Find Academic Supervisors

• Bioeconomy
• Renewable Energy
• Biomass Production and Utilization
• +5 more

Prof. Mariusz Jerzy Stolarski is a full-time faculty member at the University of Warmia and Mazury in Olsztyn, affiliated with the Department of Genetics, Plant Breeding and Biomaterial Engineering within the Faculty of Agriculture and Forestry. His research focuses on bioeconomy, renewable energy systems, and sustainable biomass production. Scientific discipline: Agriculture and horticulture ORCID: 0000-0003-0712-9678 Email: mariusz.stolarski@uwm.edu.pl Phone: +48 89 523 48 38 His research explores biomass valorization, biofuel processing, and environmental efficiency assessments across agricultural and forestry systems. Recent work examines supercritical CO2 extraction effects on biomass stability, intercropping systems in organic farming, and economic viability of multi-purpose energy crops like industrial hemp and Virginia fanpetals. Scientific indicators highlight significant contributions: 79/96 publications (WoS/Scopus), 878/1141 citations (WoS/Scopus), H-index 21/24, and Google Scholar H-index 29 with 3089 citations. He has promoted 4 doctors and currently supervises 2 doctoral students.

Gloria RobertsView profile

Research Fellow

• Neuroscience
• Psychiatry
• Bipolar Disorder
• +3 more

Dr. Gloria Roberts is a Research Fellow at the Black Dog Institute, affiliated with the University of New South Wales' Faculty of Medicine, School of Psychiatry. Her research focuses on identifying predictors of bipolar disorder development in high-risk populations, with particular emphasis on neural mechanisms of executive functioning and emotional processing. Location: Black Dog Institute, Hospital Road, Prince of Wales Hospital, Randwick NSW 2031 Contact: +61 2 9382 8324 | ORCID: https://orcid.org/0000-0002-1966-5120 Education Background: B.Sc in Applied Psychology (University College Cork, Ireland, 2002) M.Sc in Neuropharmacology (National University of Ireland Galway, Ireland, 2003) Diploma in Statistics (Trinity College Dublin, Ireland, 2006) PhD in Neuroscience (Trinity College Dublin, Ireland, 2008) Dr. Roberts' research program centers on the neural basis of emotional dysregulation characteristic of mood disorders, employing structural and functional Magnetic Resonance Imaging as her primary research tool. Her work integrates advanced neuroimaging analysis techniques including diffusion tensor imaging tractography, dynamic causal modeling, graph theory, and machine learning approaches. She maintains active collaborations with Queensland Institute of Medical Research (Brisbane), Neuroscience Research Australia (Sydney), and the Centre for Healthy Brain Ageing (Sydney). Analysis of Dr. Roberts' publication record (94 journal articles, 2 book chapters, 25 conference papers) reveals a consistent research trajectory focused on neurocognitive patterns in bipolar disorder. Her recent work increasingly incorporates machine learning techniques to identify predictive biomarkers, with a growing emphasis on longitudinal studies tracking high-risk populations. The interdisciplinary nature of her research bridges neuroscience, psychiatry, and computational methods to address fundamental questions about mood disorder development. Scientific Contributions: Extensive publication record across multiple formats (journal articles, book chapters, conference presentations) Development of innovative neuroimaging analysis techniques for bipolar disorder research Establishment of multi-institutional collaborations across Australia Integration of machine learning approaches with traditional neuroimaging methods Dr. Roberts actively mentors junior researchers and contributes to the broader scientific community through peer review activities and participation in research networks focused on mood disorders. Her work has significant implications for early intervention strategies and the development of novel therapeutic approaches for bipolar disorder.

• Phenomenology
• Continental Philosophy
• Philosophical Theory
• +3 more

Emanuele Caminada is a tenure-track Lecturer at the Higher Institute for Philosophy, KU Leuven. He is affiliated with the Husserl Archive: Center for Phenomenology and Continental Philosophy (OE), located at Cardinal Mercierplein 2 - bus 3200 in Leuven. His research focuses on Phenomenology and Continental Philosophy, with particular emphasis on Husserlian studies and related theoretical frameworks. Education details are linked via his ORCID profile . His academic work contributes to philosophical inquiries into existential themes, perception, and critical theory. No specific grants, awards, or advised students are listed in the provided information. He is part of the Husserl Archive team, a specialized research center dedicated to advancing Phenomenological and Continental philosophical scholarship.

