Find Academic Supervisors

• Cybersecurity
• Privacy-Preserving Technologies
• Homomorphic Encryption
• +4 more

Amy Corman is a Lecturer in Mathematics - Cybersecurity at the School of Science, RMIT University, based at the City Campus in Australia. Her academic work bridges theoretical mathematics with practical cybersecurity applications, focusing on privacy-preserving technologies and cryptographic protocols. Dr. Corman's research spans several critical areas in modern cybersecurity: Privacy-preserving technologies for healthcare data Post-quantum cryptography and homomorphic encryption Secure protocols for distributed and peer-to-peer systems Gender diversity issues in the cybersecurity workforce Public understanding of data privacy mechanisms Her publication history reveals an evolution from foundational work on peer-to-peer security protocols (2006-2007) to contemporary research on healthcare data privacy and post-quantum cryptography (2021-2025). Recent publications demonstrate increasing focus on making complex privacy technologies accessible and usable, particularly in healthcare contexts where differential privacy and homomorphic encryption can protect sensitive information while enabling research. Her 2025 work on code-based alternatives to lattice-based post-quantum homomorphic encryption represents cutting-edge research preparing cryptographic systems for the quantum computing era. Dr. Corman maintains active research supervision with projects focused on: Privacy Preserving Technologies for Securing Healthcare Data (2025) Enhancing Zero-Knowledge Server Functionality (2023) Her research on women's attrition in cybersecurity (2024) combines literature review with interview analysis to address workforce diversity challenges in the field. This multi-faceted research program demonstrates both technical depth in cryptographic methods and awareness of broader social implications of security technologies.

• Ethnomusicology
• Cognitive Ethnomusicology
• Rhythm Perception
• +3 more

Udo Will is a Professor of Ethnomusicology at the School of Music, Ohio State University, supported by an Academic Enrichment Award. His roles include being president of the European Seminar in Ethnomusicology and serving on the editorial board of the British Journal for Ethnomusicology. He previously held teaching positions at the University of Bielefeld (Music/Sociology) and the University of New England, Australia. Dr. Will’s research focuses on cognitive ethnomusicology, rhythm perception, cultural studies of music, and the intersection of neuroscience with musical practices. Key themes include rhythmic entrainment, cross-cultural musical analysis, and the evolutionary history of vocal/instrumental music. His work bridges disciplines through EEG methodologies, linguistic studies, and comparative cultural frameworks. His articles (2018–1997) explore topics like rhythmic memory mechanisms, neural synchronization to music, and cultural influences on musical perception. Notable works include studies on North Indian alap improvisation, Australian Aboriginal pitch systems, and tonal language processing. Awards include the Academic Enrichment Award (School of Music). His contributions span theoretical frameworks in cognitive ethnomusicology and applied research in music neurocognition.

Plamen Ch. IvanovView profile

Research Professor

• Network Physiology
• Nonlinear Dynamics
• Physiological Systems
• +3 more

Plamen Ch. Ivanov is a Research Professor and Director of the Keck Laboratory for Network Physiology at Boston University's School of Science. He pioneered the interdisciplinary field of Network Physiology, focusing on dynamic interactions between organ systems to understand health and disease. His work integrates statistical physics, nonlinear dynamics, and network theory to analyze physiological signals and model emergent systems behavior. Education: M.S. in Condensed Matter Physics (Sofia University), Ph.D. in Cellular Biophysics (Boston University). Research interests center on systems physiology, cardiac-respiratory dynamics, sleep regulation, and network-based approaches to aging and exercise physiology. His lab developed novel methods for analyzing time-varying organ system interactions, contributing to the Human Physiolome initiative. Key contributions include discovering basic laws of physiological regulation, identifying critical dynamics in brain rhythms across sleep states, and revealing age-related breakdown in cardio-muscular networks. Articles focus on network physiology applications in sleep medicine, exercise science, and neurodegenerative disorders. Major Awards: $1M W.M. Keck Foundation Award (2015) Editorial Roles: Field Chief Editor of Frontiers in Network Physiology Founding Director: International Summer Institute on Network Physiology (ISINP) NIH/ONR/BSF-funded research Labs/Teams: Leads the Keck Lab, collaborates internationally on PhysioNet data sharing platform. Active in machine learning approaches for physiological signal analysis and network modeling.

