Find Academic Supervisors

• Computer Vision
• Machine Learning
• Image Processing
• +4 more

Adjunct Professor Shuai Wan is affiliated with the School of Engineering at RMIT University (City Campus, Australia). His research focuses on computer vision, machine learning, 3D point cloud compression, neural video coding, and remote sensing . Key contributions include lightweight deep learning frameworks for image/video compression, spatio-temporal context models for point clouds, and adaptive quantization techniques. Research Outputs Insights : Wan’s work spans 2024–2025 , emphasizing end-to-end deep learning solutions for challenges in Exemplar-based colorization with semantic attention Rendering-oriented 3D point cloud compression Slimmable video codecs with variable bitrate G-PCC standard enhancements for quantization and entropy coding Adversarial example detection in remote sensing Technical Domains : His articles intersect artificial intelligence, signal processing, and computer graphics , with applications in cloud gaming, SAR systems, and industrial data compression. Methods include transformers, attention networks, and 3D convolutional architectures .

Scott MillerView profile

Lecturer

• Physical Layer Security
• Visible Light Communication (VLC)
• Acoustic Telemetry Systems
• +5 more

Scott Miller is a Lecturer in the Department of Industrial & Systems Engineering at Texas A&M University. His research focuses on physical layer security, wireless communication systems, and signal processing in harsh environments. He specializes in visible light communication (VLC), acoustic telemetry, and hybrid FSO-mmWave systems. Key contributions include secure IM-OFDMA system design, IQ imbalance analysis, and medium-specific communication protocols for downhole monitoring. Research interests span secure communication protocols, network coding, cognitive radio networks, and system reliability in fading channels. He has pioneered work on VLC-based downhole gas pipeline monitoring using hydrogen/nitrogen mediums and developed learning-based link selection approaches for hybrid wireless systems. His work emphasizes practical applications in industrial telemetry and secure wireless transmission. Notable trends in his publications include: Advancements in physical layer security mechanisms for uplink systems Innovative use of non-traditional mediums (e.g., CO₂, hydrogen) for VLC Integration of machine learning for signal detection and link optimization Robustness analysis of hybrid FSO-mmWave networks under various impairments His research bridges theoretical communication frameworks with real-world industrial applications, addressing challenges in energy, oil/gas sectors, and secure IoT deployments.

Yan YanView profile

Assistant Professor

• Bioinformatics
• Machine Learning
• Big Data Analysis
• +7 more

Yan Yan is an Assistant Professor at the School of Computer Science, University of Guelph. His research focuses on bioinformatics, multi-omics analysis, and AI-driven computational models for understanding biological processes. His lab develops algorithms for genome-wide association studies, single-cell RNA-seq analysis, and de novo peptide sequencing, with applications in plant genomics and digital agriculture. Education : Not explicitly stated, but his publications suggest advanced training in bioinformatics and computational biology. Research Interests : Bioinformatics, Machine Learning, Big Data Analysis, Statistical Association, and AI applications in agriculture. His work integrates artificial intelligence with omics data to uncover disease mechanisms and improve agricultural practices. Recent trends in his publications emphasize robotics, structural health monitoring, and environmental sensing using hybrid neural networks and deep learning techniques. Grants & Awards : No awards explicitly listed, but his prolific publication record indicates sustained research activity. Advising & Labs : Advises students like B S Puliparambil and J Tomal. His lab actively collaborates on projects involving AI in agriculture, robotics, and structural engineering. Current initiatives include digital twins for human-robot collaboration and precision livestock monitoring systems. Labs/Teams : Leads a computational biology and AI lab focusing on multi-omics integration and smart agriculture solutions.

• Biostatistics
• Clinical Trials
• Statistical Modeling
• +7 more

Erich J Greene is a Research Scientist in the Department of Biostatistics at the Yale School of Public Health , where he contributes to clinical trial methodology and statistical analysis. Yale Center for Analytical Sciences (YCAS) Yale Data Coordinating Center (YDCC) Education: PhD in Psychology (2003), Princeton University MA in Psychology (1997), Princeton University MS in Physics (1995), Cornell University AB in Physics (1991), Princeton University Research Interests span Biostatistics , Clinical Trial Design , Survival Analysis , and Public Health Data Science . His work focuses on: Competing risks and clustering in time-to-event data Electronic health record data validation Sex/gender disparities in cardiovascular outcomes Pragmatic trial methodologies Bayesian approaches for complex biomedical data Publication Trends reveal expertise in: Cluster-randomized trial statistical methods Fall injury prevention modeling Dementia care comparative effectiveness ICD-10 coding algorithms Non-proportional hazard scenarios Zero-inflated recurrent event modeling Collaborations include frequent partnerships with: James Dziura (9 co-publications) Can Meng (8 co-publications) David Ganz and Denise Esserman (6 each) Additional Activities: Served on the Board of Directors for the New Haven Theater Company (2011-2022).