Daniel TubbenhauerView profile

Research Professor

• Categorical Representation Theory
• 2-Representation Theory
• Modular Representation Theory
• +6 more

Dr. Daniel Tubbenhauer is an ARC Future Fellow at the University of Sydney's School of Mathematics and Statistics, specializing in categorical representation theory, 2-representation theory, and their applications to topology, cryptography, and machine learning. His research bridges algebra, category theory, and low-dimensional topology, with a focus on modular representation theory and diagrammatic algebra. Education: PhD in Mathematics (2013), supported by extensive postdoctoral research globally. Research Interests: He explores categorical structures in representation theory, including categorification of quantum groups, link homologies, and applications in cryptography. His work emphasizes diagrammatic methods and computational approaches to algebraic problems. Publications: Over 30 peer-reviewed articles, including foundational work on web categories, Soergel bimodules, and applications of representation theory to machine learning. Recent projects analyze growth rates in tensor powers and fractal behavior in algebraic structures. Awards: Australian Research Council Future Fellowship (2023), supporting his research on categorical representation theory. Teaching & Supervision: Taught courses on quantum topology, category theory, and representation theory. Current student: Daniel Collison (PhD). Advises on projects linking representation theory to AI and cryptography. Labs/Teams: Collaborates with global networks in algebraic topology and categorification, including projects at the Sydney Mathematical Research Institute. Maintains an active YouTube channel ( VisualMath ) for outreach.

Colin AllisonView profile

Research Professor

• Multi-User Virtual Worlds
• Distributed Systems
• Computer Networks
• +5 more

Dr Colin Allison is an Honorary Research Professor at the University of St Andrews' School of Computer Science, specializing in Multi-User Virtual Worlds (Metaverses), Distributed Systems, Computer Networks, and Quality of Service (QoS). He holds a PhD in Computer Science from the University of St Andrews, an M.Sc. in Computing from the University of Dundee, and an M.A. in Sociology from the University of Edinburgh. His research focuses on immersive learning environments, virtual world infrastructure, and educational technologies. Notable projects include leading the Immersive Learning Research Network (iLRN), managing Open Virtual Worlds initiatives, and investigating Quality of Service in distributed systems. Dr. Allison has organized international conferences and published extensively on virtual reality applications in education and cultural heritage. Key contributions include advancing scalable learning environments like Finesse, exploring video fingerprinting for digital asset management, and investigating covert channels in internet protocols. He has collaborated on interdisciplinary projects such as LAVA (virtual archaeology) and the Global Smart Spaces initiative. Dr. Allison has secured grants for projects like the European Learning Grid Infrastructure (ELeGI) and has served as Principal Investigator for initiatives such as Interface and the Scottish Metropolis Area Networks project. His work bridges academic research with practical applications in education, technology, and heritage preservation. He has advised on multiple research projects and has been a keynote speaker at conferences on internet security, immersive education, and virtual worlds.

Siegrid LöwelView profile

Professor

• Systems Neuroscience
• Neural Plasticity
• Cortical Development
• +7 more

Siegrid Löwel is a Full Professor of Systems Neuroscience at the University of Göttingen, affiliated with the Department of Systems Neuroscience within the Johann-Friedrich-Blumenbach-Institute for Zoology and Anthropology. She is also a Board Member of the Göttingen Campus Institute for Dynamics of Biological Networks since 2021, highlighting her leadership in interdisciplinary neuroscience research. Her educational background includes a Dr. phil. nat. from the University of Frankfurt am Main, completed under Prof. Wolf Singer at the Max Planck Institute for Brain Research. Her career includes professorships at the University of Jena (2005–2010), a guest professorship at Magdeburg, and a research associate professorship at the University of California, San Francisco. Siegrid Löwel's research focuses on the development and plasticity of neuronal circuits in the mammalian cortex. Her lab employs optical and 2-photon imaging, electrophysiology, and viral gene knockdown to study how experience and learning shape neural networks. Her work has pivotal implications for brain regeneration and rehabilitation after injury or disease. She was among the first to demonstrate that correlated neural activity underlies long-range cortical circuit development—famously summarized as 'neurons that fire together, wire together.' The recent publications reflect a strong focus on structural and functional cortical plasticity, particularly in the visual system. Themes include silent synapses, critical period regulation, optogenetic interventions for blindness, and the impact of environmental enrichment and exercise on neural plasticity. These studies span molecular, cellular, and systems levels, contributing to both basic neuroscience and translational applications. Scientific awards and recognitions include: Hertie Excellence Program Scholarship in Neurosciences (2004–2005) Dorothea Erxleben Guest Professorship, University of Magdeburg (2003–2004) Löwel leads an active research group and is affiliated with the Göttingen Graduate Center for Neurosciences (GGNB) in multiple programs, including Systems Neuroscience and Sensory and Motor Neuroscience. She has secured long-term research support through institutional roles and collaborative networks. While specific grant details are not listed, her sustained publication record and leadership positions indicate robust funding and research activity. Her lab continues to explore mechanisms of neural plasticity with potential clinical applications in stroke recovery, amblyopia, and neurodegenerative conditions. She is associated with the research group homepage: http://systemsneuroscience.uni-goettingen.de .