• Complex Systems
• Network Theory
• Dynamical Systems
• +17 more

Nicolas Rubido Obrer is a Lecturer in the Department of Physics at the School of Natural and Computing Sciences, University of Aberdeen, UK. He is affiliated with the Institute for Complex Systems and Mathematical Biology (ICSMB) and previously served as an Adjunct Professor at the Physics Institute, Universidad de la República (UdelaR), Uruguay, and as a Research Fellow at the Aberdeen Biomedical Imaging Centre (ABIC). He earned his PhD in Physics from the University of Aberdeen in 2014, with a thesis on energy transmission and synchronization in complex networks. PhD in Physics – University of Aberdeen (2014) MSc in Physics – Universidad de la República (2010) BSc in Physics – Universidad de la República (2008) His research focuses on complex systems, employing network theory, dynamical systems, numerical modeling, and data analysis to study emergent behaviors such as synchronization and chaos. He applies these methods across interdisciplinary domains including brain networks (Alzheimer’s disease, sleep-wake cycles), climate modeling, and power-grid stability. He is particularly interested in network inference and reverse engineering system connectivity from observational data. The recent trend in his publications reflects a strong emphasis on interdisciplinary neuroscience, with high-impact contributions in Nature Medicine , NeuroImage , and Scientific Reports , focusing on brain aging, neurodegeneration, and neuroimaging. His work also spans climate dynamics and foundational network theory, demonstrating both applied and theoretical depth. His scientific awards include the prestigious Springer Theses Award (2015) and the Young Researchers Award at Dynamics Days Europe (2016), as well as the SUPA Studentship Prize (2011). Nicolas supervises PhD and MSc students in Physics, Mathematics, and Applied Health Sciences, and is actively involved in international collaborations with institutions in Uruguay, Brazil, Spain, Argentina, and the UK. He has led and contributed to projects on EEG-based biomarkers for aging, functional ultrasound imaging, and climate forecasting. His research integrates theoretical modeling with experimental and clinical data, advancing methodologies in network science and complex systems analysis. He is a member of the Non-Linear Physics group at UdelaR and associated with the Laboratory of Instabilities in Fluids. His ongoing work includes developing data-driven models for complex systems and exploring the role of network structure in synchronization and information transmission.

Ekkehard UllnerView profile

Lecturer

• Nonlinear Dynamics
• Statistical Physics
• Systems Biology
• +7 more

Dr. Ekkehard Ullner is a Lecturer in the Department of Physics at the University of Aberdeen, affiliated with the Institute for Complex Systems and Mathematical Biology (ICSMB) and the School of Natural and Computing Sciences. He has been a SULSA Lecturer for Systems Biology since 2003 and is actively involved in research, teaching, and postgraduate supervision. His educational background includes a Dr. rer. nat. (summa cum laude) from the University of Potsdam, Germany, with a thesis on noise-induced phenomena in neural models, supported by an International Max Planck Research School stipend. He also held a research fellowship from the Alexander von Humboldt Foundation. Dr. Ullner's research centers on nonlinear dynamics and stochastic processes in biological systems. Key areas include balanced neuronal networks, synthetic genetic oscillators, collective dynamics in spiking neurons, noise-induced phenomena, and modeling of complex biological systems. His work bridges physics, biology, and computational modeling. His recent publications (2014–2024) reflect a strong focus on collective neural dynamics, noise-induced computation, aging propagation in biological networks, and robust control in gene expression. The research demonstrates interdisciplinary collaboration and a consistent application of statistical physics to biological problems. Alexander von Humboldt Foundation Research Fellowship Dr. rer. nat. summa cum laude (University of Potsdam) Dr. Ullner supervises PhD students in Physics and related fields, particularly in data science, statistical physics, and modeling biological systems. He is also the Director of Postgraduate Programmes in the Department of Physics and serves as Postgraduate Research School Officer. He teaches courses such as Relativity and Quantum Mechanics (PX2510), Quantum Mechanics (PX3511), and Statistics and Time Series Analysis (PX5010). He is associated with the SyMBioSIS research group and contributes to interdisciplinary initiatives at the intersection of physics, biology, and data science.

