Find Academic Supervisors

• Nuclear Engineering
• Fluid Mechanics
• Resources Engineering
• +3 more

Glenn Sjoden is a Professor in the Department of Civil & Environmental Engineering at the University of Utah, specializing in nuclear engineering applications. With degrees including a PhD in Nuclear Engineering from Pennsylvania State University (1997), MS from Air Force Institute of Technology (1992), and BS from Texas A&M University (1984), his research spans computational nuclear engineering, reactor design, radiation transport, and nuclear forensics. His research interests focus on reactor physics optimization, isotope production/separation methodologies, nuclear detection systems, and planetary defense applications. Current investigations examine neutron transport modeling, thermoelectrically cooled detectors, asteroid impact mitigation strategies, and advanced morphological analysis for nuclear forensic applications. Recent publications demonstrate consistent focus on experimental validation of computational models across nuclear engineering domains. Article analyses reveal predominant themes in reactor optimization (32%), radiation detection (27%), isotope production (20%), nuclear forensics (13%), and planetary defense (8%). Methodological approaches emphasize Monte Carlo simulations, spectral matching techniques, and automated image processing algorithms. Laboratory activities include the Utah TRIGA reactor facility where his team conducts experimental validation of neutron imaging systems, radioisotope production, and detector performance characterization under controlled irradiation conditions.

• Cybersecurity
• Privacy
• Child Exploitation Prevention
• +8 more

Dr. Joel Scanlan is a Senior Lecturer in Health Information Management at the Tasmanian School of Business and Economics (TSBE) , University of Tasmania, Hobart. He also holds an adjunct Associate Professor position in maritime cybersecurity at Western Norway University of Applied Sciences (HVL). With a PhD in Network Security and Data Mining from the University of Tasmania, Dr. Scanlan has over two decades of experience in teaching and industry consulting in cybersecurity and privacy. His research is centered on the technical and social harms of the internet, with a strong emphasis on child exploitation prevention, cybersecurity, data privacy, and machine learning . He works in multidisciplinary teams involving psychology, law, and maritime security, contributing to high-impact projects on online safety, CSAM deterrence, and digital interventions. His work has informed policy discussions, including submissions on social media regulation and participation in coalitions like SaferAI for Children. Dr. Scanlan's recent publications highlight trends in AI-driven safety tools , such as chatbots for adolescent support, honeypot experiments for deterring online predators, and digital interventions to prevent child sexual abuse perpetration. His research bridges technical innovation with ethical and social considerations, particularly in balancing privacy and surveillance. Google Scholar : Access via Google Scholar ORCID : 0000-0003-2285-8932 LinkedIn : Professional Profile He has been involved in supervising research students and collaborative projects, particularly in the design and evaluation of online safety technologies. Dr. Scanlan is an active participant in national and international research networks, including the Child Sexual Abuse Reduction Research Network and Te Puna Haumaru Seminar Series in New Zealand. His public engagement includes speaking at conferences such as #AIC2025Conference, contributing to media discussions, and advocating for transparency and accountability in higher education and digital policy.

• Image Restoration
• Blind Deconvolution
• Superresolution
• +5 more

Assoc. Prof. Filip Šroubek, Ph.D., DSc. is a Professor of Applied Mathematics at the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University , and an Associate Professor at the Faculty of Mathematics and Physics, Charles University . He serves as Deputy Head of the Department of Image Processing at the Czech Academy of Sciences. His career spans postdoctoral research at Instituto de Optica (CSIC, Madrid) and a Fulbright scholarship at University of California, Santa Cruz . Education: M.Sc. in Computer Science, Czech Technical University (1998) Ph.D. in Computer Science, Charles University (2003) D.Sc. (Habilitation), Czech Academy of Sciences (2014) Research Interests: Šroubek specializes in image restoration , blind deconvolution , and superresolution , with applications in biomedical imaging, forensic analysis, and mobile device optimization. His work on multi-object tracking and blur-invariant algorithms bridges theoretical and applied computer vision. Publication Trends: His recent articles focus on neural networks for image processing (2025), biomedical imaging (2024), and dynamic object tracking (2021-2023). Collaborations span neuroscience , materials science , and forensic engineering . Scientific Awards: Fulbright Visiting Scholarship (2010/2011) Honorable Mention at GCPR (2019) Outstanding Contribution Award (2013) Advising & Grants: Supervised projects include PIZZARO (forensic image analysis), 4D-STEM/PNBD (electron diffraction), and SONO (ultrasound technology). Grants emphasize interdisciplinary applications of image processing in medicine and engineering. Labs & Teams: Affiliated with the Department of Image Processing (UTIA, Czech Academy of Sciences) , he collaborates with teams in biomedical imaging, quantum dot characterization, and mobile technology optimization.

