Find Academic Supervisors

• Fusion Plasmas
• Tokamak Experiments
• Electromagnetic Field Theory
• +4 more

Pär Strand is a Professor at Chalmers University of Technology, affiliated with the Department of Astronomy and Plasma Physics. His research focuses on transport in fusion plasmas , particularly through analysis of experiments at JET and development of simulation tools for ITER and other tokamak facilities. A key contributor to EU projects, he directs the Chalmers e-Science Centre, emphasizing data-driven methodologies and large-scale simulation technologies. Expertise: Fusion plasma dynamics, electromagnetic field theory, integrated modeling frameworks Projects: Code development for ITER/JET, FAIR data principles in fusion research, turbulence transport simulations Research Trends: Recent publications highlight advancements in: Tokamak power exhaust solutions (divertor shaping, neutral baffling) Machine learning applications for pedestal dynamics and disruption prediction High-order solvers for plasma transport equations Validation of D-T fusion power predictions against JET experiments

• Computational Social Cognition
• Social Biases
• Self-Relevance
• +5 more

Marius Golubickis is a Lecturer at the School of Psychology, University of Aberdeen . His research focuses on computational social cognition , investigating how self-relevance and stereotypical beliefs influence decision-making, attention, and learning through methodologies like Drift Diffusion Modeling and EEG . Research Areas : Computational Social Cognition, Self-Bias, Stereotype-Based Processing, Attention, and Neural Correlates of Self-Relevance. His recent publications (2023–2025) explore the temporal dynamics of self-prioritization , mindfulness interventions on learning efficiency, and stereotype-based associative learning . Methodologies span EEG spectral analysis , predictive coding , and behavioral experiments . Teaching : Courses include Perception , Advanced Psychology B , and Current Topics in Psychological Studies . He accepts PhD students in Psychology and collaborates with researchers like C. Macrae and J. Falben .

Sandeep ReddivariView profile

Associate Professor

• Software Engineering
• Requirements Engineering
• Visual Analytics
• +7 more

Sandeep Reddivari is an Associate Professor and Interim Graduate Director at the School of Computing, University of North Florida . Holding a Ph.D. in Computer Science and Engineering from Mississippi State University, his work focuses on software engineering , particularly requirements engineering , visual analytics , and software maintenance , with funding from the NSF, US Army Corps of Engineers, NSA, and UNF Foundation. Education : Ph.D. (2014, Mississippi State University), M.S. (2009, Texas A&M University), B.Tech. (2006, JNTU) Research Themes : Requirements Engineering, Visual Analytics, Data Mining, Machine Learning, GenAI, Software Security Teaching : Courses in Software Engineering, Data Science, and Database Systems Awards : NSF Grant Recognition (2024), Best Doctoral Symposium Poster (2013), Outstanding Graduate Teaching Award Nominee (2018) Publications span top venues like IEEE RE, ICSE, and COMPSAC, with a focus on combining visual analytics and machine learning to enhance software decision-making. His lab at UNF mentors students in directed independent studies, emphasizing code navigation , blockchain , and educational software tools .

Oum El Kheir AktoufView profile

Professor

• Dependability
• Safety
• Security
• +5 more

Oum El Kheir Aktouf is a Professor in Computer Science at Grenoble Institute of Technology (Esisar Engineering School) and a member of the LCIS laboratory, France. She previously served as a Visiting Professor at San José State University, USA, during a sabbatical leave. Education : Master and PhD in Computer Science from Grenoble Institute of Technology Her research focuses on dependability, safety, and security of embedded and interconnected systems, including sensor-based applications and multi-agent architectures. She employs runtime testing, diagnosis, and monitoring approaches. Her work spans mobile application testing, fault diagnosis in RFID and wireless sensor networks, and security frameworks for autonomous systems. Recent publications highlight trends in Android security benchmarking , decentralized cryptography , and multi-agent resilience . She has participated in 12 funded national and international research projects and supervised courses in operating systems, real-time systems, distributed computing, and system dependability.

