جستجوی استاد راهنمای دانشگاهی

Allister Loderمشاهده پروفایل

استاد

• Mobility Policy
• Transportation Engineering
• Urban Planning
• +۳ مورد دیگر

Prof. Allister Loder is a Professor of Mobility Policy at the Technical University of Munich (TUM), affiliated with the TUM School of Social Sciences and Technology . His research focuses on mobility policy analysis, evaluation of policy measures, and urban transportation innovations. He holds a doctorate in Transportation from ETH Zurich (2019) and has held roles at Swiss Federal Railways (SBB) and TUM's Chair of Transportation Engineering and Technology. Since 2023, he leads a DFG-funded Emmy Noether Research Group. Education: Mechatronics Engineering, Hamburg University of Technology Energy Science and Technology, ETH Zurich PhD in Transportation Engineering, ETH Zurich (2019) Research emphasizes macroscopic fundamental diagrams (MFD) for urban traffic modeling, analysis of Germany's 9-Euro-Ticket and Deutschlandticket policies, and tradable mobility credit schemes. Recent work explores cycling infrastructure in metropolises and accessibility-based road pricing mechanisms. Key Awards : Recipient of the DFG Emmy Noether Research Group Fellowship (2023). Grants and Projects: Founded the Emmy Noether Research Group focused on mobility policy innovation. Active in large-scale empirical studies like the Mobilität. Leben panel tracking mobility behavior across Germany. Labs/Teams: Leads the Emmy Noether Research Group at TUM, collaborating on mobility policy design and evaluation tools.

Yea-Jen Hsuمشاهده پروفایل

دانشگاهی

• Health Services Research
• Program Evaluation
• Patient Safety
• +۷ مورد دیگر

Yea-Jen Hsu is an Associate Research Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. She is actively engaged in health services research with a focus on patient safety, quality improvement, and implementation science. Education: PhD, Johns Hopkins Bloomberg School of Public Health, 2011 MHA, National Yang-Ming University, 2003 BS, National Taiwan University, 2001 Dr. Hsu’s research centers on program evaluation and the application of implementation science to improve healthcare delivery. Her work emphasizes enhancing patient safety culture, reducing healthcare-associated infections, and developing innovative models such as integrating buprenorphine into primary care. She employs rigorous quantitative methods to assess interventions and identify success factors. Her recent publications (2024–2025) reflect a strong focus on patient engagement in pain management, hypertension disparities, infection risk modeling, and electronic health record analytics. These works span high-impact journals in medical quality, internal medicine, and infection control, demonstrating interdisciplinary collaboration and relevance to real-world healthcare systems. Scientific Awards: No awards mentioned in the provided text. Dr. Hsu collaborates extensively with national programs such as the CDC’s Prevention Epicenters and contributes to multi-level interventions aimed at systemic healthcare improvements. While no specific grants or advising roles are listed, her leadership in survey development, data evaluation, and collaborative research indicates active involvement in funded projects. She is not affiliated with a named lab or research team, but her network includes key figures in patient safety and health policy at Johns Hopkins and beyond.

Minsu Parkمشاهده پروفایل

استادیار

• Computational Social Science
• Human-centered Data Science
• Cultural Consumption
• +۹ مورد دیگر

