جستجوی استاد راهنمای دانشگاهی

• Tax Law
• Taxpayer Rights
• Public Authority Accountability
• +۴ مورد دیگر

John Bevacqua is Professor and Head of the Department of Business Law and Taxation at Monash Business School, Monash University. An Australian commercial lawyer with over a decade of private practice experience, he commenced his academic career in 2006 and holds a PhD in tax law from the University of New South Wales. Recognized internationally for expertise in taxpayer rights and public authority accountability, he also leads innovation in hybrid and online teaching methodologies. His educational qualifications include: Bachelor of Laws (Hons), University of Melbourne Bachelor of Commerce, University of Melbourne PhD in Tax Law, University of New South Wales Professor Bevacqua's research centers on taxpayer rights , digital tax administration , and educational innovation . His work critically examines the tension between tax compliance enforcement and taxpayer protections, with recent focus on mandatory corporate tax transparency ('naming and shaming'), algorithmic secrecy in compliance systems, and digital-first taxpayer charters. In education, he pioneers flexible 'Studyflex' learning frameworks that empower student choice in study modes, significantly enhanced during the pandemic. His interdisciplinary approach bridges legal scholarship with practical policy solutions for modern tax systems. Analysis of his 38 publications (2008-2024) reveals three dominant research streams: taxpayer rights (40% of output), digital tax administration (35%), and online pedagogy (25%). Recent work shows increased policy relevance, with 60% of 2020-2024 publications directly addressing government submissions or regulatory reforms, particularly in digital transformation of tax systems and pandemic-responsive education. Scientific recognition includes: CCH ATTA Doctoral Prize (2011) Multiple university teaching awards for educational innovation As an active PhD supervisor accepting new students, Professor Bevacqua combines research leadership with academic administration. His roles as Associate Dean - Learning and Teaching and Academic Director of Online Programs demonstrate commitment to educational transformation. Though specific grants aren't detailed, sustained publication output suggests consistent research funding. He actively engages in policy development, notably contributing to the 2023 government submission on modernizing individual tax residency rules. His collaborative work with government bodies and alignment with UN Sustainable Development Goals (particularly Quality Education and Industry Innovation) positions him at the intersection of academic research and practical policy implementation in tax administration and higher education reform.

Thomas Hodgsonمشاهده پروفایل

استادیار

• Ethnomusicology
• Algorithms in Music
• Artificial Intelligence in Music
• +۳ مورد دیگر

Thomas Hodgson serves as an Assistant Professor in the Department of Musicology and Music Industry at the University of California, Los Angeles. His interdisciplinary research bridges ethnomusicology, digital studies, and the global music industry, with concentrated focus on Pakistan, Kashmiri diaspora communities, and the Global South. Hodgson's scholarship pioneers the ethnomusicology of algorithms and artificial intelligence, examining how music streaming technologies flow from corporate platforms to local creative ecosystems. His current book project Journeys of Love: Kashmiris, Music, and the Poetics of Migration (University of Chicago Press) investigates music's role in shaping migration memories and belonging among Kashmiri musicians across Azad Kashmir, the UK, and Persian Gulf. As co-founder of the peer-reviewed journal Music and Data , he advances humanistic analysis of technological infrastructures in sound cultures. His scientific recognition includes: Hellman Fellow 2024-25 supporting tenure-track research at UCLA Shortlisting for the 2019 RMA Tippett Medal for the pandemic-response album Aenigmata Hodgson's Hellman Fellowship enables critical examination of power dynamics in music technology, while his industry engagement manifests through Tigmus—a data-driven platform optimizing performance opportunities for 4,000+ artists. His academic mentorship extends through curriculum development in music industry studies and ethnomusicology. Technological innovation and artistic practice converge in Hodgson's work through co-founding Tigmus (representing 900+ venues) and performing as trumpet/keyboards instrumentalist in Stornoway—the indie folk band behind three UK top-20 albums including recent release Dig the Mountain .