Patrick DesrosiersView profile

Adjunct Professor

• Dimensionality Reduction
• Dynamical Systems
• Mathematical and Computational Neuroscience
• +8 more

Patrick Desrosiers serves as an Adjunct Professor in the Department of Physics, Physical Engineering and Optics within Université Laval's Faculty of Science and Engineering, while conducting neuroscience research at the CERVO Brain Research Center. He co-directs Dynamica, a multidisciplinary complex systems research group, and participates in UNIQUE (neuroscience-AI integration) and CIMMUL (mathematical modeling applications). His academic training spans physics and mathematics at Université Laval, the University of Melbourne, and CEA-Saclay. Dr. Desrosiers' research centers on mathematical and computational neuroscience , with signature contributions in dimensionality reduction and network resilience analysis . His work bridges biological and artificial neural networks , zebrafish brain mapping , and neurovascular coupling using advanced techniques from spectral graph theory , random matrix theory , and dynamical systems . Current investigations focus on neural decoding under chronic stress and structural-functional relationships in brain networks. Analysis of his 2023-2025 publications reveals three dominant trajectories: (1) Low-dimensional representations for predicting cognitive decline and neural dynamics, (2) Network reconstruction methodologies applied to neuroscience and biodiversity, and (3) Development of computational tools like NeuroTorch for neural data analysis. His work consistently integrates mathematical rigor with biological relevance across species and scales. His recognition includes: Professeur étoile prize for exceptional teaching (Faculty of Science and Engineering, Université Laval, 2018) As Dynamica co-director, he mentors a research team comprising Antoine Légaré, Arthur Légaré, Benjamin Claveau, Jordan Charest, Marziyeh Pourmousavi, Pierre-Luc Larouche, Vincent Savard, Vincent Thibeault, and Zahra Yazdani. His collaborative framework connects physics, mathematics, and neuroscience to address fundamental questions in neural network organization, with funding evident through sustained publication output and lab operations. Dynamica Lab ( https://dynamicalab.github.io/ ) serves as the operational hub for his interdisciplinary research, maintaining active collaboration with CERVO Brain Research Center and international institutions.

Sven RaumView profile

Professor

• Operator Alge
• Group Theory
• Quantum Groups
• +4 more

Prof. Dr. Sven Raum is Chair of Algebra at the University of Potsdam , Germany, within the Institute of Mathematics . His research focuses on operator algebras and their interactions with groups and group-like structures, including Hecke algebras, groupoids, quantum groups, and tensor categories. He leads the research group GOAT (Gruppen- und Operatoralgebren-Treffen), which includes postdocs Sanaz Pooya and Jonathan Taylor.

• Information Security
• Privacy
• Pervasive Computing
• +5 more

Tuomas Aura is a Professor at the Department of Computer Science , Aalto University , and a member of the Helsinki Institute for Information Technology (HIIT) and the Helsinki-Aalto Institute for Cybersecurity (HAIC) . His expertise spans information security , privacy , pervasive computing , and communications . Research Trends: His recent work focuses on securing Kubernetes clusters , TLS identity binding , SIM provisioning protocols , and IoT authentication , with a strong emphasis on network security and cryptographic protocols . Key sub-fields include microservice connectivity , threat modeling , and EAP-based authentication . Publications: His 2025 work on Kubernetes misconfigurations and TLS identity binding addresses critical cloud and protocol vulnerabilities. Earlier studies (2024-2020) explore SIM transparency, HTTP/2 security, and formal verification of device-pairing flaws, reflecting a consistent focus on IoT security and network protocols .