Minsu Park is an Assistant Professor of Social Research and Public Policy at New York University Abu Dhabi (NYUAD), with affiliate status at the Center for Data Science at New York University (NYU). He holds a PhD in Information Science from Cornell University, where he was advised by Michael W. Macy and Mor Naaman. His academic work bridges computational techniques and social science theory, focusing on cultural consumption, social networks, and human-centered data science. PhD in Information Science, Cornell University His research centers on understanding how individuals form cultural preferences through social and psychological mechanisms, particularly in domains like music, food, fashion, and science. He leverages large-scale digital trace data—including social media, streaming platforms, and physiological signals from smart devices—to model behavior. His interdisciplinary approach draws from sociology, social computing, and data science, aiming to uncover both individual and global patterns in cultural dynamics. Key themes include variety-seeking behaviors, affective preferences, and the interplay between social position and taste. The 15 most recent publications reflect a strong trend toward using computational methods to explore sociocultural phenomena. Topics span affective preference rhythms in music, testing sociological theories like cultural omnivory, imputing user attributes from digital behavior, and enhancing model interpretability. These works are published in high-impact venues such as Nature Human Behaviour and ICWSM, indicating recognition in both computer and social sciences. Minsu Park is deeply committed to responsible data science, addressing issues like algorithmic bias, transparency, fairness, data privacy, and research ethics. He emphasizes mixed-methods approaches and critical reflection on data generation and usage. Published in Nature Human Behaviour Presented at ICWSM Focus on ethical and interpretable AI Advocate for reproducibility and data curation He mentors students through capstone projects in computer science and teaches courses such as Human-Centered Data Science and Textual Analysis for the Social Sciences. While specific grants are not detailed in the text, his research program suggests involvement in interdisciplinary, data-intensive projects likely supported by academic or scientific funding bodies. His technical expertise includes Python, R, machine learning frameworks (TensorFlow, Keras), and tools like Gephi and AWS. He leads or contributes to research initiatives involving smartwatch-based data collection, surname-based ethnicity matching, and global music consumption analysis, as evidenced by his public GitHub repositories. These projects highlight his commitment to open science and collaborative research.

Israat Haqueمشاهده پروفایل

دانشیار

• Software-defined Networking (SDN)
• Cyber-physical Systems (CPS)
• Internet of Things (IoT)
• +۱۲ مورد دیگر

Dr. Israat Haque is an Associate Professor in the Faculty of Computer Science at Dalhousie University, Halifax, where she leads the Programmable and Intelligent Networking (PINet) research group. She also holds an adjunct professorship in the Department of Computing Science at the University of Alberta. PhD in Computer Science, University of Alberta NSERC Postdoctoral Fellow, University of California, Riverside MSc in Computer Science, Concordia University Her research focuses on developing high-performance, secure, and dependable distributed and emerging networking systems, with key interests in Software-Defined Networking (SDN), Cyber-physical Systems (CPS), Internet of Things (IoT), 5G/6G technologies, and AI/ML applications in networking. She applies data-driven approaches to solve real-world problems in network programmability, stream processing, and edge/cloud computing. The 15 most recent publications highlight a strong trend in in-network computing, IoT security, AI-driven network reliability, and stream processing. Her work spans from theoretical surveys to practical system implementations, often leveraging programmable data planes (P4), machine learning, and hardware acceleration to address challenges in performance, security, and fairness in distributed systems. Dr. Haque has received numerous prestigious recognitions: IEEE/ACM N2Women Rising Star Award (2021) ACM FAccT Best Paper Award (2023) IEEE WICE Outstanding Mentoring Award (2025) University of Alberta Alumni Honour Award (2024) Digital Nova Scotia Thinking Forward Award (2022) Intel Fast Forward Initiative Winner (2022) President’s Research Excellence Award, Dalhousie (2021) She actively mentors PhD and MSc students and leads externally funded research projects, including a Canada First Research Excellence Fund (CFREF)-supported initiative on Securing Smart Environments. She has served on editorial boards of IEEE Transactions on Vehicular Technology and IEEE Communications Magazine, and on program committees of top conferences such as IEEE ICNP, IEEE NetSoft, and ACM SIGCOMM. Her lab, PINet, fosters innovation in networking systems and produces high-impact research with real-world applicability. Dr. Haque leads the PINet research group, which includes current PhD and MSc students working on cutting-edge topics like post-quantum cryptography, network programmability for security, and large ML model security. The group collaborates with institutions such as the University of Alberta, Laval University, and Concordia, and has strong industry ties with Intel, Meta, Amazon, and Facebook.

