embedded systems and cybersecurity protocols. His work bridges theoretical computer science with practical applications in safety-critical systems.

• Cybersecurity
• Healthcare IT Safety
• User Interface Design
• +۳ مورد دیگر

Professor Harold Thimbleby is an Emeritus Professor in the Department of Computer Science at Swansea University, within the Faculty of Science and Engineering. He specializes in cybersecurity, healthcare IT safety, user interface design, and medical device software. His research emphasizes improving the reliability of digital systems in critical settings like healthcare, focusing on reducing errors caused by poor design and addressing the legal and ethical challenges arising from IT failures. Key research interests include: Cybersecurity vulnerabilities in hospitals and their legal implications Designing safer user interfaces for medical devices and healthcare systems Reproducibility in computational science and algorithmic transparency Ethical and safety standards in healthcare IT procurement and deployment Recent work highlights include a 2024 paper in The Computer Journal on improving science through code reliability, and a 2024 legal analysis of digital evidence in court cases. His publications span over two decades, addressing topics from historical cryptography to modern digital healthcare challenges. Prof. Thimbleby is actively engaged in postgraduate supervision and contributes to interdisciplinary initiatives to enhance the safety and efficacy of technology in healthcare.

• Bilingualism
• Emotion
• Cognitive Development
• +۷ مورد دیگر

Andree HARTANTO is an Associate Professor of Psychology (Education) at Singapore Management University's School of Social Sciences. His research focuses on bilingualism, emotion regulation, cognitive development and aging, technology and social media impacts, and healthy aging. He holds a PhD (2018), MSc (2016) from SMU, and a BS from James Cook University (2013). He advises/co-advises students including Quek Yi Xuan, Jonathan Louis Chia Jie Sheng, and others. Courses taught include Introduction to Psychology, Cognitive Psychology, and Psychology Research Methods. His work explores how technology (e.g., AI companions, social media) affects emotional well-being, cognitive functions, and interpersonal dynamics. Recent studies investigate AI ethics, smartphone overuse, and cross-cultural emotional responses. Research highlights include examining stress moderation via mindfulness, the role of dispositional religiosity in mixed emotions, and interventions targeting digital addiction. He actively contributes to open science initiatives and registered replication projects.

• Data Science
• Machine Learning
• Tensor Factorization
• +۵ مورد دیگر

Dr Thiru Balasubramaniam is a Research Fellow at Queensland University of Technology (QUT), working within the Faculty of Science, School of Computer Science. His expertise lies at the intersection of data science, machine learning, and real-world applications, with a specific focus on tensor factorization methods for managing multifaceted data from IoT and Web 3.0 applications. His educational background includes a PhD from Queensland University of Technology and a Bachelor of Engineering from Anna University. Prior to his doctoral studies, he worked as a Research Assistant at the Singapore University of Technology and Design - Massachusetts Institute of Technology (SUTD-MIT) International Design Centre, where he analyzed mobility data to personalize city environments for elderly citizens in Singapore. Dr Balasubramaniam's research interests span multiple areas of data science: Tensor and Matrix Factorization methods Pattern Mining and Text Mining applications Recommender Systems development IoT data processing Web 3.0 applications Real-time analytics for multifaceted data His publication record demonstrates consistent contributions to high-impact venues including IEEE TKDE, ACM TKDD, WWW, WISE, AusDM, and PRICAI. The trend in his recent work shows increasing application of tensor factorization techniques to diverse real-world problems including environmental monitoring, pandemic modeling, social media analysis, and smart grid technology. His research often involves interdisciplinary collaborations, particularly with Professor Richi Nayak at QUT. Scientific recognition includes: QUT-CDS first byte research funding worth 30,000 AUD Dr Balasubramaniam has been actively involved in teaching data analytics subjects at QUT since 2017, including Data Exploration and Mining, Data and Web Analytics, Data Mining Technology and Applications, and Web Computing. His teaching spans both undergraduate and postgraduate levels. His research has been supported through various collaborative grants and institutional funding mechanisms at QUT.

• Exploratory Data Analysis
• Dimension Reduction
• Cluster Analysis
• +۷ مورد دیگر

Michel van de Velden is an Associate Professor of Statistics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. His work bridges statistical methodology and data science, with a focus on exploratory techniques and machine learning. His research interests lie primarily in exploratory data analysis , with a focus on dimension reduction , cluster analysis , and data visualization . He also actively contributes to supervised machine learning , particularly using tree-based methods such as random forests. His methodological work often addresses challenges in categorical data and mixed-type variables . The recent articles highlight a strong trend in developing exact and unbiased statistical methods for clustering and distance computation. His work spans correspondence analysis , hierarchical clustering algorithms , and software tools for mixed data, reflecting a blend of theoretical rigor and practical implementation. He has served on the editorial boards of Computational Statistics and Statistical Papers , contributing to academic peer review and publication quality. Michel van de Velden has supervised academic work and contributed to open datasets and software, indicating active mentorship and collaboration. His research is supported by ongoing publications and editorial activities, suggesting sustained engagement in the academic community. He is involved in developing software such as manystat and datasets related to categorical data visualization, indicating leadership in reproducible and open research practices.