Connie J. MulliganView profile

Professor

• Molecular Genetics
• Epigenetics
• Human Health and Disease
• +7 more

Connie J. Mulligan is a Professor in the Department of Anthropology at the University of Florida (UF) , with affiliations to the Center for African Studies and the Genetics Institute. She has led a distinguished research program since 2005, focusing on molecular genetics, epigenetics, and biocultural approaches to health disparities. Her work bridges evolutionary anthropology and public health, supported by continuous NSF grants since 2005. Educational Background: Ph.D. in Molecular Biophysics and Biochemistry from Yale University (1990) B.S. in Honors Biology and Chemistry from University of Illinois, Champaign-Urbana (1983) Mulligan's research investigates how childhood adversity , maternal stress , and racial discrimination interact with genetic/epigenetic factors to influence health outcomes. Her team studies populations in Tallahassee (hypertension in African Americans), DRC (intergenerational stress effects), and Jordan (Syrian refugee resilience). She pioneered biocultural frameworks showing gene-environment interactions in diseases. Her 15 most recent publications span three major research themes: (1) epigenetic mechanisms linking maternal stress to neonatal health (2016-2020), (2) genetic ancestry analysis in African/Ethiopian populations (2009-2011), and (3) molecular anthropology of prehistoric migrations (2008-2009). Notably, she discovered gene-specific DNA methylation patterns in war-affected DRC mothers and Science -featured refugee resilience research. Scientific Recognition: UF Term Professorship (2017-2018) President of American Association of Anthropological Genetics (2017-2018) Senior Editor at American Journal of Physical Anthropology Workshop Organizer on Social & Behavioral Epigenetics (2014-2019) As an advisor, she has mentored 10 PhD candidates (as chair) , 9 Masters students, and >50 undergraduates (>200 semesters total). Her lab collaborates with Yale , Hashemite University , and Washington University , focusing on trauma epigenetics and global health research. Her work appears in Nature , Science , and PLoS ONE , with media coverage in National Geographic , The Atlantic , and NPR . She co-organized NSF workshops on data sharing in biological anthropology and serves on editorial boards of major journals.

• Human-Machine Interaction
• Usability Testing
• User Experience (UX)
• +5 more

Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users

Kasey StantonView profile

Assistant Professor

• Transdiagnostic Psychopathology
• Mood Disorders
• Personality Assessment
• +6 more

Kasey Stanton, Ph.D., serves as an Assistant Professor of Clinical Psychology in the Department of Psychology at the University of Wyoming, where her research bridges transdiagnostic frameworks with clinical assessment innovation. Her work addresses critical gaps in diagnostic specificity and treatment development through dimensional psychopathology models. Education Clinical Psychology Internship, Alpert Medical School of Brown University Ph.D. in Psychology, University of Notre Dame B.S. in Psychology, Montana State University Billings A.S., Miles Community College Research Program Dr. Stanton's laboratory pioneers transdiagnostic approaches to mood and personality disorders, with particular emphasis on bipolar spectrum symptoms and externalizing behaviors. Her methodological expertise in psychometrics drives innovations in measure development and factor analytic techniques, directly informing clinical practice through improved diagnostic frameworks and assessment tools that capture symptom complexity beyond categorical boundaries. Publication Themes Her 2023-2024 publications reveal three convergent research strands: (1) factor analytic investigations of mood dysregulation as a transdiagnostic mechanism, (2) community-level analyses of personality disorder stigma and diagnostic accuracy, and (3) methodological advancements in psychometric modeling that address construct heterogeneity. These works collectively challenge traditional diagnostic boundaries while providing empirical foundations for dimensional assessment systems. Academic Engagement Teaching: PSYC 2000 (Research Methods), PSYC 4390 (Personality Science), PSYC 4500 (Introduction to Clinical Psychology) Student Recruitment: Actively reviewing graduate applications for Fall 2025 admission (deadline December 1, 2024) Open Science: Maintaining preprints and research materials via Open Science Framework (https://osf.io/bczyx/)