• Bioprocess Engineering
• Downstream Processing
• Industrial Biotechnology
• +۷ مورد دیگر

Rainer Hahn is an Associate Professor in Biochemical Engineering at the Institute of Biochemical Engineering, Department of Biotechnology and Food Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU). He also serves as Head of the Downstream Processing Unit at the BioIndustrial Pilot Plant and is a key researcher at the Austrian Center of Industrial Biotechnology (ACIB). His work is centered on bioprocess engineering with a strong focus on downstream processing and biopharmaceutical purification. University: University of Natural Resources and Life Sciences, Vienna (BOKU) School: Department of Biotechnology and Food Sciences Department: Institute of Biochemical Engineering Role: Associate Professor, Head of Downstream Processing Unit His research interests span Bioprocess Engineering , Downstream Processing , Industrial Biotechnology , Pharmaceutical Technology , and Chemical Biology . He investigates advanced purification techniques, particularly in chromatography and protein separation processes. His recent work emphasizes multicomponent adsorption, protein A affinity systems, and purification of complex biomolecules like secretory immunoglobulin A (sIgA). The trend in his recent publications reveals a strong emphasis on protein purification , chromatographic modeling , and process optimization in biopharmaceutical manufacturing. His work integrates experimental analysis with mathematical modeling to improve efficiency and predictability in downstream operations, especially in multi-component systems. Topics such as continuous chromatography , pH transients , and affinity resin development reflect his leadership in advancing industrial bioprocessing. His notable scientific awards include: HOUSKA PRIZE (Recognition Award) - 2016 Dissertation Prize of the Austrian Society for Biotechnology - 2002 Rainer Hahn has been actively involved in numerous research projects funded by FWF, national enterprises, and private foundations, focusing on biopharmaceutical purification and process development. He mentors students and contributes to academic training through lectures and supervision. He is also a dedicated reviewer for leading journals such as Journal of Chromatography A , Biotechnology and Bioengineering , and Separation and Purification Technology . His work is closely tied to industrial applications, particularly in the development of scalable and efficient biomanufacturing processes. He is associated with the BioIndustrial Pilot Plant and collaborates with ACIB, contributing to innovation in industrial biotechnology. His research group focuses on developing robust downstream strategies for next-generation biopharmaceuticals.

• Operations Research
• Supply Chain Management
• Pharmacy Administration
• +۲ مورد دیگر

Bahram Alidaee is a tenured Professor at the University of Mississippi's School of Business Administration, holding the School of Business Fellow Endowed Position. He has been affiliated with the Department of Marketing, Analytics and Professional Sales since joining Ole Miss in 1995, offering expertise in Operations, Supply Chain Management, and Pharmacy Administration. Education: B.S. in Business Administration, University of Tehran (1975) MBA in Industrial Management, University of North Texas (1980) Ph.D. in Mathematics (Operations Research concentration), University of Texas at Arlington (1988) His research focuses on applying operations research to large-scale industrial problems, with consulting experience spanning Casino Gaming, Furniture Industries, NAVY Personnel Assignment, Hospital Quality Management, and Blood Services. He has secured over $5.4 million in research grants through collaborations. Scientific Recognition: Outstanding Senior Researcher of the Year (School of Business Administration, 2×) Editorial board member for multiple journals Alidaee has directed 11 doctoral dissertations and taught operations/supply chain courses at all academic levels (undergraduate, MBA, PMBA, Ph.D.).

• Atmospheric Aerosols
• Environmental Spectrochemistry
• Air Quality Monitoring
• +۷ مورد دیگر

Satoshi Takahama is an Adjunct Professor at the Laboratory for Environmental Spectrochemistry (LESC) within the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL). He also contributes to teaching through the SSIE - Teaching unit at EPFL and serves on the PhD program committee for Civil and Environmental Engineering. His research is centered on the measurement, analysis, and modeling of atmospheric aerosols and their impacts on air quality and climate. Research Interests: Measurement and modeling of atmospheric aerosols Application of Fourier-transform infrared (FTIR) spectroscopy for aerosol characterization Functional group analysis of organic particulate matter Development of computational and chemometric tools for environmental data analysis Climate and air quality impacts of biomass burning and urban emissions His recent publications reflect a strong focus on the chemical evolution of aerosols, instrumental development (e.g., electrostatic collectors), and data-driven approaches to emission inventories and monitoring. These works span atmospheric chemistry, environmental engineering, and analytical method development. Scientific Awards: No awards listed in the provided text. Advising and Grants: Supervised multiple PhD students including Virginia Tadei, Gözde Bitlislioglu, Eirini Boleti, Nikunj Dudani, Giulia Ruggeri, and Amir Yazdani. Involved in large-scale monitoring network studies (e.g., IMPROVE, SEARCH) and international field campaigns (e.g., Cal-Mex, SOAS). Contributed to the development of open platforms such as AIRSpec for infrared spectroscopy analysis. Labs and Teams: Laboratory for Environmental Spectrochemistry (LESC), EPFL Collaborations with research groups in the U.S. and Europe on aerosol characterization and modeling Active participant in international conferences and research networks in aerosol science.