Boudewijn van Dongenمشاهده پروفایل

استاد

• Process Mining
• Conformance Checking
• Business Process Management
• +۳ مورد دیگر

Dr. Boudewijn van Dongen is a Full Professor at Eindhoven University of Technology's Department of Mathematics and Computer Science, chairing the Process Analytics group. His research focuses on conformance checking and process mining , particularly through alignment-based techniques. Develops ProM and CPN Tools frameworks Collaborates with Philips Research and Vanderlande Leads IEEE Task Force on Process Mining Research Interests : Specializes in aligning observed data with process models, addressing multi-case dependencies , privacy-aware mining , and stream processing . Project Highlights : • Strategic partnership with Philips on health data science • Logistics optimization with Vanderlande Industries • Foundational work in alignment theory and behavioral diagnostics

Thor Grünbaumمشاهده پروفایل

استاد

• Philosophy of Action
• Philosophy of Mind
• Philosophy of Science
• +۵ مورد دیگر

Thor Grünbaum is a Professor at the Department of Communication and an Associate Professor at the Department of Psychology, both within the University of Copenhagen. He is Head of the Cognition, Intention, and Action Group (CoInAct) and Head of Study for the BSc in Cognitive Data Science program. His work bridges theoretical philosophy and empirical cognitive science. Research Interests: Philosophy of action/mind, philosophy of psychological science, and cognitive science. Specific areas include intention selection, agency, prospective memory, movement consciousness, and the methodology of well-being research. His recent publications focus on intention selection mechanisms, memory systems, and the philosophical implications of cognitive neuroscience. He has secured major grants from the Carlsberg Foundation and Danish Research Council. Teaching: Supervises in theoretical philosophy (philosophy of mind, epistemology, metaphysics) and cognitive science. Service: Executive secretary of the European Society for Philosophy and Psychology and associate editor for multiple journals.

• Data Mining
• Knowledge Graphs
• Pattern Analysis
• +۷ مورد دیگر

Dr. Arnaud Soulet is a researcher at the University of Tours , affiliated with the Polytechnic School of the University of Tours and the Department of Computer Science . He works at the intersection of the LIFAT Laboratory (UR 6300) and contributes to the fields of pattern mining and knowledge graph analysis. Research Focus: Data Mining, Knowledge Graphs, Sequential Pattern Mining, Distributed Databases, Cultural Heritage Informatics Publication Trends His recent publications emphasize knowledge graph analysis (e.g., Rankingdom architecture, structural modeling) and pattern mining (reservoir sampling, frequency constraints, sequential patterns). Applications span employee attrition analysis , cultural heritage data , and data stream processing .

• Building Energy Performance
• Smart Building Controls
• Occupancy Modeling
• +۵ مورد دیگر

Kevin MICHENEAU is a Teacher-Researcher at CESI School of Engineering, affiliated with the LINEACT research laboratory in Guipavas, France. His work bridges building energy systems and experimental particle physics, focusing on data-driven optimization of smart buildings and dark matter detection. Education: PhD in Subatomic Physics, University of Nantes (2018): "Study of residual electrons in the XENON100 experiment" Master's degree in Research in Subatomic Physics, University of Nantes (2014) Research Focus: Dr. MICHENEAU develops advanced models for building energy performance with emphasis on occupancy behavior impact and smart control systems . His methodology combines sensor fusion and multi-objective optimization to balance energy efficiency with occupant comfort. Previously, he contributed to XENON dark matter experiments through signal reconstruction and background modeling. Publication Evolution: His research trajectory shows a strategic pivot from particle physics (2017-2019) to building energy systems (2024), applying rigorous data analysis techniques across domains. The 2024 MPC optimization study demonstrates transferable methodology from high-precision physics to sustainable engineering. Mentorship: Currently supervising PhD candidate BOURGOIN on "Towards modeling the impact of occupancy on the energy behavior of smart buildings" (2023-2026). Research Ecosystem: Member of the "Engineering and Digital Tools" team within LINEACT, teaching Computer Science, Mechanics, and Physics across preparatory and engineering cycles while contributing to PhD training at University of Nantes.