• Image Analysis
• Artificial Intelligence
• Deep Learning
• +5 more

Joakim Lindblad is a Professor at the Department of Information Technology, Uppsala University , and holds affiliated roles as Senior Research Associate at the Mathematical Institute of the Serbian Academy of Sciences and Arts, and Head of Research at Topgolf Sweden AB. With over two decades of expertise in image analysis and machine learning , his work bridges computational methods with biomedical applications. Key affiliations: Uppsala University, Serbian Academy of Sciences, Topgolf Sweden Specializations: Deep Learning, Multimodal Image Registration, Quantitative Microscopy His research focuses on reliable image processing frameworks that integrate intensity and spatial information , particularly for biomedical applications . Recent publications highlight innovations in autofluorescence-based cancer detection , self-supervised one-class learning for sparse instance identification, and rotation-equivariant CNNs for robust analysis of cytology images. Recent article trends demonstrate expertise in multimodal image analysis (2024: 3 papers), oral cancer detection (2025: 2 papers), and multiscale biomedical imaging . His 2025 work on the Uppsala Storytelling Dataset introduces novel frameworks for multimodal dataset creation in AI research. While no scientific awards are explicitly mentioned, his extensive publication record (2000-2025) across top venues like Pattern Recognition , PLOS ONE , and IEEE Transactions indicates significant academic impact. His methodological contributions span stochastic distance transforms , fuzzy set defuzzification , and multimodal image registration techniques. Collaborative work with researchers like Nataša Sladoje and interdisciplinary teams has produced innovations in automated cytology analysis , TEM image enhancement , and AI-driven medical diagnostics . His 2021-2022 projects introduced contrastive learning approaches for multimodal image registration and explainable AI frameworks for infant engagement analysis.

• Network engineering
• Multimedia Communication
• Distributed Multimedia Systems
• +4 more

Prof. Hermann Hellwagner is a Full Professor at the Department of Information Technology, University of Klagenfurt. He has held roles such as Vice President (Natural and Technical Sciences) at the Austrian Science Fund (FWF) and Vice Dean of the Faculty of Technical Sciences. His research focuses on multimedia communication, network engineering, and future internet architectures. Notable projects include work on adaptive streaming, edge computing, and drone networks. He holds a Ph.D. in Systolic Architectures from the University of Linz (1988). Research interests span distributed multimedia systems, information-centric networking (ICN), and optimizing video streaming quality-of-experience (QoE). Recent work emphasizes edge computing solutions for low-latency streaming and dynamic codec adaptation. His contributions include frameworks like ALPHAS and MEDUSA for bitrate optimization, and studies on point cloud streaming in augmented reality. Publications (2021–2025) highlight advancements in edge-assisted streaming, hybrid P2P-CDN architectures, and transcoding techniques. His work often bridges theoretical models with real-world implementations, addressing challenges in latency, cost, and device adaptability. Current projects involve 6DoF video streaming and multi-robot system optimization. Labs/Teams: Part of the Institute of Information Technology (ITEC), Klagenfurt. Collaborates on EU-funded projects and industry partnerships in 5G edge computing and drone networks. Active in standards groups for HTTP adaptive streaming protocols.

• VLSI CAD
• Low-power IC Design
• Mixed-signal IC Design
• +5 more

Riadul Islam serves as an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), maintaining his primary office in room 316 of the Information Technology and Engineering (ITE) Building. His academic appointment focuses on hardware design and verification within the institution's engineering framework. His educational qualifications include: Ph.D. in Computer Engineering from UCSC (2017) M.A.Sc. in Electrical and Computer Engineering from Concordia University, Montreal (2011) B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (2007) Professor Islam's research centers on VLSI CAD tools and low-power digital/mixed-signal IC design , with significant contributions to current-mode clock networks, vehicular security systems, and error-robust circuit architectures. His work increasingly integrates machine learning for design automation while exploring neuromorphic computing applications and secure hardware implementations. This multidisciplinary approach bridges traditional IC design with modern AI-driven optimization techniques. Analysis of his 2023-2025 publications reveals three dominant research thrusts: (1) Machine learning applications in early-stage Design Rule Checking (DRC) prediction and clock network optimization, (2) Graph-based intrusion detection systems for automotive networks (particularly CAN bus security), and (3) Event-based vision systems and neuromorphic computing architectures. These areas demonstrate consistent innovation in merging hardware design with AI/ML methodologies for enhanced system reliability and efficiency. He directs the UMBC VLSI and SoC Research Group , which develops energy-efficient clocking networks, secure vehicular communication protocols, and compute-in-memory architectures. The lab maintains active collaboration with industry partners on hardware security and neuromorphic computing initiatives while supporting graduate student research in cutting-edge IC design methodologies.