Kristy MartireView profile

Professor

• Forensic Psychology
• Evidence Evaluation
• Criminal Trials
• +5 more

Professor Kristy Martire is a distinguished academic in the School of Psychology at the University of New South Wales, specializing in forensic psychology and evidence evaluation within criminal justice contexts. Her research bridges psychological science with legal practice, focusing on how lay decision-makers interpret complex forensic evidence. Education: PhD in Forensic Psychology, University of New South Wales, Sydney (2008) Master of Psychology (Forensic), University of New South Wales, Sydney (2008) BA(hons), majoring in Psychology and History, University of Sydney (2004) Professor Martire's research examines the development of expertise, processes of evidence evaluation in criminal trials, and communication between experts and lay decision-makers in forensic settings. Her work employs online crowd-sourcing platforms and electronic questionnaires to assess how evidence characteristics impact belief-updating among international samples of lay decision-makers. She collaborates extensively with legal practitioners, forensic scientists, psychologists, and statisticians to ensure experimental validity and maximize practical implications for the criminal justice system. Her recent publications reveal a strong focus on juror comprehension of statistical evidence, transparent reporting in forensic science, and the psychological mechanisms underlying expertise development. The research consistently addresses critical gaps identified in the 2009 NAS report on forensic science, with particular emphasis on improving the reliability and communication of forensic evidence in legal contexts. Research Funding: ARC Discovery Project (DP220102412) 2022-2024: Misinformation: Evidence evaluation in an alternate fact reality ARC Linkage Project (LP160100008) 2016-2019: Improving the communication of forensic science evidence to courts ARC Discovery Early Career Researcher Award (DE140100183) 2014-2016: Unravelling the golden thread: Presumption of innocence, fair trial, and lay belief change NH&MRC Project Grant (APP1021862) 2012-2015: Reducing smoking in socioeconomically disadvantaged groups Professor Martire actively supervises PhD students interested in forensic evidence validity, lay comprehension of scientific evidence, and expertise development. Her lab culture includes PhD, Masters, and Honours students alongside academics and legal professionals, with weekly meetings to discuss research projects and emerging questions. She teaches courses including Forensic Psychology: Crime, Courts and Corrections (PSYC1027), Psychology & Law (PSYC3301), and Applications of Forensic Psychology (PSYC7402).

Christopher SaundersView profile

Professor

• Statistical learning theory
• Pattern recognition
• Forensic identification of source problems
• +7 more

Christopher Saunders is a Professor of Statistics and affiliate faculty in Natural Resource Management at South Dakota State University (SDSU). He holds a Ph.D. in Statistics from the University of Kentucky, an M.S. in Statistics from the same institution, and a B.S. in Mathematics from California State University, Chico. His professional experience spans roles at The MITRE Corporation, George Mason University, and as a visiting professor at the University of Salzburg. Saunders specializes in statistical learning theory, forensic identification of source problems, and biometric analysis, with applications in forensic science, pattern recognition, and large-scale simulations. His work emphasizes quantitative methods for evidence interpretation, algorithmic bias mitigation, and forensic data validation. Research interests include statistical methods for forensic source attribution, hierarchical data modeling, and the application of machine learning to forensic challenges. Saunders has contributed to foundational studies on error rate assessment in forensic evidence, probabilistic evidence evaluation, and the development of automated systems for handwriting and biometric analysis. His interdisciplinary work bridges statistics, computer science, and forensic science, addressing practical problems in criminal investigations and national security. Educations: Ph.D. in Statistics, University of Kentucky, 2008 M.S. in Statistics, University of Kentucky, 2006 B.S. in Mathematics, California State University, Chico, 2002 Visiting Scientist, FBI Labs Forensic Science Research, 2013 Notable awards include the 2020 Outstanding Researcher Award and 2016 Young Investigator Award from the Jerome J. Lohr College of Engineering. His grants include leadership on NIH-funded projects and collaborations with MITRE Corporation, National Institute of Justice, and other federal agencies. Saunders has advised graduate students in forensic statistics and led teams developing statistical frameworks for evidence interpretation and forensic validation. His research has advanced methodologies for explosive material analysis, handwriting examination, and forensic database design. Current projects focus on algorithmic fairness in forensic systems and improving the accuracy of biometric and trace evidence evaluation through advanced statistical modeling.

