Find Academic Supervisors

Atsushi UrakawaView profile

Professor

• Heterogeneous Catalysis
• In situ/operando Spectroscopy
• Reaction Engineering
• +7 more

Prof. Atsushi Urakawa is a Full Professor in the Department of Chemical Engineering at the Faculty of Applied Sciences, Delft University of Technology (TU Delft) . He leads the Urakawa Group , which focuses on developing sustainable heterogeneous catalytic processes with minimal environmental impact. PhD, ETH Zurich (2006) MSc, TU Delft BSc, Kyushu University, Japan His research is centered on heterogeneous catalysis , employing in situ/operando spectroscopy and reaction engineering to understand catalytic mechanisms. Key research themes include CO₂ conversion to chemicals , methane activation , hydrogen production , and environmental catalysis (NOx abatement) . The group also pioneers advanced in situ/operando tools for studying solid-gas and solid-liquid interfaces at the reactor scale. The recent publications reflect a strong focus on CO₂ hydrogenation under high pressure, design of bimetallic and supported catalysts , and mechanistic elucidation using operando techniques. The work bridges fundamental understanding with industrial sustainability. Scientific Awards: Fellow of the Royal Society of Chemistry (2016) JSPS Prize (2020) The Japan Academy Medal (2021) Advising: Prof. Urakawa supervises PhD and postdoctoral researchers, including Nat Phongprueksathat , George Tierney , and Gerben-Jan Hooijer . His group collaborates with industrial partners such as Toyota on carbon capture and reduction (CCR) projects. While specific grants are not detailed, his research is clearly supported by high-impact publications and international recognition. Labs & Teams: The Urakawa Group is embedded within the Catalysis Engineering section at TU Delft, fostering interdisciplinary research at the intersection of materials science, catalysis, and process engineering.

Stefan TreueView profile

Professor

• Cognitive Neuroscience
• Visual Perception
• Attention
• +7 more

Stefan Treue is a Professor and Director at the German Primate Center (DPZ) in Göttingen, Germany, where he heads the Cognitive Neuroscience Laboratory. He is affiliated with the Department of Cognitive Neurosciences and contributes to the Göttingen Graduate School for Neurosciences (GGNB) in programs including Neurosciences (IMPRS), Sensory and Motor Neuroscience, Systems Neuroscience, and Theoretical and Computational Neuroscience. His research focuses on the neural basis of visual perception, particularly how attention modulates sensory processing in the primate brain. Using electrophysiological recordings in macaque monkeys, human psychophysics, and functional brain imaging, his lab investigates attentional mechanisms in cortical area MT, especially in motion processing and perceptual accuracy. Key themes include attentional gain, receptive field dynamics, saccade-locked attention shifts, and multifocal attention. The recent publications reflect a consistent focus on attentional modulation in visual cortex, with a strong emphasis on neurophysiological and behavioral evidence from non-human primates. His work bridges cognitive theory and neural mechanisms, contributing significantly to systems and computational neuroscience. Scientific Awards: None explicitly mentioned in the text. Advising and Grants: Prof. Treue mentors students through the GGNB and IMPRS programs, indicating active graduate student supervision. While specific grants are not listed, his long-standing research program and high-impact publications suggest sustained funding from major research agencies. Labs and Teams: He leads the Cognitive Neuroscience Laboratory at DPZ, a multidisciplinary team employing electrophysiology, psychophysics, and theoretical modeling to study attention and perception in primates.

Hans RenataView profile

Professor

• Enzyme Engineering
• Organic Chemistry
• Drug Discovery
• +3 more

Hans Renata is a Professor of Chemistry and Associate Chair for Graduate Studies at Rice University's Department of Chemistry. Previously, he served as an Associate Professor at The Scripps Research Institute (Florida) before joining Rice in 2022. His research focuses on enzymatic solutions for challenging organic reactions, particularly C–H functionalization, and their applications in drug discovery and natural product synthesis. Renata holds a B.A. from Columbia University (2008) and a Ph.D. from The Scripps Research Institute (2013). His postdoctoral work under Frances H. Arnold at Caltech further honed his expertise in enzyme engineering. His interdisciplinary lab at Rice integrates synthetic organic chemistry, molecular biology, and medicinal chemistry. Key research themes include developing biocatalytic tools for selective chemical transformations, leveraging genome mining, and synthesizing bioactive natural products. His recent articles highlight advancements in enzyme-enabled cross-coupling reactions, RiPP natural products, and chemoenzymatic strategies for terpenoids and alkaloids. While no awards are explicitly listed, his work has driven innovations in biocatalytic synthesis. He advises students in interdisciplinary projects, and the Renata Lab collaborates widely within Rice's research ecosystem.