Junhao Wenمشاهده پروفایل

استادیار

• Computational Neuroscience
• Artificial Intelligence in Healthcare
• Medical Imaging Analysis
• +۷ مورد دیگر

Dr. Junhao Wen is an Assistant Professor of Computational Neuroscience at the Department of Radiology, Columbia University Irving Medical Center. He is also an Affiliated Member of the Health Analytics Center. His interdisciplinary work bridges advanced artificial intelligence and biomedical data to investigate human aging and disease mechanisms. Dr. Wen's research focuses on integrating AI and machine learning with multi-organ imaging (e.g., brain MRI) and multi-omics data (including genetics and proteomics). His work aims to uncover biomarkers and mechanistic insights into neurodegenerative diseases and aging processes. This positions him at the forefront of computational biomedicine and precision health analytics. His scientific approach combines deep learning, statistical modeling, and large-scale biomedical datasets to develop predictive models of disease progression. These methods are applied across diverse populations to enhance early diagnosis and intervention strategies. The Health Analytics Affiliation underscores his role in advancing data-driven healthcare solutions at Columbia. While no specific publications or awards are listed in the source text, his research trajectory reflects strong engagement with cutting-edge computational methodologies in medicine. Dr. Wen has previously held positions as a postdoctoral researcher at the University of Pennsylvania and as an Assistant Professor at the University of Southern California. He earned his Ph.D. from Sorbonne University in 2019, establishing a foundation in computational methods applied to neuroscience and biomedical data. He advises graduate students and may lead a research laboratory focused on AI-driven health discovery, though specific advisees are not named. His work likely involves collaboration across departments and institutions, supported by grants in AI, neuroscience, and aging research, although specific funding sources are not mentioned. Dr. Wen's laboratory, accessible via https://labs-laboratory.com/ , serves as a hub for interdisciplinary research in computational neuroscience and health analytics.

Milos Nikolicمشاهده پروفایل

مدرس

• Databases
• Data Management
• Incremental Computation
• +۷ مورد دیگر

Milos Nikolic is a Lecturer in Database Systems at the School of Informatics, University of Edinburgh. He is a member of the Database Group and the Laboratory for Foundations of Computer Science. Prior to joining Edinburgh, he was a Departmental Lecturer in the Department of Computer Science at the University of Oxford. He holds a PhD in Computer Science from EPFL. Research Interests: Milos Nikolic's research focuses on databases and large-scale data management, with emphasis on incremental computation, in-database learning, stream processing, and query compilation. His work explores how complex analytical queries—such as SQL, linear algebra, and machine learning tasks—can be efficiently maintained and evaluated in dynamic and distributed environments. He develops novel techniques in query optimization and compilation to enable real-time analytics over evolving data. His recent publications demonstrate a strong trend in dynamic query evaluation, particularly around conjunctive and hierarchical queries under updates, incremental view maintenance (e.g., F-IVM), and scalable processing of nested and biomedical data. His work often leverages theoretical foundations to achieve worst-case optimal performance, grounded in conjectures like the Online Matrix-Vector Multiplication (OMv) hypothesis. Scientific Awards: Best Paper Award, ICDT 2019 Advising and Grants: Milos is actively seeking PhD students to work on data management topics. While no formal list of advisees is provided, he collaborates extensively with researchers such as Dan Olteanu, Ahmet Kara, and Haozhe Zhang. His projects, including Adaptive Query Processing , Incremental Maintenance of Complex Analytics , and Declarative Data Pipelines (industry-supported), suggest ongoing grant and industry collaborations. Labs and Teams: He is a key member of the Database Group and the Laboratory for Foundations of Computer Science at the University of Edinburgh, contributing to cutting-edge research in foundational and applied database systems.