• Smart Grids
• Energy Storage Systems
• Electric Vehicle Charging
• +7 more

Dr. Ben Potter is a researcher at the University of Reading, with a sustained record of scholarly contributions in electrical engineering and energy systems. His work is closely associated with the development and analysis of smart grid technologies, energy storage, electric vehicle integration, and power electronics. He has collaborated extensively with researchers including William Holderbaum, S. T. Smith, and T. Yunusov across multiple high-impact journals and conferences. His research interests span a wide range of topics critical to modern energy infrastructure: Smart grid control and optimization Energy storage integration and scheduling Electric vehicle charging and depot management Low-voltage distribution network operations Techno-economic modeling of energy systems Power electronics and resonant converters The trend in his recent publications shows a strong focus on integrating renewable energy and electric transport into the grid through intelligent control, economic modeling, and real-time parameter estimation. His work often combines theoretical modeling with practical implementation, particularly in the context of distribution network operator (DNO) challenges. Dr. Potter has made significant contributions to the understanding of: Carbon impacts of electricity network investments Frequency response in complex power systems Design of axial flux wind generators Non-invasive transmission line monitoring He has advised or collaborated with several researchers who appear as co-authors, though no formal PhD or Master’s students are explicitly listed. His research has been supported by projects related to smart grids, energy storage, and sustainable infrastructure, as reflected in his publication topics. He is affiliated with a research group focused on power systems and energy management, likely within the School of Engineering at the University of Reading, though the exact departmental structure is not specified in the data.

• Control Theory
• Nonlinear Systems
• Complex Networks
• +7 more

Jinsheng Sun is a prolific researcher with active contributions to Control Theory , Complex Networks , and Image Processing , often collaborating with scholars from institutions like the University of Melbourne and Harbin Institute of Technology . His work spans theoretical advancements and applied methodologies. Key Affiliations : Co-authored papers with researchers from diverse domains, indicating interdisciplinary collaborations. Research Themes : Focus on control systems for nonlinear dynamics, synchronization in complex networks, and forensic analysis of digital media. Research Interests revolve around: Designing adaptive control mechanisms for nonlinear systems and vibration systems , as seen in his 2025 work on transient performance design. Advancing complex network analysis through novel algorithms for identifying vital spreaders and secure synchronization protocols. Developing digital forensics techniques for JPEG compression and watermarking, with applications in information security . Recent Article Trends highlight his focus on control theory (e.g., neural network-based tracking control, H∞ fault detection) and network science (e.g., pinning synchronization, spreader identification). His 2024 work also includes robotics (object-driven navigation) and point cloud segmentation via interactive frameworks. Advising and Grants are not explicitly mentioned, but his extensive co-authorship network suggests mentorship roles. Funding details remain absent in the provided data. Labs and Teams : Collaborated with teams working on TCP/AQM systems , image encryption , and metabolic network reconstruction (e.g., 2018 work on Eriocheir sinensis).

W. Stephen McNeilView profile

Associate Professor

• Chemistry Education
• Chemical Bonding
• Active Learning
• +3 more

Dr. W. Stephen McNeil is an Associate Professor in the Department of Chemistry at the University of British Columbia Okanagan Campus . His primary academic focus lies in Chemistry Education Research , where he investigates alternative conceptions in advanced chemical bonding models and develops innovative active/collaborative learning strategies. PhD in Chemistry from University of British Columbia (1995) BSc in Chemistry from University of British Columbia (1991) His research addresses two core areas: (1) identifying student alternative conceptions in chemical bonding theories through qualitative interviews, and (2) assessing the effectiveness of flipped-classroom methods on affective learning outcomes. He has developed educational frameworks integrating Johnstone’s Triangle and United Nations Sustainable Development Goals into introductory chemistry curricula. Dr. McNeil has received multiple teaching excellence awards including the 3M National Teaching Fellow (2025) and Chemical Institute of Canada Award for Chemistry Education (2019) . He actively mentors students in discipline-based educational research, emphasizing research design, theoretical frameworks, and pedagogical dissemination. Professional affiliations include serving as Past-Chair of the Chemistry Education Division at the Chemical Institute of Canada. His outreach work connects chemistry concepts to interdisciplinary contexts , including Indigenous knowledge systems and environmental sustainability.