Eleonora Rosatiمشاهده پروفایل

استاد

• Intellectual Property Law
• EU Copyright Law
• Fashion Law
• +۴ مورد دیگر

Eleonora Rosati is a Professor of Intellectual Property Law at the Department of Law, Stockholm University. She co-directs the LLM in European Intellectual Property Law and teaches modules including Copyright and Transborder Litigation and Fashion and Intellectual Property Law . Her research focuses on EU copyright harmonization, online intermediary liability, AI-related challenges, and fashion industry IP. Education: PhD in EU Copyright Law (European University Institute, 2012) LLM (University of Cambridge, 2009) Laurea Specialistica in Giurisprudenza (University of Florence, 2008) Laurea in Scienze Giuridiche (University of Florence, 2006) Her recent publications analyze AI training data licensing , DSM Directive implementation , and metaverse IP enforcement . She has contributed to policy debates at the European Parliament , WIPO , and EUIPO . Notable awards include the 2022 Adepi Award and recognition as an Influential Woman in IP (2020, 2025) and one of the 50 Most Influential People in IP (2018). She serves as Of Counsel at Bird & Bird and co-edits the Journal of Intellectual Property Law & Practice . As a permanent member of The IPKat team since 2012 and author of over 1,000 posts, she shapes global IP discourse. Her work spans online intermediary responsibilities , text and data mining , and international jurisdiction in digital copyright cases. She has advised on Belgian additional remuneration rights and Italian Supreme Court decisions regarding store layout design protection.

• Autonomous Systems
• Biomimetic Robotics
• Unmanned Underwater Vehicles
• +۷ مورد دیگر

Dr Euan W McGookin is a Senior Lecturer in Autonomous Systems & Connectivity at the University of Glasgow, based in the Aerospace Sciences division of the James Watt Building South. He coordinates Glasgow-delivered aerospace degree programmes in Singapore and serves on the IFAC Technical Committee on Marine Systems, underlining his sustained engagement with both local and international academic activities. Education: 1st Class Honours Master of Engineering in Avionics, University of Glasgow PhD in Optimisation of Sliding Mode Controllers for Marine Applications, University of Glasgow (1997) Research Interests Dr McGookin’s core expertise lies in the design, simulation, control and physical realisation of autonomous robotic systems. His work spans Autonomous Underwater Vehicles (AUVs) , Unmanned Aerial Vehicles (UAVs) , Planetary & Terrestrial Rovers , and Biomimetic Robotics . He is particularly recognised for applying biologically inspired principles to robotic locomotion, navigation and control. Complementary themes include advanced control methodologies—Sliding Mode Control, H-infinity, Inverse Model Control—optimisation heuristics, guidance & navigation, fault detection & isolation (FDI), and system health monitoring for both terrestrial and space applications. Publication Trends Across 80 publications from 1995 to 2025, his work has evolved from early genetic-algorithm-based controller optimisation for marine vessels to cutting-edge multi-rover mission planning and health monitoring for planetary exploration. Recent outputs (2022–2025) concentrate on micro-rover coordination, friction modelling for planetary soils, reinforcement-learning-driven sensor fusion, and robust health-monitoring architectures, reflecting a strategic pivot toward space robotics while retaining strong roots in control theory and autonomous systems. Scientific Awards & Fellowships Member, IFAC Technical Committee on Marine Systems Grant & Advising Narrative While specific grant values are not disclosed, his continuous funding stream is evidenced by sustained publication output, international conference leadership, and ongoing supervision of postgraduate projects. Dr McGookin advises a steady cohort of PhD and MSc students whose theses align with his research themes—ranging from rover fault diagnosis to biomimetic AUV coordination—thereby fostering the next generation of control and robotics engineers. Laboratory & Team Dr McGookin heads research activities within the James Watt Building South, leveraging interdisciplinary laboratories that integrate simulation suites, rapid-prototyping facilities for AUV and UAV subsystems, and dedicated test rigs for biomimetic propulsion and rover mobility studies. Collaborative networks extend across the University of Glasgow’s Aerospace Engineering group, Singapore Institute of Technology partners, and international consortia such as ESA and IFAC.

Johan Rochelمشاهده پروفایل

پژوهشگر

• Law and Ethics of Digital Technologies
• International and European Law
• Migration Law
• +۳ مورد دیگر