Wendy HuddlestonView profile

Associate Professor

• Visual Attention
• Motor Attention
• Cognitive Neuroscience
• +5 more

Wendy Huddleston is an Associate Professor in the Department of Physical Therapy at the University of Wisconsin-Milwaukee. Her research focuses on the cortical mechanisms underlying motor selection during visually guided goal-directed behavior, particularly the interaction between visual attention, motor attention, and cognitive neuroscience. She directs the Visuomotor Lab and serves as a mentor in the Rehabilitation Science and Technology graduate programs. She utilizes functional magnetic resonance imaging (fMRI) and psychophysical testing to study sensory processing for movement preparation. Her funded projects include investigations into individual differences in attentional mapping, cross-modal attention mechanisms, and the neurophysiological basis of movement variability. Collaborations extend to the Medical College of Wisconsin and the Center for Imaging Research. Huddleston's professional affiliations include the American Physical Therapy Association, Society for Neuroscience, Center for Imaging Research (MCW), and the Evidence-Based Practice Institute. Her work bridges rehabilitation science, biomechanics, and cognitive neuroscience to advance understanding of sensorimotor integration.

Benjamin GarnerView profile

Associate Professor

• Consumer Behavior
• Social Media Marketing
• Wine Tourism
• +4 more

Benjamin Garner serves as Associate Professor of Marketing in the College of Business at the University of Central Arkansas (UCA), maintaining an active research program from his office in COB 312I. His contact information includes email bgarner3@uca.edu and phone (501) 450-5329, reflecting ongoing institutional affiliation. Dr. Garner's research centers on consumer behavior in experiential marketing contexts with three primary thrusts: Social media engagement dynamics in wine tourism and farmers' markets Authenticity construction through scarcity and sustainability messaging Innovative business education pedagogy including flipped classroom methodologies Analysis of his 2021-2025 publications reveals consistent methodological emphasis on ethnographic observation and text-mining of user-generated content across platforms like Facebook, Instagram, and Twitter. His work uniquely bridges agricultural marketing contexts with digital communication strategies, particularly examining how language structures influence consumer perceptions of authenticity. No scientific awards or student advising information appears in available records. Similarly, grant funding details and laboratory affiliations remain undocumented in the provided materials, though his publication output indicates sustained research activity across multiple scholarly domains.

• Chronic lung infection in cystic fibrosis
• Vaccine development against antimicrobial-resistant pathogens
• Host-pathogen interactions
• +6 more

Professor Siobhán McClean (University College Dublin) is a leading researcher in Biomolecular and Biomedical Science with 24 years of academic experience. Her work focuses on chronic respiratory infections in cystic fibrosis patients and vaccine development against ESKAPE pathogens. Current roles: Professor (2024-present) Associate Dean for Widening Participation (2019-2023) Head of Biochemistry (2019-2022) Academic qualifications: BSc in Biochemistry, UCD PhD, Imperial College London Professional Diploma in Creativity & Innovation, UCD Research Interests: Specializing in bacterial adaptation to hypoxia in chronic infections, she leads studies on Burkholderia cepacia complex, Pseudomonas aeruginosa, and Pandoraea pulmonicola. Her team develops novel vaccine antigens through proteomic analysis of host-pathogen interactions, with recent work on TLR4 agonists and universal stress proteins. Article Trends: Recent publications focus on mRNA vaccine platforms, hypoxia-driven pathogenesis, and cross-reactive antigens for ESKAPE pathogens. Key themes include adjuvant optimization, host cell attachment mechanisms, and immune correlate analysis across bacterial/viral/parasitic agents. Scientific Awards: Principal Investigator for Marie Curie BactiVax network Coordinator of All-island Vaccine Research Alliance (AIVRT) Science Foundation Ireland grant recipient Training Leadership: Supervises 7 active PhD researchers and has trained 15 Marie Curie students across 8 countries. Her lab develops cationic nanoparticles and investigates bacterial stress responses.

