Find Academic Supervisors

• Astrophysics
• Early Universe Studies
• Gamma-Ray Bursts
• +3 more

Nathaniel Butler is an Associate Professor at Arizona State University's School of Earth and Space Exploration. His research focuses on astrophysical explosions and their role in probing the early universe, with emphasis on gamma-ray bursts (GRBs) and their optical counterparts. He holds a Ph.D. in Physics from MIT (2003) and a B.A. in Physics (magna cum laude) from Princeton University (1998). Education: Ph.D. Physics, Massachusetts Institute of Technology, 2003 B.A. Physics (magna cum laude), Princeton University, 1998 Research Interests: Dr. Butler's work centers on understanding the properties and evolution of the early universe through observations of GRBs and associated phenomena. His projects involve collaborations with advanced facilities like the COLIBRÍ robotic telescope and the SVOM mission, focusing on optical counterpart detection, afterglow analysis, and multi-messenger astronomy. His expertise in data mining and transient event analysis supports large-scale sky surveys and rapid-response observation protocols. Grants & Advising: No student advisees or grant details listed. His research is supported through institutional affiliations and collaborative projects. Labs/Teams: Active in the COLIBRÍ telescope initiative and projects like the Exoplanet Climate Infrared Telescope (EXCITE) and Star-Planet Activity Research CubeSat (SPARCS).

Mitchell L. NeilsenView profile

Professor

• Cyber-Physical Systems
• Distributed Systems
• Scientific Computing
• +7 more

Mitchell L. Neilsen is a Professor in the Department of Computer Science at Kansas State University's College of Engineering, where he also serves as the graduate program director. He holds the Warren and Gisela Kennedy - Carl and Mary Ice Keystone Research Scholar position and maintains an active research program with multiple ongoing projects. His educational background includes a Ph.D. in Computer Science (1992), M.S. in Computer Science (1989), and M.S. in Mathematics (1987), all from Kansas State University, plus a B.S. in Mathematics Education from the University of Nebraska-Kearney (1982). After beginning his career as an assistant professor at Oklahoma State University, he returned to K-State in 1996. Research Interests: Cyber-Physical Systems: Design, Analysis, Verification of systems integrating computing, networking, and physical processes Distributed Systems: Algorithms, design, and analysis of distributed computing systems Scientific Computing: Computational Fluid Dynamics, Finite Element Analysis, High Performance Computing, and Simulation Application Areas: Agriculture technology, Dam safety analysis, Mobile applications, Natural resources management, and Real-time Embedded Systems His research program shows clear evolution toward agricultural technology applications, particularly high-throughput phenotyping, while maintaining strong foundations in cyber-physical systems and scientific computing. Recent publications indicate increasing integration of machine learning and computer vision techniques into traditional research areas. Research Funding: National Science Foundation U.S. Department of Agriculture Sandia National Laboratories Department of Homeland Security Private industry partners Dr. Neilsen has mentored numerous graduate students through their M.S. and Ph.D. programs, with recent advisees focusing on applications in agricultural technology, dam safety, and embedded systems. His advising approach emphasizes practical applications of theoretical computer science concepts. Current Teaching (Fall 2024): CIS 450 - Computer Architecture and Operations CIS 625 - Concurrent Software Systems CIS 720 - Advanced Operating Systems

Duncan KoerberView profile

Associate Professor

• Crisis Communication Theory
• Writing Pedagogy
• Media and Journalism History
• +3 more

Duncan Koerber is an Associate Professor at Brock University’s Department of Communication, Popular Culture and Film. He holds a PhD from York University and Ryerson University, an MA in Journalism from the University of Western Ontario, and a BA in English, Professional Writing, and Political Science from the University of Toronto. His research focuses on crisis communication theory, writing pedagogy, and media/journalism history. He teaches courses on business communication, public relations, and crisis communication. Education: PhD, Communication & Culture, York University and Ryerson University MA, Journalism, University of Western Ontario BA, English, Professional Writing & Political Science, University of Toronto Research Interests: His work examines how media shape political identities (e.g., early Canadian newspapers’ role in party formation), modern crisis communication in social media, and writing pedagogy. He investigates why social media crises are so damaging to organizations and explores historical media’s role in political discourse. Recent projects include analyzing municipal pandemic communication and sports crisis management. Publications: Koerber authored Crisis Communication in Canada (2017, UTP) and co-edited a 2020 Canadian Journal of Communication special issue on crisis theory. His research appears in top journals like Public Relations Review and Journal of Canadian Studies . Teaching & Advocacy: He emphasizes practical writing skills for professional contexts. Courses include business communication strategies and crisis management frameworks for organizations facing reputational threats. Labs/Teams: No dedicated lab, but collaborates with Brock’s Communication Research Group on interdisciplinary projects.