• Agricultural Economics
• Food Security
• Commodity Markets
• +4 more

Oleg Nivievskyi is a prominent agricultural economist with dual institutional affiliations, primarily at Kyiv School of Economics (90%) and secondarily at the School of Economics, University of Queensland (10%). His research focuses on agricultural economics, food security, and commodity markets with particular emphasis on Ukraine and the Black Sea region. He holds a terminal degree from Georg-August-Universität Göttingen obtained in 2010. Dr. Nivievskyi's research interests span agricultural policy analysis, spatial price transmission, crop rotation economics, and the economic impacts of conflict on agricultural systems. His recent work has been dominated by studies examining the global ramifications of Russia's invasion of Ukraine on agricultural markets, food security, and trade patterns. He specializes in quantitative analysis of market dynamics, policy impacts, and agricultural productivity, often employing sophisticated modeling techniques including spatial price equilibrium modeling and machine learning applications. His publication record reveals a strong focus on the intersection of agricultural economics and geopolitical events, particularly the war in Ukraine. The research trends indicate increasing sophistication in modeling approaches, moving from traditional agricultural economics analyses to more complex network equilibrium models that account for wartime disruptions to global food systems. His work spans both theoretical economic modeling and practical policy analysis, with significant attention to Ukraine's agricultural sector and its role in global food security. Dr. Nivievskyi maintains active research collaborations across multiple institutions, including frequent co-authorship with researchers from the University of Göttingen, World Bank, and various Ukrainian research entities. His work appears in leading agricultural economics journals and has been cited by numerous researchers studying commodity markets, food security, and the economic impacts of conflict. While specific details about his teaching responsibilities and graduate student supervision aren't explicitly documented in the provided materials, his extensive publication record and institutional affiliations suggest active engagement in academic mentoring and research leadership. His work has received support from major international organizations including the World Bank and International Agricultural Trade Research Consortium.

Sebastian WallotView profile

Professor

• Nonlinear Dynamics in Psychology
• Methodology and Evaluation Research
• Reading Processes and Comprehension
• +7 more

Sebastian Wallot is a Professor of Psychology at Leuphana University of Lüneburg, Germany, specializing in Methodology and Evaluation Research. His academic position centers on developing and applying advanced analytical methods to psychological phenomena, particularly focusing on nonlinear dynamics and time series analysis. Wallot maintains an active research profile with 90 publications spanning from 2011 to 2025, demonstrating consistent scholarly productivity across multiple domains of psychological science. Wallot's research interests bridge complex systems theory with empirical psychological research. He has developed significant expertise in recurrence quantification analysis (RQA) and its applications to diverse psychological phenomena including reading processes, joint action coordination, and psychophysiological measures. His work demonstrates how nonlinear dynamics can reveal patterns in human cognition and behavior that traditional linear methods might miss. Wallot approaches psychological research from a complex systems perspective, emphasizing the interconnectedness of cognitive, physiological, and social processes across multiple timescales. His publication record shows a clear trajectory from foundational work on reading processes and eye movement dynamics toward increasingly interdisciplinary applications in sports science, music cognition, developmental psychology, and occupational health. Recent publications highlight methodological innovations in analyzing time series data of unequal length, multivariate approaches to leader-follower relationships, and applications of nonlinear methods to practical problems in sports medicine and employee recovery. Wallot leads several significant research projects including 'The role of (non-)synchronous coordination and its quantification in joint action,' 'Regularities in Reading Times,' and the prestigious Heisenberg Professorship project 'Quantifying nonlinear dynamics in psychological data.' His collaborative work spans multiple institutions and disciplines, as evidenced by his co-authorship on the MusicLab Copenhagen Dataset and various cross-institutional studies in sports medicine and developmental psychology.