Emily JeffersonView profile

Professor

• Health Data Science
• Trusted Research Environments (TREs)
• Data Science
• +6 more

Emily Jefferson is a Professor of Health Data Science at the University of Dundee, currently serving as CTO of Health Data Research (HDR) UK and Interim Director of DARE UK. She holds an honorary professorship in Population Health and Genomics. With a PhD in Bioinformatics and industry experience in Big Data and project management, her career spans academia, finance, and solo global travel. Her research focuses on Trusted Research Environments (TREs), data governance, and machine learning applications in healthcare. She led the Health Informatics Centre (2013–2022), managing a 60-person team supporting over 100 projects. Key achievements include ISO27001 certification and Scottish Government-accredited Safe Haven infrastructure. Since 2014, she has secured over £120M in grants as PI/Co-I, delivering £28M. Notable projects include HT-ADVANCE (hypertension biomarkers), Alleviate (chronic pain data hub), and GRAIMATTER (TRE disclosure control guidelines). She chairs boards at Swansea University and European Bioinformatics Institute. Awards include the 2016 Farr Institute Future Leader. Her work addresses SDG 3 (Good Health) and 9 (Industry/Innovation). Recent publications emphasize TRE innovation, hypertension subtyping, and pandemic data infrastructure (e.g., CO-CONNECT for COVID-19).

Katharina Kleinen-von KönigslöwView profile

Professor

• Political Communication
• Digital Public Spheres
• Transnational Communication
• +4 more

Katharina Kleinen-von Königslöw is a Full Professor of Journalism and Communication Studies at the University of Hamburg , focusing on digital communication and sustainability. Since 2018, she serves as Vice Dean for Teaching and Studies at the Faculty of Economics and Social Sciences and leads the Erasmus Mundus Master's program Journalism, Media and Globalisation . Her research spans digital public spheres , transnational communication , and sustainability framing in social media, with a methodological emphasis on quantitative and qualitative empirical methods . Recent publications analyze: Platform governance (Google/YouTube’s role in conspiracy theories) Climate futures framing across countries Right-wing populists’ linking practices Automated content analysis via machine learning She has secured major grants from institutions like Landesforschungsförderung Hamburg and Swiss National Science Foundation , co-leading interdisciplinary projects on security and sustainability. Her work has been cited over 1,600 times on Google Scholar. Her team includes researchers like Dr. Gerret von Nordheim and Dr. Laura Liebig, with collaborations across Europe and North America.

Manish MotwaniView profile

Assistant Professor

• Software Engineering
• Automated Program Repair
• Automated Testing
• +4 more

Manish Motwani is an Assistant Professor at the School of Electrical Engineering and Computer Science, Oregon State University. His research focuses on automating software engineering practices to improve software quality, particularly in high-performance computing (HPC), REST APIs, and natural language-driven program repair. He leads the Advanced Software Engineering Research (ANSWER) lab, which is part of the Software Engineering and Human-Computer Interaction group. Education: Ph.D. in Computer Science (University of Massachusetts Amherst), Postdoctoral Fellow (Georgia Institute of Technology) Motwani's research bridges empirical analysis of software repositories with automated techniques for testing, debugging, and program repair. Key projects include: Automated Testing for HPC Applications OpenAPI Specification Generation via Static Analysis High-Quality Patch Validation Using Bug Reports JaRFLy Framework for Patch Evaluation Swami Tool for Natural Language Test Oracles RAFL and Blues Fault Localization Techniques His work addresses critical challenges such as patch overfitting, HPC bug detection, and semantic search for real-world defects. He has published in top venues like ICSE, TSE, and EMSE, and holds two U.S. patents for automated requirements and regulatory compliance tools. At Oregon State, Motwani actively mentors and seeks motivated PhD students interested in software testing, debugging, and program repair for HPC and AI/ML applications. He previously contributed to requirements engineering at Tata Research Development and Design Centre in India.