Robin MejiaView profile

Research Professor

• Health Disparities
• Health Care Access
• Criminal Justice Statistics
• +4 more

Robin Mejia is an Assistant Research Professor at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences, affiliated with the Department of Statistics & Data Science. Currently on leave during AY 24-25, he holds offices in BH 129D and is based in Pittsburgh, Pennsylvania. His career spans science journalism, documentary filmmaking, and academic research in biostatistics and epidemiology. Education includes a BA in Biology (UC Santa Cruz, 1997), MPH in Epidemiology (UC Berkeley, 2012), and PhD in Biostatistics (UC Berkeley, 2016). His interdisciplinary work addresses health disparities, forensic science methodology, and statistical applications in human rights investigations. Research focuses on: 1) Analyzing health care access disparities during the pandemic through large-scale surveys, 2) Improving forensic laboratory practices via blind proficiency testing, and 3) Statistical methods for human rights casualty estimation. His recent work includes landmark studies on global vaccine hesitancy trends and forensic science reform initiatives. Key Projects: CSAFE Lab Group collaborations, DELPHI Lab pandemic tracking, and statistical methods for forensic validation Publications span epidemiology, forensic science, and human rights data analysis Recipient of 2005 CNN documentary award Advocates for statistical rigor in criminal justice systems and forensic science practices. Active in training forensic professionals and advancing transparent statistical reporting standards.

Åsa Källström CaterView profile

Professor

• Family Violence and Child Welfare
• Child Resilience and Resistance
• Intimate Partner Violence (IPV)
• +3 more

Åsa Källström Cater is Professor of Social Work at Örebro University since 2015, focusing on children's experiences with family violence and resilience factors. She collaborates with researchers in social work, psychology, and criminology across Sweden and the USA. Doctoral Dissertation (2004): Negotiating Normality and Deviation in Children's Perspectives on Father's Violence Docent in Social Work (2013): Early childhood violence exposure analysis Her research spans four key areas: Children's interpretations of paternal violence Risk factors for violence-exposed youth Broad victimization types (physical/emotional/sexual) Ethical research practices with vulnerable children Recent publications examine violence in family subsystems (2019), cognitive disability support barriers (2025), and mentorship programs for unaccompanied migrants (2020). She contributed to international book chapters on: US method implementation in Sweden Interpersonal violence research Peace-building through child protection Active projects include: Post-victimization support matching Intimate partner violence risk management Women abused in childhood (AWARE) Collaborations: Michigan-Örebro IPV Research Network Nordic Child Witness Network COST Cultural Victimology iRiSk Risk Assessment Framework The Violence Hub Outreach Platform

• Operations Research
• Logistics Optimization
• Combinatorial Optimization
• +3 more

Matthias Prandtstetter is an External Lecturer in the Department of Logic and Computation at TU Wien. His research focuses on optimization in logistics, transportation systems, and combinatorial problems. He has contributed to projects such as Algorithmic Discrete Optimization (EU-funded 2004–2008) and MyITS (2011–2013). His work integrates metaheuristics, integer programming, and semantic technologies to address challenges in warehouse logistics, home healthcare scheduling, and document reconstruction. Education: PhD in Hybrid Optimization Methods, TU Wien (2009) Diploma in Exact and Heuristic Methods for Car Sequencing, TU Wien (2005) Research interests include: Logistics optimization Metaheuristics and hybrid algorithms Multi-modal routing systems Document reconstruction from shredded fragments Production scheduling and car sequencing Key projects: Algorithmic Discrete Optimization (EU, 2004–2008) MyITS: Semantically Enriched Multi-Modal Routing (2011–2013) ASP and HEX-Programme (2008–2015) His research has addressed practical applications like cooperative delivery systems, spare parts warehouse routing, and cross-cut document reconstruction. Advising & grants: Supervised 8 students in optimization-related theses Received EU funding for Algorithmic Discrete Optimization Labs/teams: Active in TU Wien's operations research and logistics research groups, collaborating on projects involving semantic technologies and combinatorial optimization.