Joshua I. GoldView profile

Professor

• Neuroscience
• Computational Neuroscience
• Cognitive Neuroscience
• +6 more

Joshua I. Gold is a Professor of Neuroscience at the Perelman School of Medicine, University of Pennsylvania , where he co-directs the Computational Neuroscience Initiative . His research focuses on the neural mechanisms underlying inference and learning in decision-making, integrating computational modeling with human and non-human primate studies . Education: Sc.B. in Neural Sciences from Brown University (1991), Ph.D. in Neurosciences from Stanford University (1997) Grants: NIH R01 EY015260, NIH F31 MH093099, NIH F21 MH093099 Gold's work explores how uncertainty, contextual information , and neural computations shape adaptive behavior. His lab employs psychophysics, electrophysiology , and pupillometry to study decision-making in dynamic environments. Recent publications highlight Bayesian inference, dual anticipatory processes , and neural correlates of reward prediction . Scientific Contributions: Developed computational models for learning rate regulation Investigated subthalamic nucleus and caudate nucleus roles in decision-making Linked noradrenergic systems to adaptive learning

Rebecca YangView profile

Visiting Professor

• Building Integrated Photovoltaics
• Solar Energy Applications in Buildings
• Construction Innovation
• +2 more

Rebecca Yang is a Visiting Professor at RMIT University's School of Property, Construction and Project Management, specializing in building, construction, and distributed renewable energy research. She integrates theoretical knowledge with cutting-edge technologies to advance sustainable urban development. Her research focuses on solar energy applications in buildings, construction innovation, and international energy policy frameworks through her leadership roles in the International Energy Agency's Photovoltaic Power Systems Programme (PVPS) Task 15 and Solar Heating and Cooling Programme (SHC) Task 66. She established RMIT's Solar Energy Application Lab and has 8 years of BIPV expertise. Notable achievements include: Australian representative in international BIPV standardization (IEC 63092) 2019 Facilitator Prize for BIPV Tool development She supervises research projects related to: Solar building envelope optimization Machine learning for energy systems Fire safety in BIPV installations Blockchain-enabled energy trading Circular economy for PV waste

Olivier GevaertView profile

Associate Professor

• Biomedical Data Fusion
• Machine Learning
• Cancer Driver Genes
• +6 more

Olivier Gevaert is an Associate Professor at Stanford University with dual appointments in the Department of Medicine (Biomedical Informatics) and the Department of Biomedical Data Science. He leads interdisciplinary research at the intersection of machine learning and biomedical data fusion, with significant contributions to cancer genomics, imaging biomarkers, and synthetic biomedical data generation. His work spans multiple Stanford institutes including Bio-X, Cancer Institute, and Neurosciences Institute. His research focuses on: Biomedical data fusion across molecular, cellular, and tissue scales Multi-omics integration for cancer driver gene discovery Imaging genomics/radiogenomics Medical digital twin frameworks Synthetic data generation for machine learning Key awards include Faculty Fellow at Stanford Center at Peking University and fellowships from King Baudouin Foundation and Belgian American Educational Foundation. His lab has produced transformative tools like Moonlight, EpiMix, SEQUOIA, and RNA-GAN. He teaches foundational courses in biomedical data science and machine learning approaches.

• Software Engineering
• Software Testing
• Program Analysis
• +4 more

Alessandro (Alex) Orso is the Dean and Professor at the University of Georgia College of Engineering , starting in 2025. Previously, he spent 25 years at Georgia Institute of Technology , where he served as a Professor in the College of Computing , Director of the Scientific Software Engineering Center , and Associate Dean for Off-Campus and Special Initiatives . Education: Ph.D. in Computer Science – Politecnico di Milano, Italy M.S. in Electrical Engineering – Politecnico di Milano, Italy B.S. in Electrical Engineering – Politecnico di Milano, Italy Research Focus: Alex Orso is a leading expert in software engineering , with a focus on software testing , program analysis , and debugging . His work aims to improve software reliability, security, and trustworthiness , and has been validated on real-world systems. He has led initiatives to integrate AI and large language models into testing workflows, particularly for REST APIs and mobile applications . Scientific Recognition: Distinguished Member of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) ISSTA Impact Paper Award (2021) Research Funding & Leadership: Orso has secured major funding from Google, IBM, Microsoft , and government agencies. In 2021, he led the acquisition of $11 million from Schmidt Futures to establish the Scientific Software Engineering Center at Georgia Tech, where he served as inaugural director. Teaching & Innovation: He was an early advocate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) and has taught a virtual software engineering course since its launch in 2014.