• Complex Systems
• Computational Physics
• Network Theory
• +3 more

Adam Landsberg is a Professor of Physics at the W.M. Keck Science Department, affiliated with Claremont McKenna College, Pitzer College, and Scripps College. His research focuses on mathematical and computational modeling of complex systems, spanning interdisciplinary domains such as opinion dynamics, network theory, nonlinear dynamics, and combinatorial games. Educated at Princeton University (A.B. in Physics) and U.C. Berkeley (Ph.D. in Physics) Former Visiting Assistant Professor at Haverford College Research collaborations with institutions including Cornell University and U.C. Berkeley His recent publications highlight trends in modeling cultural dissemination, synchronization in superconducting systems, and nonlinear dynamics in combinatorial games. He frequently collaborates with students, as indicated by student co-authors in multiple papers. While no explicit scientific awards are listed, his contributions to research are evident through extensive publications in journals like CHAOS, Physical Review Letters, and PLoS One. His work bridges physics, mathematics, and computational science, with applications in social systems, neuroscience, and economic models.

• Dutch Language
• Estonian Language
• Germanic Languages
• +7 more

Anne Tamm is an Associate Professor in the Department of Dutch Studies at Károli Gáspár University of the Reformed Church in Hungary, where she has been teaching since 2013. She is affiliated with the Institute for German and Dutch-speaking Cultures within the Faculty of Humanities and Social Sciences. Her academic career spans multiple institutions including the University of Tartu, University of Florence, Johns Hopkins University, and Central European University, where she has held various teaching and research positions. Dr. Tamm's research focuses on linguistic typology, language and cognition, with particular expertise in Estonian, Dutch, Germanic, and Finnic languages. Her work examines cross-categorial phenomena, evidentiality, aspectual systems, and partitive constructions across languages. She has made significant contributions to understanding how cognitive and social factors influence grammatical structures, particularly in Uralic languages. Her research integrates theoretical linguistics with experimental approaches to explore how language structure relates to cognitive processing. The most recent publications reveal a consistent research trajectory examining scalar properties across grammatical categories, the relationship between evidentiality and aspect, and how social cognitive factors shape linguistic complexity. Her work demonstrates a sophisticated integration of typological, cognitive, and functional approaches to linguistic analysis, with particular attention to Uralic languages and their comparison with Germanic systems. Scientific Awards and Distinctions: KRE BTK Research Project Award (2018-2019) Publication Award from KRE BTK (2016) Honorary Alumunus from University of Tartu (2016) Research Project Award for 'Evidential and Generic Issues of Social Cognitive and Developmental Linguistics' (2012) OTKA PD 73826 Cross-Categorial Case research grant (2009-2010) Dr. Tamm has supervised numerous doctoral students and served as an opponent in many doctoral defenses. She has participated in significant research projects including the Dutch Science Fund NWO's Internationalization project 'Partitives in Europe' (2017-2020), Hungarian-Estonian bilateral researcher exchange projects (2016-2021), and the Cambridge University Press project 'Uralic Syntax' (2016). She has also contributed to Routledge's 'Essential Grammar of Estonian' and edited volumes on negation in Uralic languages. Her international scholarly engagement is extensive, with guest professorships at the University of Amsterdam, University of Groningen, Johns Hopkins University, and University of Florence. She has organized numerous international conferences and workshops on Uralic syntax, negation, and typology, demonstrating her leadership in the field of comparative linguistics.