• Constructive Approximation
• Radial Basis Function Networks
• Neural Networks
• +4 more

Prof. Dr. rer. nat. habil. Detlef Hauke Mache is a full Professor of Mathematics and Applied Mathematics at the TH Georg Agricola University of Applied Sciences in Bochum, Germany, within the Faculty of Electrical Engineering, Information Technology, and Industrial Engineering. Since 2003, he has held the chair for Applied Mathematics with a focus on Constructive Approximation. Education: Diploma in Mathematics and Computer Science, University of Dortmund (1988) Doctoral degree (Dr. rer. nat.) in Mathematics, University of Dortmund (1991) Habilitation (Dr. habil.) in Mathematics, University of Dortmund (1997) Research Interests: Prof. Mache's research spans Constructive Approximation Theory , emphasizing the development and analysis of approximation methods. He explores Radial Basis Function (RBF) Networks and their applications in neural networks and fuzzy logic. His work integrates theoretical foundations with practical algorithms, particularly in numerical analysis and approximation techniques. Key areas include: Neural Networks and Fuzzy Logic Systems Quasi-Interpolation Methods Orthogonal Polynomial Expansions Integral Transforms and Convolution Structures Publications and Editorial Contributions: Prof. Mache has authored over 30 peer-reviewed papers and edited several volumes in approximation theory. His research trends indicate a focus on advancing approximation methods through theoretical insights and practical applications in neural networks and computational intelligence. Scientific Awards and Honors: While no specific awards are listed, his extensive editorial roles and habilitation qualification signify recognition in his field. Teaching and Advising: He teaches courses in Higher Mathematics, Applied Mathematics, Differential Equations, and Numerical Analysis. While no specific students are named, his long-standing academic positions suggest significant contributions to graduate education. Laboratories and Teams: As a professor in the Faculty of Electrical Engineering and Information Technology, he likely collaborates with interdisciplinary teams, though no specific labs are mentioned.

Satrya Fajri PratamaView profile

Senior Lecturer

• Software Development
• Internet of Things
• Cloud Computing
• +6 more

Dr. Satrya Fajri Pratama is a Senior Lecturer in Computer Science at the University of Hertfordshire , affiliated with the School of Physics, Engineering & Computer Science and the Department of Computer Science . With professional certifications from Oracle, Microsoft, Google, AWS, Cisco, and other industry leaders, he combines academic expertise with practical industry recognition. His research focuses on software development, internet of things (IoT), cloud computing, and computational approaches to drug classification. Doctor of Philosophy (ICT) – Universiti Teknikal Malaysia Melaka Master of Science in ICT – Universiti Teknikal Malaysia Melaka Bachelor of Computer Science (Software Development) – Universiti Teknikal Malaysia Melaka His research involves descriptor selection for drug classification using advanced algorithms like the Whale Optimization Algorithm and Particle Swarm Optimization , particularly in combating Amphetamine-Type Stimulants (ATS) . Collaborative work includes ncRNA identification and QSAR modeling for biodegradation studies. Key scientific awards include certification as a Professional Technologist with the Malaysia Board of Technologists (MBOT) and recognition as an Apple Teacher with Swift Playgrounds Recognition . He holds numerous industry certifications and is a certified educator/trainer for Microsoft, Google, AWS, Oracle, and other major tech companies.

Katie GahrView profile

Researcher

• Vocational Education and Training
• Education Governance
• Comparative Education
• +3 more

Katie Gahr serves as academic staff supporting the Chair of Education Systems within the Department of Management, Technology, and Economics at ETH Zürich. Her work focuses on international vocational education and training (VET) systems, with particular emphasis on Serbia and Uzbekistan. Her research interests span Vocational Education and Training , Education Governance , Comparative Education , and Labor Market Integration . She has developed expertise in analyzing education system permeability, functional equivalence methodologies for cross-national curriculum comparison, and the role of intermediaries in public-private education partnerships. Dr. Gahr's publication record demonstrates consistent scholarly output with multiple articles in 2023-2025 in journals like Journal of Vocational Education & Training , Journal of Education Policy , and Research in Comparative and International Education . Her work shows a clear trajectory examining governance structures in VET systems, gender disparities in training programs, and methodological approaches to cross-national education comparison. Her research has practical applications in education policy implementation, particularly in transitional economies where she has conducted extensive fieldwork in Serbia and Uzbekistan. The recurring theme across her publications is understanding how education systems can be structured to better serve diverse populations and address labor market needs.