Marius Florin Niculescuمشاهده پروفایل

دانشیار

• Cybersecurity
• Economics of Information Systems
• Digital Sustainability
• +۱۱ مورد دیگر

Marius Florin Niculescu is an Associate Professor in the Department of Information Technology Management at the Scheller College of Business, Georgia Institute of Technology. His research and teaching focus on IT management, business analytics, cybersecurity, and the economics of information systems. He has published extensively in top-tier journals and is actively involved in editorial leadership. Dr. Niculescu earned his Ph.D. in Operations, Information and Technology from Stanford Graduate School of Business (2009), an M.S. in Financial Mathematics from Stanford University (2007), and a B.A. in Applied Mathematics from Harvard University (2004). His research interests span cybersecurity, digital sustainability, freemium business models, platform and network economics, cloud computing, software quality and pricing, and open innovation. His work explores how digital technologies create value, how platforms compete under network effects, and how security and sustainability can be integrated into IT strategy. His recent publications, appearing in Management Science , Information Systems Research , and MIS Quarterly , reveal a strong trend toward understanding the economic and strategic implications of cybersecurity, cloud computing, and platform design. His work combines empirical analysis with economic modeling to inform managerial decisions in digital markets. ISS Sandra A. Slaughter Early Career Award (2017) AIS Best Publication of the Year Award (2013) Best Conference Paper Award, INFORMS Conference on IS & Technology (2012) Poets & Quants Best 40 Under 40 Professors (2019) Brady Family Award for Faculty Teaching Excellence (2019) Full-Time MBA Core Professor of the Year (2017, 2018, 2019) Management Science Distinguished & Meritorious Service Awards Dr. Niculescu has served as Associate Editor for Information Systems Research (2016–2020) and Management Science (2020–2024), and is currently a Senior Editor for Production and Operations Management . He has advised PhD students as the ITM Area PhD Coordinator and has led executive education programs for The Home Depot and Bank of America. He has also been a Georgia Tech Grand Challenges Faculty Fellow. He has been actively involved in major conferences, serving as President of the INFORMS eBusiness section (2013), co-chair of the 2015 INFORMS Conference on IS & Technology, and co-chair of the 2016 Theory in Economics of Information Systems (TEIS) Workshop.

Thomas Grätschمشاهده پروفایل

استاد

• Finite Element Method
• Vibroacoustics
• Mechanical Engineering
• +۳ مورد دیگر

Prof. Dr. Thomas Grätsch is a faculty member at Hamburg University of Applied Sciences within the Faculty of Technology and Computer Science, specifically in the Department of Mechanical Engineering and Production. His office is located in Room 226e at Berliner Tor 21, 20099 Hamburg, with contact number +49 40 428 75-8705. Prof. Grätsch specializes in computational mechanics with a focus on the Finite Element Method (FEM) and its applications in vibroacoustics. His research particularly addresses noise emission from wind turbines, structural vibration analysis, and mechanical system simulations. He has developed sophisticated models for predicting and reducing tonal noise in wind energy systems, with emphasis on gearbox vibrations and acoustic radiation from large structures. His publication record shows a consistent research trajectory focused on wind turbine noise simulation, with recent work (2018-2022) concentrating on hybrid multistep procedures, large-scale finite element modeling, and practical applications for noise reduction in wind energy systems. His work bridges theoretical computational methods with practical engineering applications in renewable energy technology. Prof. Grätsch holds several administrative roles including Program Coordinator for the Master's program 'Calculation and Simulation in Mechanical Engineering', Spokesperson for the Mechanics Group, Member of the Department Council for Mechanical Engineering and Production, and Deputy Member of the Confidence Committee of the Faculty of Technology and Computer Science. He is also a Member of the Editorial Board of Computers & Structures. His research projects focus on vibroacoustics, particularly addressing noise emission from wind turbines through computational simulation and structural analysis. His work has practical implications for the wind energy industry seeking to reduce environmental noise pollution while maintaining energy production efficiency.