Mark SextonView profile

Academic

• Digital Musicology
• Generative Music
• Algorithmic Composition
• +12 more

Mark Sexton is a Principal Lecturer and Academic Lead at the School of Film, Media and Creative Technologies, University of Portsmouth, where he has been contributing since 2007. He serves as Associate Head (Academic) in the Faculty of Creative & Cultural Industries and leads initiatives in teaching, learning, assessment, and curriculum development. He has led the accreditation of multiple courses and contributed to academic governance at institutional and external levels. His research centers on Digital Musicology , intersecting traditional musicology with digital tools and computational methods. Key interests include: Generative Music and Algorithmic Composition Spatial Audio and Sound Design Music for Games and Interactive Media Creative Coding and Machine Learning in Music Digital Humanities in Creative Practice His recent publications (2023) explore the works of Ligeti, Birtwistle, Beethoven, and original cast recordings using digital analysis techniques. These works reflect a consistent trend in applying computational and digital methods to musicological inquiry and creative applications. Mark is actively involved in interdisciplinary research projects, including AI-driven sound design and computational score analysis. He collaborates with institutions and researchers across the UK and contributes to innovation in digital arts. Professional affiliations include: Incorporated Society of Musicians Alan Turing Institute – AI & Arts Interest Group Society for Music Theory – Jazz Interest Group Audio Engineering Society (AES) Media in the Digital Age – Turing Special Interest Group He advises on academic practice, curriculum innovation, and assessment design. His leadership extends to course development and quality assurance. He has also served as an external examiner and workshop facilitator. Mark is a practicing musician, composer, and sound engineer, enriching his academic work with professional creative experience. He previously served as Head of the Music Department at Northbrook College, Sussex, before joining the University of Portsmouth.

• Brain Plasticity
• Neuronal Excitability
• Alzheimer's Disease
• +7 more

Claudio Grassi is a Full Professor of Physiology at the Catholic University of the Sacred Heart, Faculty of Medicine and Surgery "A. Gemelli", Rome. He serves as Director of the Department of Neuroscience since 2019 and contributes to university governance as a member of the Quality Committee and Advisory Board. Graduate in Medicine and Surgery Specialist in Neurology PhD in Neuroscience His research focuses on: Mechanisms of brain plasticity and neuronal excitability Neurodegenerative disease biomarkers (Alzheimer's) Role of viral infections in neurodegeneration Noninvasive brain stimulation effects Metabolic influences on synaptic plasticity Cochlear damage and auditory cortex plasticity Recent publications analyze HSV-1 infection, tau propagation, and metabolic impacts on hippocampal function. Grassi mentors 10 PhD students and a Master's tutor. Contact: claudio.grassi@unicatt.it

• Computer Science
• Artificial Intelligence
• Robotics

Gonzalo Esteban Costales is a researcher affiliated with the University of Leon from 2012 to 2025, specializing in Computer Science and Artificial Intelligence within the Robotics research group. His work bridges haptic simulation, robotics, and educational technology. Education: Ph.D. in Computer Science (2020), University of Leon, with a thesis on haptic simulators for expert knowledge transfer . Research Interests: Haptic simulation for surgical training and rehabilitation Robotics security in industrial environments Educational technology frameworks Version control analytics for student performance Open-source vulnerability detection tools Key Article Trends: Recent publications focus on haptic workspace optimization, threat modeling for robotic production plants, and security enhancements in continuous integration workflows. His work spans simulation design, cybersecurity, and educational applications of robotics.

• Production Systems Engineering
• Software Engineering
• Cyber-Physical Production Systems
• +4 more

Prof. Dietmar Winkler is a Lecturer at TU Wien's Department of Information Systems Engineering, specializing in Cyber-Physical Production Systems (CPPS) and Software Engineering. His work focuses on integrating safety, security, and quality aspects into production systems through model-driven engineering and agile practices. He contributes to Industry 4.0 initiatives, particularly in asset-based risk mitigation and knowledge graph frameworks for security analysis. Research interests include: production systems engineering, cyber-physical systems, test-driven validation, model integration, and software quality intelligence. His publications emphasize multi-view modeling, traceability pipelines, and empirical studies on test code readability. Recent work explores security-log analysis via knowledge graphs (VloGraph), test scenario validation using design models, and efficient FMEA re-validation in agile environments. He co-leads projects on digital production system safety and coordinates multi-disciplinary engineering artifacts. Active in academic communities, he organizes conferences like Software Quality: The Next Big Thing. His contributions bridge theory and practice in systems engineering, with a focus on improving software development processes in complex industrial settings.