• Civil Engineering
• Materials Science
• Structural Engineering
• +3 more

Michael Raupach is a Professor at RWTH Aachen University holding the Chair of Building Materials Science - Building Conservation. His work focuses on concrete durability, reinforcement corrosion, and sustainable construction materials, with particular expertise in alkali-activated binders, carbon textile reinforcement, and electrochemical monitoring systems. Research Interests: Concrete durability, corrosion protection, sustainable materials, structural maintenance, BIM applications, and non-destructive testing. Recent Work: Investigates electrically heated carbon textile reinforced concrete systems, develops hybrid alkali-activated materials for realkalization, and explores chloride diffusion mechanisms in low-carbon binders. Publications: Active in journals covering concrete technology, corrosion engineering, and sustainable construction methods.

• High-Performance Computing
• Computational Fluid Dynamics
• Numerical Analysis
• +9 more

Niclas Jansson is a researcher at the PDC Center for High Performance Computing at KTH Royal Institute of Technology. He holds an M.S. in Computer Science (2008) and a Ph.D. in Numerical Analysis (2013) from KTH. His career spans roles such as postdoctoral researcher at RIKEN Advanced Institute for Computational Science (2013-2016) and visiting scientist at RIKEN (2018-2021), where he contributed to the Japanese exascale program Flagship 2020. A core focus of his research involves extreme-scale computing and numerical method development. He is a key developer of RIKEN's multiphysics framework CUBE , the HPC branch of FEniCS , and the spectral element flow solver Neko . His work is currently supported by a Swedish Research Council Starting Grant aimed at enhancing high-order spectral element methods for exascale fluid simulations. Niclas has published extensively on topics such as GPU acceleration , adaptive finite element methods , in situ visualization , and extreme-scale turbulence modeling . He also teaches Computational Fluid Dynamics (SG2212) at KTH.

Shifali AroraView profile

Assistant Professor

• General Gastroenterology and Endoscopy
• Esophageal Diseases
• Quality Improvement
• +2 more

Shifali Arora, MD is an Assistant Professor of Medicine at the UNC School of Medicine , currently serving as Vice Chief of Clinical Operations for the Division of Gastroenterology and Hepatology. She also holds the position of Medical Director of Gastroenterology Clinics at UNC. Completed AAAS Policy Fellowship and NIH Mobile Health Training Key affiliations: Center for Esophageal Diseases and Swallowing , UNC Hospitals Value Care Action Group , UNC Clinician Leadership Program Research Focus spans three main areas: Quality Improvement in GI care through electronic health record optimization and standardized clinical templates Esophageal Motility Disorders and GI manifestations of systemic diseases Health Policy and Health Informatics including mHealth security and Affordable Care Act implications Scientific Contributions include: Operational innovations in endoscopy scheduling and patient education Clinical research on bowel preparation, pharmacological effects on GI function, and rare disease presentations Education & Training : Undergraduate : University of Illinois at Chicago (Biology & Psychology) Medical School : University of Illinois at Chicago Residency : Duke University Fellowship : Rush University (Gastroenterology & Hepatology) Policy Training : American Association for the Advancement of Science

Kirti RuikarView profile

Associate Professor

• Digital Construction
• Building Information Modeling (BIM)
• Data Science in Construction
• +7 more

Dr. Kirti Ruikar is a Reader in Digital Construction with 19 years of experience, specializing in applying digital technologies like BIM and AI to enhance safety, resilience, and performance in construction and infrastructure projects. She holds a BArch, MSc, and EngD, and is a Fellow of the Higher Education Academy (FHEA). As a University Special Envoy for India, she bridges international collaborations. Her research focuses on BIM integration for site safety and sustainability, Data-driven solutions for infrastructure projects, AI applications in construction safety, Public-Private Partnerships in developing countries, Enterprise systems optimization, and policy interventions in roadworks management. Notable projects include Data Lakes for Indian highways (collaboration with IIT Delhi), BIM-based safety frameworks for staircases and ladders, Social network analysis for knowledge management, and FCDO-funded automated construction safety systems. Her work spans over 150 publications, including 3 books and 50 journal papers, with a strong emphasis on Q1 journals. She has secured £1m+ in funding from Innovate UK, EPSRC, and international bodies. Collaborations include Asite, Arup, and Derby City Council. Her research outputs highlight trends in Industry 4.0 adoption, AI-driven safety systems, and leveraging data lakes for infrastructure resilience. She advocates for ethical innovation and cross-disciplinary collaboration to address global construction challenges.