Maarten Vinkمشاهده پروفایل

استاد

• Migration
• Citizenship
• Immigrant Naturalization
• +۴ مورد دیگر

Maarten Vink is a Full-time Professor at the Robert Schuman Centre for Advanced Studies at the European University Institute (EUI) in Florence, Italy. He serves as Chair in Citizenship Studies and Director of the Global Citizenship research area within the Global Governance Programme, and is also Co-Director of the Global Citizenship Observatory (GLOBALCIT). Originally from the Netherlands, Professor Vink is currently on leave from Maastricht University where he holds the position of Professor of Political Sociology and was one of the founders of the Maastricht Center for Citizenship, Migration and Development (MACIMIDE). Professor Vink's educational background includes a PhD in Political Science from Leiden University (2003), establishing his foundation in political sociology with a specialization in citizenship and migration studies. Professor Vink's research focuses on the complex interplay between migration and citizenship in contemporary societies. His work examines immigrant naturalization processes, comparative citizenship regimes across different national contexts, dual citizenship policies, and the Europeanization of citizenship norms. He investigates how citizenship laws and policies affect migrant integration, political participation, and social cohesion in diverse democratic societies. His research combines theoretical insights from political science and sociology with rigorous empirical analysis of citizenship policies and their implementation across multiple countries. The recent publications by Professor Vink reveal a strong emphasis on global comparative analysis of citizenship policies, with particular attention to dual citizenship acceptance patterns, immigrant inclusion metrics, and the security of citizenship status across different political contexts. His work demonstrates methodological sophistication that combines large-scale dataset development with nuanced qualitative analysis of citizenship law implementation. ERC Consolidator Grant (2016-2021) for the research project 'Migrant Life Course and Legal Status Transition (MiLifeStatus)' Professor Vink has supervised several graduate students including June Haugrud, Meret Stephan, and Ashley Mantha-Hollands. His research has been supported by significant grants, most notably the European Research Council Consolidator Grant that funded his five-year research project on migrant life course and legal status transitions. This project represents a substantial investment in understanding the longitudinal dynamics of migrant integration and citizenship acquisition. As Co-Director of the Global Citizenship Observatory (GLOBALCIT), Professor Vink leads an international research team focused on developing comprehensive datasets and analytical frameworks for understanding citizenship policies worldwide. The GLOBALCIT team has created influential resources including the GLOBALCIT Citizenship Law Dataset, which enables systematic comparison of citizenship regulations across different countries and time periods.

Dan Steinbergمشاهده پروفایل

دانشگاهی

• Probabilistic Machine Learning
• Variational Inference
• Bayesian Deep Learning
• +۷ مورد دیگر

Dan Steinberg is a senior research scientist and team leader of the Decisions & Statistical Learning team at CSIRO Data61 in Canberra, Australia. His expertise lies in probabilistic machine learning, variational inference, Bayesian deep learning, causal inference, and their application to domains spanning synthetic biology, geospatial analytics, and algorithmic fairness. Education PhD in Computer Vision / Machine Learning (2013) – University of Sydney, Australian Centre for Field Robotics Bachelor of Engineering (Mechatronics, First-Class Honours) – University of Sydney (2008) Bachelor of Commerce (Finance) – University of Sydney (2008) Research Interests Steinberg’s core research agenda revolves around building scalable probabilistic models that can learn efficiently from limited or noisy data and provide principled uncertainty estimates. Key themes include: Variational Inference & Bayesian Deep Learning: developing lightweight yet powerful algorithms for approximate posterior inference in complex models (e.g., Aboleth, Revrand). Active Learning & Experimental Design: creating methods that decide which experiments or measurements will maximise information gain, with recent focus on in-silico protein engineering via Variational Search Distributions (VSD). Causal Inference: leveraging machine-learning tools to perform robust observational causal studies for evidence-based policy, including work on youth well-being and academic outcomes. Algorithmic Fairness: translating normative notions of equity into quantifiable objectives for regression-based decision systems. Large-scale Spatial Analytics: Landshark—an open-source TensorFlow toolkit for supervised learning on massive geospatial raster datasets. Notable Software & Tools Aboleth: A minimal-overhead TensorFlow framework for Bayesian deep learning. Landshark: Command-line tools for large-scale spatial inference. Revrand: Scalable Bayesian generalised linear models with non-conjugate likelihoods. libcluster: Extensible C++ library for hierarchical Bayesian clustering. Scientific Awards Oral Presentation Award – ICML 2025 Workshop on Scaling up Intervention Models (SIMS) Oral Presentation Award – NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty (BDU) Oral Presentation Award – NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning Spotlight Paper Award – NeurIPS 2014 (Extended and Unscented Gaussian Processes) Research Team & Collaborations As Team Leader – Decisions & Statistical Learning at CSIRO Data61, Steinberg directs a multi-disciplinary group that partners with government agencies (e.g., Jobs and Skills Australia, Australian Institute of Health and Welfare) and industry to deploy machine-learning solutions at scale. He has previously held roles as Principal Researcher at Gradient Institute (2019-2023), Senior Research Engineer at CSIRO Data61 (2016-2019), Researcher at NICTA (2013-2016), and Research Associate at the University of Sydney (2012-2013).