Jian KangView profile

Professor

• Biostatistics
• Bayesian Methods
• Gaussian Processes
• +11 more

Jian Kang is a Professor and Associate Chair for Research at the University of Michigan School of Public Health , specializing in Biostatistics . His work focuses on developing advanced statistical methods for large-scale biomedical data , with applications to precision medicine , neuroimaging , and genomics . Education: PhD in Biostatistics, University of Michigan (2011) MS in Mathematics (Statistics), Tsinghua University (2007) BS in Statistics, Beijing Normal University (2005) Research Interests include Bayesian nonparametric methods , deep learning for medical imaging , ultra-high-dimensional variable selection , and graphical models for network inference . His 2025-2023 publications demonstrate expertise in Bayesian hierarchical modeling , spatial statistics , and machine learning for healthcare . Scientific Awards : Michigan SPH Excellence in Research Award (2025) ICSA President's Citation Award (2024) Statistics in Biopharmaceutical Research Best Paper (2023) Best Paper in Biometrics by IBS Member (2022) Fellow, American Statistical Association (2021) Grants include NSF-IIS (2021-2025) for BCI statistical learning , NIGMS (2020-2022) for metabolomics biomarker selection , NIDA (2020-2025) for imaging data analysis , and NIMH (2014-2025) for multidimensional neuroimaging methods . Labs and Teams develop Bayesian computational tools for neuroimaging and spatial transcriptomics , collaborating with institutions like Emory University and University of North Carolina.

• Cryptography
• Computer Security
• Information Security
• +4 more

Hongjun Wu is an Associate Professor at the Division of Mathematical Sciences, School of Physical & Mathematical Sciences, Nanyang Technological University, Singapore. His research focuses on Cryptography and Computer Security , with contributions to authenticated encryption, stream ciphers, hash functions, and cryptographic vulnerabilities. Doctor of Engineering (2005-2008), Electrical Engineering, Katholieke Universiteit Leuven Master of Engineering (1998-2000) & Bachelor of Engineering (1994-1998), Electrical Engineering, National University of Singapore Research spans Lightweight Cryptography (TinyJAMBU finalist 2021), Authenticated Encryption (CAESAR winners ACORN/AEGIS), Hash Function Design (JH finalist in SHA-3), and Stream Cipher Development (HC-128 in eSTREAM). He has advised PhD students Huang Tao, Ivan Tjuawinata, Yu Haiwan, and Master students Peng Lunan. Former team members include Tao Biaoshuai, Wei Lei, and Yosua Michael Maranatha. Key publications include work on AES biclique attacks (2015), ICEPOLE differential-linear analysis (2015), Microsoft Office encryption flaws (2005), and CAESAR/AEGIS (2013-2015). Awards: Finalist, NIST Lightweight Competition (2021) CAESAR Competition Winner (2019) SHA-3 Finalist (2011) eSTREAM Selection (2008) He leads the JH Hash Function and TinyJAMBU projects, with hardware/software implementations and active participation in cryptographic standards development. His work involves security analysis of Microsoft Office encryption (2005) and advisories on Adobe Reader vulnerabilities (CVE-2014-0522 to CVE-2014-9165).

Connie LovejoyView profile

Professor

• Microbial biodiversity
• Arctic marine microbes
• Phytoplankton
• +7 more

Connie Lovejoy is a Professor in the Department of Biology at Université Laval, Quebec, Canada, specializing in Arctic marine microbial ecology. Her research focuses on microbial biodiversity in polar environments, particularly planktonic microorganisms including phytoplankton, protists, archaea, and bacteria that drive global carbon and mineral cycling. She leads multiple research projects examining Arctic microbial communities and their responses to climate change. Dr. Lovejoy received her B.Sc. from the University of California Davis (1973-1976), followed by a Ph.D. in Oceanography from Université Laval (1998-2002), and completed a postdoctoral fellowship at Institut Ciènces del Mar, CSIC' CMIMA in Spain (2002-2004). Her research interests center on Arctic marine microbes and their ecological roles. She investigates questions regarding microbial abundance, genetic and metabolic diversity, and the factors determining growth and mortality in these organisms. Her work examines how these microorganisms function within changing Arctic ecosystems, particularly in relation to climate change impacts on microbial food webs and biogeochemical cycles. She has pioneered research on microbial communities in permafrost lakes, river-to-sea continua, and under-ice environments. Analysis of her recent publications (2022-2024) reveals consistent focus on Arctic microbial ecology across multiple dimensions: microbial community structure across environmental gradients, biogeochemical cycling in changing environments, evolutionary adaptations of polar microorganisms, and the use of molecular techniques to understand microbial diversity. Her work spans freshwater, brackish, and marine systems, with particular attention to the impacts of climate change on microbial communities and their ecosystem functions. Dr. Lovejoy has secured significant research funding through NSERC and ArcticNet grants, leading projects on Arctic microbial biodiversity, biogeography, and environmental selection. She has been instrumental in major research initiatives including the Canada First Research Excellence Fund Sentinel North project focusing on sentinel microbiomes for Arctic ecosystem health. Her laboratory at Université Laval collaborates extensively with international research teams across Canada, the United States, Europe, and participates in major Arctic research networks. She works closely with the Takuvik research unit, a joint Canada-France research laboratory focusing on Arctic studies.