Gunho SohnView profile

Associate Professor

• 3D Urban Space Modelling
• Photogrammetric Computer Vision
• Geometric Remote Sensing
• +7 more

Gunho Sohn is an Associate Professor and Department Chair in the Earth and Space Science and Engineering (ESSE) Department at York University's Lassonde School of Engineering. His research focuses on advanced geomatics engineering applications, including 3D urban modeling, photogrammetric computer vision, and geospatial data integration. He specializes in developing innovative solutions for navigation systems, energy optimization, and autonomous robotics through interdisciplinary approaches. Dr. Sohn's work emphasizes practical implementations of remote sensing technologies, with notable contributions to LiDAR data processing, SLAM systems, and BIM-GIS integration. His research has addressed real-world challenges such as improving air quality models using industrial plume observations and creating inclusive pedestrian navigation tools using open geospatial datasets. Recent trends in his publications highlight advancements in deep learning for geospatial tasks, including semantic segmentation of aerial LiDAR data, noise reduction in sensor networks, and UAV positioning systems. His work also explores digital twin applications for simulating urban environments and optimizing building energy consumption through BIM data analysis. While no specific awards or grants are listed, his extensive publication record reflects significant contributions to the fields of geomatics and computer vision. His research group collaborates on large-scale datasets like YUTO MMS and Yuto Semantic, advancing mobile mapping and semantic understanding of urban infrastructure.

Girija ChettyView profile

Professor

• Multimodal Systems
• Medical Image Computing
• Computer Vision
• +7 more

Girija Chetty is a Full Professor in Computing and Information Technology at the University of Canberra's School of Information Technology and Systems. She holds a PhD in Information Sciences and Engineering and has over 35 years of experience in academia and research leadership roles, including Head of Software Engineering and Program Director of ITS courses. Her research focuses on multimodal systems, medical image computing, AI, and data science. She leads a dynamic research group comprising PhD students, postdocs, and international collaborators. Education: PhD in Information Sciences (Australia, 2007), MSc and BSc in Electrical Engineering/Computer Science (India). She has held visiting roles at Deakin University and CSIRO. Research interests span computer vision, pattern recognition, and medical diagnostics, with 200+ publications in top journals/conferences. Her work addresses global challenges via AI-driven solutions in healthcare (e.g., pain assessment systems, malaria diagnostics) and sustainability (SDG impact frameworks). Projects include AI for remote ultrasound imaging and smart farming systems. She actively collaborates with industry and global research institutions. Grants/Projects: 12 funded initiatives including AI for extreme environment healthcare, malaria pathogen detection, and big data-driven population health. Awards: Senior IEEE/Australian Computer Society membership, editorial roles in IEEE/Elsevier journals. Labs/Teams: Leads a multidisciplinary research group focused on medical AI and multimodal systems.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +4 more

Dr. Milos Hauskrecht is a Professor of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds a PhD from MIT (1997) and an M.Sc. from Slovak Technical University (1988). His research focuses on AI, machine learning, and data mining, with applications in medicine and finance. He leads projects in real-time clinical monitoring, anomaly detection, and time-series analysis of EHR data. He has advised numerous PhD and MS students, including notable alumni now at Amazon, DeepMind, and Microsoft. Research interests include reasoning under uncertainty, optimization, and AI-driven medical decision support. Current grants include NIH funding for AI in renal therapy and clinical monitoring. He has published widely in top venues like ICML, NeurIPS, and journals such as Artificial Intelligence in Medicine. His work on conditional outlier detection earned the Homer Warner Award (AMIA 2010). He teaches machine learning and advises on interdisciplinary AI projects.

• Artificial Intelligence
• Computer Vision
• Digital Agriculture
• +3 more

Ferdous Sohel is a Professor of Information Technology at Murdoch University and inaugural lead of the Agricultural Technologies program. His research spans AI, computer vision, and digital agriculture, with applications in medical imaging and environmental monitoring. He received the Mollie Holman Doctoral Medal and Vice Chancellor's Early Career Research Award. Research Impact: Developed innovative AI models for aquaculture oxygen prediction, 3D object tracking, quantum neural networks, and prohibited item detection. His work advances precision agriculture through hyperspectral classification frameworks and irrigation decision systems. Professional Service: Associate Editor for IEEE Transactions on Multimedia and senior IEEE member. Current projects include adversarial robustness for LiDAR systems and lightweight dormitory security networks.