• Sediment Transport
• River Morphology
• Microplastic Pollution
• +۲ مورد دیگر

Dr. BARANYA Sándor is an Associate Professor and Head of the Department of Hydraulic and Water Resources Engineering at the Budapest University of Technology and Economics, Faculty of Civil Engineering. He holds key administrative roles, including Faculty Council Representative, Chairman of the Economic Committee, and Erasmus Committee Member. His office is located in Building K, Room MF 19, and he can be contacted via email or phone. His research spans sediment transport , river morphology , microplastic pollution , and computational fluid dynamics (CFD) . He employs innovative methods such as acoustic mapping, machine learning, remote sensing (Sentinel-2, Landsat), and numerical modeling to study large river systems, particularly the Danube. His work addresses ecological impacts, including thermal pollution from power plants and microplastic distribution. Recent publications (2023–2025) focus on: Sediment-microplastic dynamics using integrated field-data and AI Historical river regulation impacts CFD-based restoration strategies Advanced monitoring techniques (e.g., acoustic velocimetry, deep learning for riverbed analysis) He teaches courses including Hydraulics , Hydromorphology , and Water Utilisation & Damage Prevention , and mentors students in TDK (Research Society) projects on sediment transport, river habitats, and microplastics. He participates in EU initiatives like DanubeSediment for transnational sediment management.

Torsten Zeschمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Educational Technology
• +۶ مورد دیگر

Prof. Dr.-Ing. Torsten Zesch serves as Deputy Scientific Director, Member of the Executive Board, and Head of the Research Professorship for Computational Linguistics at FernUniversität in Hagen since March 2022. He previously held W2 and W1 Professorships for Sprachtechnologie (Language Technology) at Universität Duisburg-Essen from 2014-2022. Zesch is also Spokesperson of the Advisory Board of the German Society for Computational Linguistics and Language Technology (GSCL) since 2024, having previously served as GSCL President from 2018-2024. Dr. Zesch completed his dissertation (Dr.-Ing.) in Computer Science at Technische Universität Darmstadt in 2009. His research spans robust language processing systems, analysis of non-standard language structures, and educational applications of language technology, with particular focus on automatic content scoring and spelling error correction for learner language. Zesch's recent publications reveal a strong focus on integrating language technology with educational applications. His work demonstrates expertise in developing practical NLP solutions for educational assessment, including transformer-based spelling error feedback systems, hierarchical automatic scoring methods, and leveraging LLMs for educational applications despite cold-start problems. He also maintains significant research in hate speech detection, particularly in multimodal contexts and visio-linguistic models. As leader of the Computational Linguistics research professorship within the CATALPA research center, Zesch directs a team investigating how language technology can support educational processes. His projects DAKODA and KISS-Pro focus on language acquisition and educational applications. He has contributed significantly to the field through numerous publications in top NLP and educational technology venues, with over 100 publications spanning from 2006 to present.