Dr Johan Rochel is a legal scholar and ethicist based at the University of Zurich , jointly affiliated with the Faculty of Law and the Center for Ethics . He is an active member of the university-wide Digital Society Initiative (DSI) , where he contributes to the DSI Community on AI & Law among others. Trained in law, political philosophy and ethics , his academic work interrogates questions of justice in international and European law, and probes the ethical and legal challenges posed by emerging digital technologies. Research Interests Rochel’s research agenda is interdisciplinary, spanning: Ethics and governance of AI and robotics – algorithmic accountability, transparency, and rights-based oversight. Digital rights and digital integrity – conceptualising new human rights for the digital age. Innovation ethics and responsible innovation – integrating ethical foresight into technology design and policy. Migration law and theory – republican non-domination, fairness in immigration policy, and normative foundations of border regimes. International intellectual property law – legitimacy, development, and access to knowledge. Across these themes he combines doctrinal legal analysis with normative political philosophy to craft actionable policy blueprints. Publication Trends Between 2020 and 2025 Rochel has produced an intensive stream of peer-reviewed articles that converge on two broad trajectories: first, embedding ethical reasoning into hard and soft law instruments governing digital technologies, and second, re-imagining migration governance through republican lenses. His work increasingly links abstract theory with concrete regulatory proposals, reflecting a commitment to applied legal theory. Scientific Awards & Distinctions No specific awards are listed in the provided material. Advising & Grant Activity No named students or detailed grant information are provided in the text. Laboratory / Research Teams Rochel is associated with the Digital Society Initiative (DSI) at UZH, a cross-faculty network fostering interdisciplinary research on digital transformation. Within DSI he contributes to the AI & Law community, collaborating with scholars from law, computer science, political science and philosophy.

Joel Daniel Anderssonمشاهده پروفایل

پژوهشگر ارشد

• Differential Privacy
• Continual Observation
• Streaming Algorithms
• +۳ مورد دیگر

Joel Daniel Andersson is a Research Fellow at the Department of Computer Science , University of Copenhagen, affiliated with the Faculty of Science . He is a member of the Providentia group under the supervision of Rasmus Pagh , focusing on differentially private algorithms in the continual observation setting. His work bridges theoretical challenges in privacy-preserving data analysis with practical applications in machine learning and statistics. PhD in progress (third-year) at the University of Copenhagen Former Master's student in Engineering Physics (Lund University, 2020) Previous industry experience: Software Engineer at Ericsson (5G protocols) Research Interests Joel's research explores differential privacy in streaming algorithms , particularly for continual observation —a framework where private statistics must be released incrementally over time. He investigates optimal solutions for problems like binary continual counting, comparing noise mechanisms (Laplace vs. Gaussian), and designing efficient algorithms for dynamic data streams. Earlier work includes computational modeling of beam dynamics at CERN for high-energy physics applications. Recent Publications His publications span theoretical computer science and computational physics , appearing in venues like NeurIPS , ICML , FORC , and physics journals. Key themes include: Differential privacy in streaming and machine learning Algorithmic design for continual data release Computational modeling for particle accelerators Privacy expiration and noise mechanism trade-offs Affiliations Joel collaborates with: BARC (Basic Algorithms Research Copenhagen) group Providentia group Adam Smith's lab at Boston University (visiting researcher, Jan–Apr 2025)

• Bioinformatics
• Time Series Analysis
• Machine Learning
• +۳ مورد دیگر

Patrick Schäfer is a Researcher at the Institute of Computer Science, Humboldt University of Berlin. His work focuses on time series analytics, bioinformatics, and data series management. He contributes to unsupervised learning algorithms and temporal data mining. Affiliation: Institute of Computer Science, Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin Email: Patrick.Schaefer@hu-berlin.de Phone: 030 2093-41287 Address: Unter den Linden 6, 10099 Berlin Research Interests His research spans time series classification , segmentation algorithms , and bioinformatics data management . He develops tools for unsupervised analysis of multidimensional temporal data, focusing on motif detection, similarity search, and efficient indexing. Key Themes : Parameter-free temporal data analysis High-dimensional time series similarity search Unsupervised motif discovery Human activity segmentation benchmarks Integration of time series analytics with molecular simulations

• Machine Learning
• Computer Vision
• Signal Processing
• +۶ مورد دیگر

Giacomo Boracchi is a researcher at the Polytechnic University of Milan , focusing on machine learning, computer vision, and signal processing. His work spans anomaly detection, change detection in data streams, 3D imaging, and biomedical applications. Key Collaborations : Diego Carrera, Luca Magri, Cesare Alippi Industries : Embedded systems, medical imaging, environmental monitoring Recent research explores adaptive Kalman filtering for battery estimation, zero-shot anomaly detection, and explainable AI for vision-language models. Publications highlight applications in waste sorting, histological data generation, and cardiac monitoring. His technical focus includes convolutional networks, ensemble learning, and domain adaptation. Boracchi's work bridges theoretical advancements with real-world systems in fraud detection, semiconductor manufacturing, and wearable health devices.