Horst EidenbergerView profile

Associate Professor

• Multimedia Information Retrieval
• Virtual and Augmented Reality
• Machine Learning
• +6 more

Horst Eidenberger is an Associate Professor at the Technische Universität Wien (TU Wien), affiliated with the Institute for Visual Computing and Human-Centered Technology within the Faculty of Informatics. He holds part-time status at the university. His research focuses on computational perception of audiovisual media, forensic biometrics, multimedia systems, machine learning, and virtual/augmented reality. He leads projects like the Virtual Jumpcube and Vreeclimber hybrid systems, integrating sensory stimuli in VR environments. Eidenberger supervises numerous student theses, covering topics from AI political agents to plant detection with machine learning. He teaches courses on deep learning, VR design, and multimedia retrieval. His work bridges technical innovation with practical applications, including cybersecurity, healthcare, and immersive storytelling. Roles: Associate Professor, Expert Witness in IT/Sigproc, VR Project Lead. Research Interests: Biometric media analysis, hybrid VR systems, optical music recognition, and machine learning. Projects: Vreeclimber climbing wall, Virtual Jumpcube, DeepOMR, and forensic biometrics. Publications span over 50 peer-reviewed articles, emphasizing multimedia retrieval, VR systems, and cognitive modeling. His Handbook of Multimedia Information Retrieval (2012) remains a foundational text. Eidenberger actively mentors students and contributes to interdisciplinary collaborations in AI, HCI, and digital media.

Luca MaianoView profile

Research Fellow

• Computer Vision
• Deep Learning
• Machine Learning
• +7 more

Luca Maiano is a Research Fellow at AlcorLab (Vision, Perception, and Learning Laboratory) within the Department of Computer Science at Sapienza University of Rome. He holds a PhD in Data Science and both bachelor's and master's degrees in Computer Engineering from the same institution. Research Interests: Computer Vision Deep Learning and Continual Learning Media Forensics and Deepfake Detection AI Security and Adversarial Machine Learning Fake News and Disinformation Detection Urban Mobility AI Systems His recent work focuses on detecting synthetic media through multimodal and feature-fusion approaches, adapting models to evolving generative techniques, and securing AI systems against data poisoning. He has contributed to cutting-edge research in deepfake detection, ground-to-aerial image matching, and cooperative urban mobility ecosystems. Recent Publication Trends: His publications from 2024–2025 span top venues in computer vision and AI, showing a strong focus on the security and robustness of AI systems in detecting disinformation. The work integrates deep learning with forensic analysis, emphasizing continual adaptation and multimodal fusion for real-world deployment. Scientific Contributions: Active contributor to media forensics and AI security Published in Pattern Recognition Letters, Computer Vision and Image Understanding, ECIR, IGARSS, and LNCS Guest editor for special issue on disinformation detection Advising and Grants: While no formal students or grants are listed, his role as a research fellow under Prof. Irene Amerini suggests involvement in funded research projects and potential mentorship within the AlcorLab research group. Laboratory Affiliation: Member of AlcorLab (Vision, Perception, and Learning Laboratory) at Sapienza University, a research group focused on computer vision, machine learning, and perception systems.

• Biometrics
• Information Forensics
• Computer Security
• +3 more

Marcel Sébastien is a current researcher at the LIDIAP laboratory within the School of Engineering (STI) at EPFL. His work focuses on biometric systems, information forensics, and security applications. With over 200 scholarly works since 2000, he has contributed to journals like IEEE Transactions on Information Forensics and Security and conferences such as the International Conference on Biometrics. His research emphasizes secure biometric authentication, signal processing for fraud detection, and privacy-preserving technologies. Key areas of expertise include multi-modal biometric fusion, deep learning for template protection, and forensic analysis of biometric data. He has collaborated extensively with institutions like IEL, LTS5, and EDEE at EPFL. Despite no explicit mention of awards, his prolific publication record indicates significant contributions to the field. No formal student advisees or grants are listed in the provided text, though his involvement with LIDIAP suggests leadership in research teams focused on applied computer science and security.