Hamid KarimiView profile

Assistant Professor

• Social Media Mining
• Educational Data Mining
• Machine Learning
• +3 more

Hamid Karimi is an Assistant Professor of Computer Science at Utah State University (USU), where he leads the Data Science and Applications (DSA) lab. His research focuses on using AI and data mining for social good, including social media mining, educational data mining, and machine learning. He earned his Ph.D. in Computer Science from Michigan State University (MSU) in 2021, with a thesis on AI for social good. His interdisciplinary work includes the Teachers in Social Media project, which developed algorithms to improve PK-12 education quality. Dr. Karimi has received several awards, including the Best Paper Award at ASONAM 2018 and the International Faculty Recognition Award at USU in 2022. His research spans social media behavior analysis, misinformation detection, and fairness in machine learning. The DSA lab prioritizes practical solutions for socially impactful data science applications, such as cross-disciplinary projects in science and engineering. Education: Ph.D. in Computer Science, Michigan State University, 2021 Research Interests: Social Media Mining Educational Data Mining Graph Mining AI for Social Good Lab: Data Science and Applications (DSA) Lab, USU His work bridges theoretical data science with real-world applications, such as analyzing teacher behavior on Pinterest and leveraging GPT for scalable education tools. Dr. Karimi’s research emphasizes ethical AI practices and interpretable machine learning models.

Daphne YaoView profile

Professor

• Cybersecurity
• Program Analysis
• Machine Learning Algorithms
• +3 more

Daphne Yao is a Professor in the Department of Computer Science at Virginia Tech , part of the College of Engineering. She holds the Elizabeth and James E. Turner Jr. '56 Faculty Fellowship and CACI Faculty Fellowship. Her research focuses on cybersecurity, program analysis, machine learning algorithms, and applied cryptography. Yao has contributed to advancing secure coding practices, vulnerability detection in software, and privacy-preserving technologies. Education includes a Ph.D. in Computer Science from Brown University (2007), an M.S. in Computer Science from Indiana University (2002), and earlier degrees in Chemistry from Princeton University (M.A., 2000) and Peking University (B.S., 1998). Her work bridges theoretical computer science with practical applications, emphasizing real-world cybersecurity challenges. Recent research trends include combating ransomware via API profiling, improving privacy in voice assistants, and developing resilient network routing systems. Yao collaborates across disciplines, integrating machine learning into healthcare cybersecurity and epigenomic analysis. Her publications reflect a commitment to measurable, deployable security solutions and ethical AI practices. Key contributions include the CryptoGuard tool for detecting cryptographic vulnerabilities and frameworks like Madeline for low-cost cyber threat monitoring. She has also explored challenges in deploying intrusion detection systems and mitigating data-oriented attacks in cyber-physical systems.

Javier F. MedinaView profile

Professor

• Neural Circuits
• Computational Neuroscience
• Prediction Machines
• +3 more

Javier F. Medina, Ph.D., is a Professor and Brown Foundation Chair in Neuroscience at Baylor College of Medicine. His research focuses on understanding how neural circuits implement supervised learning to make predictions, particularly in the context of motor control and cognitive functions. His laboratory combines experimental techniques such as electrophysiology, optogenetics, and two-photon imaging with computational modeling and artificial neural networks to uncover the computational principles underlying brain function. Education Postdoctoral Fellowship in Neuroscience, UCSF (2007) Ph.D. in Neuroscience, University of Texas, Houston (2000) Bachelor of Science in Computer Science and Physics, Drexel University, Philadelphia (1993) Research Interests Medina’s work integrates computational neuroscience with experimental approaches to study prediction and error correction in neural circuits. His lab investigates how the cerebellum encodes temporal information, processes sensory input, and adapts through learning. Key topics include supervised learning algorithms, neural coding in Purkinje cells, and the role of prediction errors in motor adaptation. Publications His research spans themes in cerebellar circuitry, motor learning, and computational modeling. Recent work includes deep learning strategies for cell-type identification and studies on cerebellar modules for predictive control. Grants & Labs Medina leads a lab at Baylor College of Medicine, focusing on experimental and theoretical neuroscience. His work has implications for motor disorders linked to learning deficits, such as ataxia and Parkinson’s disease.