• Machine Learning
• Deep Learning
• Data Standardization
• +6 more

Tengxiang Su serves as a Postdoctoral Research Associate at Cardiff Business School, Cardiff University. He holds a PhD in Computer Engineering from Cardiff University's School of Engineering and an MSc degree from University College London (UCL). As a professional member of BCS (The Chartered Institute for IT), he contributes to advancing AI applications in construction and real estate domains. His research spans multiple AI disciplines with emphasis on machine learning integration with Building Information Modeling (BIM) systems. Key interest areas include data standardization for property valuation, knowledge graph construction through natural language processing, digital twin synchronization using LiDAR technology, and LLM fine-tuning for domain-specific applications. His work consistently bridges theoretical AI advancements with practical construction industry challenges. Recent publications demonstrate a clear trajectory toward automated valuation models and AI uncertainty mitigation in the Architecture, Engineering and Construction (AEC) sector. His 2022-2024 works particularly focus on damage assessment through digital twins and autonomous knowledge mining, showing increasing sophistication in handling complex construction data. Currently engaged in a Knowledge Transfer Partnership project (2023-2025) titled 'Data-driven strategic decision making in charity marketing' between Cerebra and Cardiff University, this work was recognized by Welsh Government for the KTP 50 Years Event (March 20, 2025). The project represents his expanding application of AI methodologies beyond traditional construction domains into nonprofit sector analytics. His technical expertise manifests across multiple platforms including GitHub where he maintains repositories related to time-series prediction (PM2.5 pollution modeling using LSTM networks) and NLP sentiment analysis, demonstrating practical implementation skills alongside theoretical research.

Svetlana GurevichView profile

Professor

• Nonlinear Physics
• Pattern Formation
• Theoretical Physics
• +8 more

Prof. Dr. Svetlana Gurevich is a faculty member and head of the Gurevich research group at the Institute of Theoretical Physics, University of Münster. Her research is centered on nonlinear physics, focusing on pattern formation, self-organization, and complex dynamical systems, with applications in laser physics and thin-film dynamics. Her primary research interests include nonlinear dynamics, pattern formation, dissipative solitons, time-delayed feedback systems, and optical cavity physics . She investigates the formation and stability of localized structures such as cavity solitons and light bullets in semiconductor lasers and microresonators, often using models like the Ginzburg-Landau and Swift-Hohenberg equations. Her work bridges theoretical modeling with physical applications in photonics and soft matter. The analysis of her recent publications reveals a strong trend in nonlinear optical systems with time delay . Her research frequently explores the dynamics of mode-locked lasers, frequency combs, and temporal localized states, examining instabilities, bifurcations, and control mechanisms induced by delayed feedback. She also applies her expertise to problems in thin-film hydrodynamics and wetting, demonstrating a broad impact across theoretical physics. She actively supervises students and offers thesis projects in her research areas, fostering the next generation of physicists. Her collaborative work involves numerous co-authors from various institutions, highlighting her active role in the scientific community. Her work is supported by ongoing research projects, including studies on delay-induced dynamics in optical systems and structure formation in self-assembling systems, indicating sustained funding and research activity.

Dariusz KowalskiView profile

Professor

• Distributed Computing
• Theoretical Computer Science
• Wireless Networks
• +3 more

Dariusz Kowalski serves as Professor in the School of Computer and Cyber Sciences and Department of Computer & Cyber Sciences, with concurrent administrative appointment in The Graduate School. His teaching portfolio includes advanced courses like CSCI 8940 (Dissertation Research) and CSCI 6900 (Introduction to Research), alongside foundational programming instruction. Academic credentials: Ph.D. in Computer Science, University of Warsaw (2001) Research centers on theoretical distributed computing, specializing in algorithmic solutions for anonymous dynamic networks, fault-tolerant consensus mechanisms, and group testing frameworks. His work addresses core challenges in communication complexity under adversarial conditions and constrained network topologies, with particular emphasis on congestion management and information dissemination in wireless environments. Analysis of his 2022 publications reveals a cohesive research trajectory focused on optimizing distributed computations in non-ideal network conditions. Key thematic threads include leaderless computation models, adversarial query responses in group testing, and weighted interference frameworks for wireless networks—collectively advancing theoretical foundations for resilient distributed systems. No scientific awards were documented in the source material. Professor Kowalski contributes significantly to academic governance through committee service including Graduate School Council (2020-2022), Promotion & Tenure committee (2020-2022), and ongoing Faculty Rights & Responsibilities Committee membership (2021-present). His professional service encompasses editorial duties for Journal of Computer and System Sciences (Associate Editor since 2018) and conference committee participation including PODC 2022. Research infrastructure details including laboratories, collaborative teams, and future project directions were not specified in the provided text.