Guru Swaroop BennabhaktulaView profile

Researcher

• Computer Science
• Artificial Intelligence
• Image Processing
• +3 more

Guru Swaroop Bennabhaktula is a Postdoctoral Researcher at the University of Groningen's Faculty of Science and Engineering, affiliated with the Bernoulli Institute. He holds an MSc and has conducted research leading to a doctoral thesis titled 'Leveraging image noise: source camera identification and increased robustness of convolutional neural networks' (2023). His research focuses on computer vision, artificial intelligence, and deep learning with particular emphasis on image forensics, CNN robustness, and sensor pattern noise analysis. He has supervised multiple student theses including projects on camera identification, siamese networks for image retrieval, and noise-resistant neural architectures. Key contributions include the PushPull-Net architecture for robust image classification and video camera identification techniques leveraging sensor noise. His work bridges fundamental computer science research with practical applications in digital forensics and neural network optimization. Award recognition includes the Ben Feringa Impact Award (2023). Bennabhaktula has taught courses like Information Retrieval (2021-2024) and served as teaching assistant for Introduction to Computing Science. His research portfolio features 8 peer-reviewed publications spanning conference papers and journal articles in prestigious venues like Pattern Recognition and Expert Systems with Applications.

• Cryptology
• Intrusion detection systems
• Wireless communication security
• +3 more

Slobodan Petrovic is a Professor of Information Security at the Norwegian University of Science and Technology (NTNU), specifically within the Department of Information Security and Communication Technology (IIK) at the Faculty of Information Technology and Electrical Engineering (IE) in Gjøvik, Norway. His academic career demonstrates a strong commitment to both research and education in cybersecurity disciplines. Professor Petrovic's research interests span across multiple critical domains in information security, with primary focus on Cryptology , Intrusion detection systems , and Wireless communication security . His work consistently bridges theoretical foundations with practical applications, particularly in digital forensics, cryptographic techniques, and network security protocols. The breadth of his research is evident in his extensive publication record spanning nearly two decades. His recent publications (2022-2024) reveal an expanding research scope into emerging security challenges including autonomous vehicle security, 5G network protection for social robots, and physical-layer security implementations for wireless communications. These articles demonstrate his ability to adapt research focus to address contemporary security threats in evolving technological landscapes. Professor Petrovic teaches cryptology and intrusion detection courses at both the Master in Information Security (MIS) program and the PhD program in Information Security at NTNU. He is an active member of the Cryptology Research Group (Norwegian Applied Crypto Lab - NaCl), contributing to Norway's cybersecurity research ecosystem. His collaborative research approach is evident through numerous co-authored publications with researchers including Nguyen Hai Thanh, Katrin Franke, Michael Cheffena Gebresilassie, and others. This collaborative network spans multiple institutions and research domains within information security.

• Operations Research
• Supply Chain Management
• Artificial Intelligence
• +6 more

Ajay Kumar is a prominent researcher and academic with extensive contributions across multiple domains including Operations Research, Artificial Intelligence, Blockchain, and Biometric Recognition. His work spans a wide range of topics, from digital transformation in supply chains to machine learning applications in healthcare and software engineering. He has collaborated with numerous scholars and published extensively in high-impact journals and conferences. Research Interests: Operations Research, AI in Healthcare, Blockchain Applications, Biometric Recognition, Software Reliability, Digital Transformation Publications: Kumar has authored numerous publications in journals like Annals of Operations Research , IEEE Transactions on Engineering Management , and SN Computer Science , as well as conferences such as CVPR and IC3I. Collaborations: Kumar has worked with leading experts like Kim Hua Tan, Shivam Gupta, Seema Bawa, and others, contributing to interdisciplinary research in supply chain, data science, and IoT. Key Contributions: His research includes innovative frameworks such as blockchain-enabled supply chains, hybrid AI models for diabetes prediction, and scalable tools for genomic data analysis. Emerging Trends: Kumar’s recent work focuses on explainable AI, fake news detection, and integrating IoT with blockchain for secure and efficient systems across health, logistics, and UAV communication.

• Biometric Security
• Face Recognition
• Synthetic Data Generation
• +9 more

Christian Rathgeb is a professor at Darmstadt University of Applied Sciences , affiliated with the da/sec Biometrics and Internet Security Research Group . His work focuses on biometric security, template protection, face recognition, and synthetic data applications. Research interests include Privacy-Enhancing Technologies 3D-Aware Face Image Quality Assessment Morphing Attack Detection Demographic Bias Mitigation Contactless Biometric Modalities His recent publications emphasize synthetic data generation, multi-biometric fusion, and forensic applications. Collaborations span institutions like TU Darmstadt, École Polytechnique Fédérale de Lausanne, and University of Vigo. Key projects involve FRCSyn (Face Recognition with Synthetic Data) and MCLFIQ (Mobile Contactless Fingerprint Quality). No explicit awards or student advisement details are provided in available data.