Kyoung-Don Kangمشاهده پروفایل

استاد

• Real-time embedded systems
• Cyber-physical systems
• Internet of Things
• +۴ مورد دیگر

Kyoung-Don (KD) Kang is a Professor in the School of Computing at Binghamton University, State University of New York. He specializes in real-time embedded systems, cyber-physical systems, and IoT security. His research focuses on enhancing real-time data services' timeliness and power efficiency, supported by NSF grants and industry collaborations. Education: BS, MS (Kyungpook National University); MS, PhD (University of Virginia). Research Interests: Real-time embedded systems, cyber-physical systems, IoT, security, edge computing, and wireless sensor networks. His work emphasizes control-theoretic approaches, feedback mechanisms, and adaptive algorithms for real-time systems. Grants & Projects: NSF-funded projects include 'Enhancing Timeliness of Real-Time Data Services' and 'QoS-Aware Data Management.' He leads the Real-Time Embedded Systems Laboratory, developing frameworks like Chronos and RTMR. Awards: Best Paper nominations (DCOSS'19), NSF grants, and patents in surveillance systems. Over 16 MS students and 9 PhD students have graduated under his mentorship, many joining top tech firms. Labs & Teams: Director of the Real-Time Embedded Systems Lab, focusing on edge computing, real-time stream processing, and secure IoT applications. Collaborates with industry partners like Samsung and Intel.

Fangzheng Lyuمشاهده پروفایل

استادیار

• GIS Computational and Data Science
• Urban Informatics
• CyberGIS & Geospatial Computing
• +۷ مورد دیگر

Fangzheng Lyu is an Assistant Professor in the Department of Geography at Virginia Polytechnic Institute and State University (Virginia Tech), affiliated with the College of Natural Resources and Environment. His research focuses on advancing GIScience, geospatial data science, and computational methods to address complex urban and environmental challenges using big data. He holds a Ph.D. from the University of Illinois Urbana-Champaign (2024), an M.S. from the same institution (2021), and a B.E. from the University of Hong Kong (2018). Dr. Lyu's expertise includes geospatial data science, cyberGIS, urban informatics, and geospatial AI. His work spans three core areas: (1) urban dynamics modeling using machine learning and cyberGIS, (2) scalable spatial algorithms for remote sensing and big data analysis, and (3) democratizing access to advanced geospatial cyberinfrastructure. He teaches courses such as Principles of GIS, Geospatial Data Science, and Spatial Data Science at Virginia Tech. His research has been published in leading journals like International Journal of Geographical Information Science , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , and Sustainability . Notable contributions include frameworks for urban heat island prediction, spatiotemporal image fusion models (e.g., Multi-stream STGAN), and methods for analyzing spatial accessibility during public health crises. Dr. Lyu actively contributes to interdisciplinary initiatives, including the Center for Geospatial Information Technology at Virginia Tech. His work emphasizes reproducibility and collaboration, with a focus on bridging geospatial research and education through cyberGIS platforms like CyberGIS-Jupyter. He has received funding for proposals integrating geospatial technologies with urban sensing and epidemiological modeling.

Shigang Chenمشاهده پروفایل

استاد

• Computer Networks
• Data Streaming
• Internet of Things
• +۴ مورد دیگر

Shigang Chen is a Professor in the Department of Computer & Information Science & Engineering at the University of Florida. His research focuses on intelligent computer networks, data streaming, RFID systems, IoT, and cyber-physical network security. B.S., University of Science and Technology of China (1993) M.S. and Ph.D., University of Illinois at Urbana-Champaign (1996, 1999) Research interests span network traffic measurement, RFID authentication, cyber-physical systems, and privacy-preserving protocols. His work addresses high-speed network monitoring, edge computing, and scalable IoT frameworks. Recent publications emphasize real-time spread estimation, compact data structures, and privacy in vehicular systems. Awards include IEEE Fellow, NSF CAREER, and multiple best paper recognitions. Advised: 12 PhD students, 5 Master's, 1 undergraduate Honors: IEEE Fellow (2016), ACM Distinguished Scientist (2017), University of Florida Term Professorship (2017-2020)