Frédéric TheunissenView profile

Professor

• Auditory Neuroscience
• Vocal Communication
• Neural Computation
• +4 more

Frédéric Theunissen serves as a Professor in the Department of Psychology at the University of California, Berkeley, where he leads the Theunissen Lab. His research centers on auditory neuroscience, investigating how neural systems process vocal communication in animals and humans through interdisciplinary approaches combining behavioral experiments, neurophysiology, and computational modeling. His work explores the neural computations underlying sound perception, focusing on how auditory systems extract behaviorally relevant features from natural soundscapes. Key research areas include pitch, timbre, and rhythm perception; signal extraction from noise; auditory memory formation; and object recognition. The lab employs diverse methodologies including single-unit recordings in songbirds, ECoG/fMRI in humans, and behavioral tests across species ranging from zebra finches to spotted hyenas. Analysis of his recent publications reveals a consistent trajectory in decoding vocal communication mechanisms across biological systems. His work bridges animal and human studies, demonstrating how neural representations of sound features enable tasks like individual caller recognition (e.g., in bird calls and hyena giggles) and hierarchical speech processing in the human cortex. The research emphasizes the evolutionary and functional links between acoustic signal properties and neural coding strategies. Theunissen Lab operates as a collaborative hub for auditory neuroscience at UC Berkeley, integrating animal behavior, human psychophysics, and computational approaches. The lab's ecosystem spans species-specific communication studies—from canaries and woodpeckers to human speech—aiming to decipher universal principles of auditory perception and the neural basis of meaning extraction in communication sounds.

Ivo SteiningerView profile

Professor

• Foreign Language Education
• Literary Competence Development
• Teacher Professionalization
• +3 more

Prof. Ivo Steininger serves as Professor of Teaching Anglophone Literatures and Cultures at Justus Liebig University Giessen, Germany. He heads the Department of English – Teaching Anglophone Literatures and Cultures and maintains an active research profile in foreign language pedagogy. His academic journey includes state examinations for teaching (2007, 2012), a summa cum laude doctorate (2013), and interim professorships at the University of Paderborn (2016–2018) and Giessen (2019–2021). In 2024, he was a visiting scholar at Saint Mary’s University, Canada. Research focuses include: Literary text comprehension in EFL contexts Digitalization and sustainability in language education Teacher professionalization processes Anglophone cultural representations in media His work bridges theoretical frameworks with classroom applications, emphasizing multimodal literacy and critical cultural awareness. Publications demonstrate strong trends in: Digital pedagogy and critical media analysis (2020–2025) Sustainability integration in curricula (2023–2024) Teacher development research (2018–2021) Multimodal literary interpretation (2018–2025) Awards and projects: Piepho-Prize (2015) for advancing foreign language education research Current projects: Second-phase teacher training, ambiguity in picture books, and Education for Sustainable Development (ESD) in EFL

Alfredo BensoView profile

Professor

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +16 more

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

Joseph SchmidtView profile

Professor

• Talent Acquisition
• Team Effectiveness
• Employee Turnover
• +4 more

Joseph Schmidt is a Professor and Edwards Enhancement Chair in Business at the Edwards School of Business, University of Saskatchewan. He holds a PhD in Industrial/Organizational Psychology (University of Calgary), an MSc in Industrial/Organizational Psychology, and a BA in Psychology, all from the University of Calgary. His research focuses on talent acquisition, team effectiveness, employee turnover, judgment errors, and bias reduction in organizational contexts. Dr. Schmidt’s academic contributions span top-tier journals such as the Journal of Applied Psychology , Personnel Psychology , and Psychological Bulletin . His work bridges theory and practice, addressing real-world challenges in HR management and organizational behavior. Notable themes include the impact of personality on workplace outcomes, the dynamics of team performance, and the design of effective selection systems. Before academia, he worked at Hay Group (global consulting) and in HR for an engineering firm. His courses include Human Resource Management , Leadership , and Organizational Dynamics . Media outlets like the Wall Street Journal and CBC Radio have featured his research insights. His publications analyze trends in performance appraisals, team variance in ratings, and the role of dynamic behavioral trends. He emphasizes methodological rigor, particularly in addressing selection bias and causal inference. While no specific awards are listed, his prolific and influential work underscores his academic standing.