Sarah AtkinsView profile

Lecturer

• Forensic Linguistics
• Applied Linguistics
• Discourse Analysis
• +4 more

Dr. Sarah Atkins is a Lecturer in the Department of Communication and Culture at Aston University and a Research Fellow at the Aston Institute for Forensic Linguistics. She holds a PhD in Applied Linguistics from the University of Nottingham and a PGCHE from Aston University. Her affiliations include membership in the British Association for Applied Linguistics (BAAL), International Pragmatics Association (IPrA), and International Association for Forensic and Legal Linguistics (IAFLL). Atkins' research explores: Forensic and legal linguistics, focusing on emergency calls, police interviews, and anonymization ethics Healthcare communication in clinical settings and Schwartz Rounds Applied linguistic ethics and professional practice Multimodal analysis of institutional interactions Her publications demonstrate strong methodological diversity, spanning conversation analysis, corpus linguistics, and multimodal approaches. Dominant themes include ethical frameworks in linguistic research, crisis communication dynamics, and healthcare team interactions. Recent work increasingly addresses technological applications like AI system co-design and forensic databank development. Scientific Awards: Poster Prize, Royal College of General Practitioners (2018) Knowledge Exchange and Impact Award (2016) Atkins mentors PhD students researching police-suspect interactions and supervises collaborative projects including the ID2 data anonymization initiative and Crimes in Action 999 call analysis. She secured £120k in research funding for projects with Birmingham Community Healthcare NHS Foundation Trust. She directs fieldwork at the Aston Institute for Forensic Linguistics and collaborates on the Forensic Linguistic Databank (FoLD) and EXCROW extortion corpus projects. Her lab develops training interventions for healthcare professionals and police services.

Seth PolsleyView profile

Assistant Professor

• Human-Computer Interaction
• Intelligent Systems
• Educational Technology
• +4 more

Seth Polsley is an Assistant Professor in the Jeffrey S. Raikes School of Computer Science and Management at the University of Nebraska-Lincoln. His academic home resides in the School of Computing, where he bridges intelligent systems design with human-computer interaction to enhance educational and universal computing experiences. BS in Computer Engineering (2014) - University of Kansas MS (2017) & PhD (2023) in Computer Engineering - Texas A&M University His research explores: Intelligent tutoring systems Brain-computer interfaces Accessible educational technologies Machine learning for child development assessment Sketch recognition in STEM learning Recent publications demonstrate expertise in tactile learning interfaces, sketch-based developmental assessment, and equitable AI systems. Key disciplines span Human-Computer Interaction, Machine Learning, and Educational Technology. Scientific recognition includes: James Blackiston Memorial Graduate Fellowship Sigma Xi Research Award With professional experience at Lexmark International and MIT Lincoln Lab, Polsley combines practical engineering with educational innovation. His work on sketch-based tools and wearable systems addresses both technical and societal challenges in computing.

Rei Sanchez-AriasView profile

Teaching Professor

• Data Mining
• Machine Learning
• Numerical Optimization
• +1 more

Rei Sanchez-Arias is a Teaching Professor and Director of the Master of Applied Data Science (MADS) program at UNC Chapel Hill's School of Data Science and Society. His expertise includes data mining, machine learning algorithm development, and data science pedagogy. He previously held positions at Florida Polytechnic University and St. Thomas University. Research interests span educational tools, health informatics, and optimization methods. Recent work involves AI for endoscopic surgery evaluation, meta-analysis of MLOps tools, and curriculum design for data science programs. Awards include the Excellence in Teaching Award from Florida Polytechnic. Student mentorship focuses on data wrangling and analytics projects.

Joseph AllencherrilView profile

Assistant Professor

• Cardiovascular Medicine
• Myocardial Infarction Management
• Clinical Research Methods
• +3 more

Dr. Joseph Allencherril is an Assistant Professor in the Department of Cardiovascular Medicine at the University of Texas Medical Branch . He holds an MD from Baylor College of Medicine - Houston, TX (completed 2016). His research focuses on acute cardiac care, including ST-segment elevation myocardial infarction (STEMI) management, gender-specific cardiovascular disease impacts, and contrast-induced kidney injury. He has contributed to over 29 peer-reviewed publications, with recent works emphasizing clinical decision-making, prognostication via lung ultrasound, and tailored interventions for atrial fibrillation patients. Key research interests include advancing STEMI classification systems, leveraging imaging technologies for better patient outcomes, and addressing public health gaps in smoking-related cardiovascular risks. Dr. Allencherril has collaborated on international studies and is affiliated with UTMB's strategic health communities research initiatives. No formal scientific awards are listed, but his work has garnered significant readership (e.g., 22+ readers on Mendeley for his 2024 smoking review). His grants and lab affiliations remain unspecified in available texts.