Miguel L. Pardalمشاهده پروفایل

استادیار

• Distributed Systems
• Cybersecurity
• Internet of Things
• +۲ مورد دیگر

Miguel L. Pardal is an Assistant Professor at Instituto Superior Técnico, Universidade de Lisboa, and a researcher at INESC-ID's Distributed Systems Group (GSD). His work focuses on Cybersecurity, Distributed Systems, Internet of Things (IoT), and Cloud Computing. He has led projects like the EU-funded Safe Cloud initiative and contributed to intrusion recovery systems (e.g., MIRES, μVerum) and blockchain-based solutions (e.g., ChainGuard, EvoChain). His research addresses challenges in secure communication, resilient distributed architectures, and location-based systems. Since 2002, he has taught courses on Network Security, Distributed Systems, and Operating Systems. His projects often intersect academia and industry, emphasizing practical applications in critical infrastructure and smart technologies. Collaborations include developing systems for vehicle-pedestrian safety (SafeWalk) and decentralized identity management. He has authored over 30 publications, with recent work covering blockchain resilience, intrusion detection in industrial processes (IM-DISCO), and generative AI for distributed algorithms. His contributions span academic conferences (DSN, EuroSys) and journals (IEEE Transactions).

Carsten Q. Schneiderمشاهده پروفایل

استاد

• Political Regime Change
• Democratization
• Comparative Politics
• +۷ مورد دیگر

Carsten Q. Schneider is a Professor in the Department of Political Science and the Doctoral School of Political Science, Public Policy, and International Relations at Central European University (CEU). He has been a key academic and administrative leader at CEU since 2004, serving as department head (2014–2017), program director for the MA in Political Science (2021–2022), and currently as Pro-Rector for External Relations since 2022, overseeing academic partnerships, communications, outreach, and alumni relations. PhD in Political and Social Science, European University Institute Diploma in Political Science, Free University, Berlin His research and teaching focus on political regime change, democratization in Europe and Latin America, and comparative methodology—especially qualitative comparative analysis (QCA) and set-theoretic methods. He is the author of multiple leading books on QCA published by Cambridge University Press and has published extensively in top journals such as Comparative Political Studies , Political Analysis , and Democratization . His recent publications demonstrate a strong trend toward integrating computational methods—particularly machine learning and automated text analysis—with traditional comparative frameworks. His 2025 article on illiberal leaders uses 38,000+ speeches across 120 countries to show how right-wing strongmen exacerbate inequality. This reflects a broader interdisciplinary shift in his work, combining political theory, methodological innovation, and large-scale data analysis. David Collier Mid-Career Achievement Award, American Political Science Association (2019) CEU Distinguished Teaching Award (2019) Elected Member, German Academy of Young Scientists (2009–2014) As Pro-Rector for External Relations, Schneider leads CEU’s engagement with academic networks, including CIVICA: The European University of Social Sciences, where he chairs the Permanent Design Team. He represents CEU in the Austrian Private Universities Conference (ÖPUK) and serves on internal governance bodies such as the Senate Committee on Strategic Development. He has advised on research transparency standards and promotes open science in qualitative and multimethod research. He has conducted research stays at Harvard University, UC Berkeley, WZB Berlin, and Pompeu Fabra, reflecting his strong international academic network.

Leona Chandra Kruseمشاهده پروفایل

استاد

• Information Systems
• Human-Computer Interaction
• Digital Innovation
• +۶ مورد دیگر

Leona Chandra Kruse is a Professor at the Department of Information Systems, University of Agder. Her research explores the intersection of technology and human experience in the digital age, focusing on designing systems for support, enjoyment, and security. Research areas: Human-Computer Interaction, Digital Transformation, Design Science Research Editorial roles: Senior Editor (European Journal of Information Systems), Special Issue Editor (Decision Support Systems) Conference leadership: Program Chair for WI 2025, Track Chair for ICIS 2025 Her work examines both legacy and emerging technologies including decision support systems, digital companions, non-fungible tokens (NFTs), and immersive environments. She investigates innovative applications such as virtual wine tasting and digital offering design for hybrid experiences. Recent research trends include: Temporal awareness in hybrid work environments Token economy applications in creative industries AI ethics and human-AI collaboration Phygital experience design Crisis informatics during VUCA situations Scientific recognition includes: AVA Research Award for Young Researchers (2024) CHIRA Best Paper Honorable Mention (2024) European Journal of Information Systems Article of the Year (2018, 2024) SIGBIT Best Paper on Web3 (2023) Academic service includes: Executive Committee, AIS Special Interest Group in Pragmatism Doctoral Consortium Chair, DESRIST 2024 Program Chair, DESRIST 2021 Special Issue Editor for top journals