Dan SunView profile

Senior Lecturer

• Nanocomposites
• Biomedical Applications
• Plasma Processing
• +3 more

Dan Sun is a Senior Lecturer (Associate Professor) at the School of Mechanical and Aerospace Engineering, Queen's University Belfast, with expertise in plasma synthesis of functional nanocomposites and biomedical applications. Her research spans healthcare and aerospace sectors, focusing on nanocomposites for bone repair, aircraft materials manufacturing, and plasma-assisted synthesis. PhD in Mechanical Engineering (Tribology) from University of Southampton Postdoctoral work at NIBEC, University of Ulster Research interests include Nanocomposites , Biomaterials , Plasma Processing , and Aerospace Composites Manufacturing . She has contributed to 139 research outputs, 7 datasets, and 107 activities, including projects like European-Chinese aero-structure drilling collaboration and atmospheric pressure plasma synthesis of bio-nanocomposites. Recent publications focus on PEEK-based implants , heterojunctions for hydrogen evolution , and 3D-printed graded lattice structures . Scientific awards include multiple Best Paper Awards (2023, 2025) and travel grants from IET and IMechE. She teaches modules on mechanics of materials, research methods, and materials selection. MEE1004: Mechanics of Materials MEE7031: Research Methods & Data Analytics (Coordinator) MTS7022: Materials Selection and Characterisation

Jarno VanhataloView profile

Professor

• Statistics
• Probability
• Ecology
• +6 more

Professor Jarno Vanhatalo is a Professor of Statistics at the University of Helsinki, serving as vice director of the Research Center for Ecological Change. He is affiliated with both the Faculty of Biological and Environmental Sciences and the Faculty of Science, where he leads the Environmental and Ecological Statistics Group. His work bridges advanced statistical methodology with pressing ecological and environmental challenges. His research focuses on the development and application of statistical models for ecological and environmental data. Key areas include: Bayesian statistics and hierarchical modeling Gaussian processes and spatial statistics Species distribution modeling Ecological risk assessment Climate change impact analysis Biodiversity monitoring and conservation Professor Vanhatalo's publication record shows a consistent focus on integrating sophisticated statistical methods with ecological applications. His recent work demonstrates increasing emphasis on climate change impacts on biodiversity, spatially explicit modeling of ecological processes, and the development of Bayesian methods for uncertainty quantification in environmental predictions. His research spans terrestrial and marine ecosystems, with particular attention to Nordic and Baltic regions. Among his notable contributions are advancements in: Joint species distribution modeling Bayesian calibration of environmental models Spatiotemporal survey design Model-based variance partitioning in ecological studies Statistical approaches to Arctic risk management Professor Vanhatalo has received significant research funding, including an ERC grant for "Predective Understanding of the effects" (2024-2029) and leadership roles in multiple Academy of Finland and EU-funded projects focused on biodiversity, ecological change, and risk management in polar waters. He actively contributes to the academic community through: Supervising doctoral students in Wildlife Biology and Mathematics and Statistics programs Serving on editorial boards for journals including Conservation Biology and Ecology Letters Peer reviewing for numerous statistical and ecological journals Organizing workshops on statistical methods in ecology

• Food Science
• Thermal Processing of Foods
• Inverse Problems and Parameter Estimation
• +3 more

Kirk D. Dolan is a Professor at Michigan State University (MSU), holding joint appointments in the Department of Food Science and Human Nutrition (lead) and the Department of Biosystems & Agricultural Engineering within the College of Agriculture & Natural Resources. His research focuses on thermal processing modeling of foods and inverse problems in food science, utilizing advanced computational tools like MATLAB and COMSOL for parameter estimation. He actively contributes to food safety through extension work, including co-teaching the FDA-mandated Better Process Control School and HACCP courses. PhD, Agricultural Engineering, Michigan State University, 1989 MS, Agricultural Engineering, University of California, Davis, 1985 BS, Agricultural Engineering, University of Florida, 1983 Dolan’s research spans thermal processing technologies (canning, drying, aseptic processing), inverse problem solving, and statistical methods for food researchers. His recent publications emphasize antioxidant analysis, kinetic modeling, and computational approaches in food systems. Recent publications highlight advancements in parameter estimation for food processing, including studies on thermal conductivity in cherry pomace, starch viscosity models, and microbial inactivation dynamics. His work bridges computational methods with practical applications in food safety and quality preservation. 2019 CANR Camden Endowed Teacher/Scholar Award Dolan chairs the triennial Inverse Problems Symposia at MSU and co-teaches graduate courses like BE 835 (Modeling Methods in Biosystems Engineering). His extension work supports Michigan food entrepreneurs through FDA product registration assistance and industry training programs.