Stefon van NoordtView profile

Assistant Professor

• Cognitive Neuroscience
• Developmental Psychology
• Neuroimaging
• +3 more

Dr. Stefon van Noordt is an Assistant Professor in the Department of Psychology at Mount Saint Vincent University. His research focuses on understanding brain-based markers of attention control and performance monitoring, particularly in developmental and individual differences contexts. He integrates behavioral, imaging, and computational tools to study neural dynamics in normative and pathological states like anxiety. His work is supported by NSERC, CIHR, and other institutions. He holds postdoctoral training from McGill University and Yale University. Education includes a Ph.D. in Psychology (2016) from Brock University, with postdoctoral fellowships at the Montreal Neurological Institute and Yale Child Study Centre. His research emphasizes EEG analysis, autism risk prediction, and medial frontal theta oscillations. Research interests span cognitive neuroscience, developmental psychology, and neuroimaging, with a focus on EEG methodologies and their application to autism spectrum disorder. Recent work includes studies on infant EEG connectivity, social exclusion effects, and neural responses to peer feedback. Dr. van Noordt collaborates on projects like the EEG-IP platform for international infant data integration and has published extensively on EEG biomarkers and neurodevelopmental trajectories. He mentors students in Honours thesis projects and postdoctoral training.

• Biomedical Engineering
• Tissue Engineering
• 3D Printing
• +5 more

Neil Lin is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA), with a joint appointment in Bioengineering. His research focuses on developing 3D-printed tissues that replicate the structure, mechanics, and functionality of human organs, with applications in drug screening and regenerative medicine. Lin leads the Lin Lab - Living Soft Material Engineering , advancing soft and living material engineering through interdisciplinary approaches. Lin holds a Ph.D. and M.S. in Engineering from Cornell University (2016 and 2013) and a B.S. in Engineering from National Tsing Hua University, Taiwan (2008). His work spans biomaterials mechanics, quantitative imaging, and AI-driven biological analysis. Research interests include the structure and dynamics of soft biomaterials, image-based force measurements, and quantitative imaging techniques for material characterization. Recent work explores cell morphology regulation, AI applications in microscopy, and mechanical heterogeneity in live tissues. Lin’s publications highlight advancements in cell trapping, AI-based image translation, and prostate cancer metabolism modeling. He has received prestigious awards, including the Young Investigator Award (2022), Hellman Fellowship, and NIH Maximizing Investigators' Research Award (2022). His lab integrates engineering and biology to address challenges in tissue engineering, with ongoing projects on 3D kidney models, drug response assays, and AI-driven phenotyping of senescent cells.

• Precision Agriculture
• Remote Sensing
• Soil Science
• +3 more

Dr. Patrick Filippi is a Lecturer in Precision Crop Management at the School of Life and Environmental Sciences, University of Sydney. He is affiliated with the Precision Agriculture Laboratory and the Sydney Institute of Agriculture. His work focuses on integrating remote sensing, machine learning, and geostatistics to address challenges in precision agriculture, particularly in crop yield modeling, soil mapping, and environmental monitoring. Research interests include precision agriculture technologies, soil science applications, data-driven crop management, and the use of satellite and proximal sensing for agricultural decision-making. He has contributed to projects funded by the Grains Research and Development Corporation (GRDC) and the University of Sydney, focusing on spatial variability in crop production, soil constraints, and machine learning interpretability. Key achievements include developing the LimeSoDa dataset for soil mapping and winning the 2016 CSIRO AgData Challenge Hackathon. His grants span topics like nitrogen fixation mapping in legumes and frost/heat management analytics. Filippi collaborates closely with industry to translate research into practical tools for farmers. Awards: 2nd Place CSIRO AgData Challenge Hackathon (2016) Labs: Precision Agriculture Laboratory (https://precision-agriculture.sydney.edu.au/) Grants: Includes Strategic Partnership Seeding Grants (2024), GRDC-funded projects (2022–2024), and Start-Up Research Funding (2024).

Chenliang XuView profile

Associate Professor

• Computer Vision
• Audio-Visual Learning
• Vision and Language
• +5 more

Chenliang Xu is an Associate Professor in the Department of Computer Science at the University of Rochester, affiliated with the Goergen Institute for Data Science and Artificial Intelligence (GIDS-AI). His research focuses on computer vision, audio-visual learning, and trustworthy AI. He holds a PhD from the University of Michigan (2016), with prior degrees from Nanjing University of Aeronautics and Astronautics and the University at Buffalo. Notable awards include the Best Paper Award at ACCV 2024 and the James P. Wilmot Distinguished Professorship. His work spans interdisciplinary topics such as video understanding, multimodal reasoning, and robust AI. Key research contributions include audio-visual scene synthesis, bias mitigation in models, and applications in public health. He has secured over $3M in grants, including NIH funding for AI-driven video description tools and public health initiatives. Prof. Xu advises a dynamic research group with 11 PhD students and numerous collaborators. His lab explores cutting-edge projects like egocentric audio-visual understanding, generative AI for avatars, and multimodal defense mechanisms. He teaches courses in machine vision, deep learning, and advanced computer vision.