LEAD AI Fellows
Meet the postdoctoral fellows who are a part of LEAD AI. The program is still recruiting fellows, and this list will be updated continously when new fellows join.
Hovedinnhold
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| Alexander Wolf is a postdoctoral fellow within the LEAD AI program at the Department of Biomedicine. He obtained his doctoral degree in computational drug design from the Free University Berlin in 2025. His doctoral research focused on the in silico investigation of various cancer-related targets to aid in the development of small-molecule inhibitors of increased affinity and improved selectivity. His LEAD AI project revolves around validation and application of de novo drug design tools with particular focus on generative AI-based algorithms to explore uncharted chemical space and ultimately design novel antibiotics. |
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| Priyanka Mehra is a Postdoctoral Fellow in the Department of Clinical Science at the University of Bergen and part of the LEAD AI Fellows programme. She obtained her PhD in Microdata Analysis from Dalarna University, Sweden, in 2025, where her research investigated how genetic interactions--epistasis and pleiotropy--shape the evolutionary dynamics of biological systems. In her doctoral work, she developed a computational framework extending the traditional NK fitness landscape model by decoupling these genetic properties from ruggedness, allowing them to evolve independently. This work provided new insights into how robustness (resistance to mutations) and evolvability (capacity to adapt) emerge under static and dynamic environments. Her current research focuses on leveraging machine learning to predict and understand female reproductive disorders such as polycystic ovary syndrome (PCOS), preterm birth etc, with the goal of advancing precision medicine in women’s health. |
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Kathrin Trattner
| Dom Ford is a postdoctoral fellow with the Center for Digital Narrative and the Department of Linguistic, Literary and Aesthetic Studies. His LEAD-AI project looks at nonplayer characters in digital games with AI-generated dialogue, how players respond to the use of this technology and how this use may challenge ideas in the philosophy of fiction like intentionality. Previously, he was a postdoctoral research at the University of Bremen working on digital games and community. He received his PhD in 2022 from the IT University of Copenhagen, where he worked on myth as a framework for understanding how games make meaning. His first book, Mytholudics: Games and Myth (De Gruyter, 2025), is based on that project. |
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| Miguel Neves is a seismologist joining the Department of Earth Science at the University of Bergen. His main goal as a LEAD AI fellow will be to implement deep learning techniques in the Norwegian National Seismic Network monitoring workflow to improve the detection and characterization of seismic signals. Before coming to Bergen, he did a first postdoc at GeoAzur in France using machine learning to enhance the recordings of a low-cost citizen run seismic network in Haiti. Prior to that, he pursued his Ph.D. at Georgia Tech in Atlanta, US, where he focused on refining earthquake catalogs for various regions to uncover insights on the faults generating the earthquakes and how earthquakes interact with each other and with external triggers. |
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UiB, Randi Heggernes Eilertsen
| Tian Bai obtained his PhD from the University of Electronic Science and Technology of China in 2024 and was a Postdoctoral Fellow at the University of Hong Kong from 2024 to 2025. His research lies at the intersection of parameterized and approximation algorithms, algorithmic game theory, and artificial intelligence. As a LEAD AI fellow in the Algorithms Research Group at the University of Bergen, his work focuses on fundamental computational problems that arise in AI systems, by introducing social parameters, encompassing incentives, fairness constraints, and behavioral biases. His research provides theoretical foundations and efficient algorithmic solutions for basic AI tasks such as robust ranking, strategic learning, and trustworthy mechanism design. |
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| Elise Perrotin completed her PhD at the University of Toulouse in 2021 and has done postdocs in CRIL (Lens, France) and AIST (Tokyo, Japan) before coming to the Department of Informatics at the University of Bergen. Her research topics encompass logical representations of and planning with theory of mind, with a focus on the trade-off between expressivity and efficiency. Theory of mind is the ability of agents, including people, to reason not only about the physical world but also about other agents' mental states, in particular their knowledge and beliefs. Being capable of theory-of-mind reasoning is essential in order both to achieve efficient collaboration between agents (machine or human) and to formally ensure protection of information in adversarial situations. |
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UiB, Randi Heggernes Eilertsen
| Gorka Abad is a Postdoctoral Fellow in the Department of Informatics at the University of Bergen and part of the LEAD AI Fellows programme. He obtained his PhD in 2025 at Radboud University, Nijmegen (the Netherlands), where his research focused on the security of deep learning systems. During his doctoral work, he studied how adversaries can compromise machine learning models through techniques such as backdoor attacks, and how these vulnerabilities can be detected and mitigated. His current research interests lie at the intersection of deep learning and cryptography, where he explores how cryptographic techniques can be used to secure machine learning models, ensuring the trustworthy deployment and usage of AI in real-world applications. |
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| Ermes Franch has a PhD in coding theory and cryptography from UiB. He is joining the Selmer Center as a postdoctoral researcher, investigating the intersection of cryptography and artificial intelligence. His research focuses on the security of neural network models, with a particular emphasis on model stealing attacks using differential cryptography techniques. By leveraging concepts from coding theory and cryptography, he aims to analyze vulnerabilities in AI systems and develop methods to enhance their robustness. As part of his research, he will visit Leuven University in Belgium. |
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| Robin Guillaume-Castel is from France, and is a LEAD AI postdoctoral fellow in Climate Science. In December 2024, he joined the Geophysical Institute of the University of Bergen and the Bjerknes Center for Climate Research. He is working on understanding future changes in extreme rainfall events using machine learning methods with Drs. Camille Li and Stefan Sobolowski. Before coming to Bergen, he completed his PhD in Toulouse, where he was focusing on understanding the general physics behind global warming and climate change. |
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| Jessa Henderson completed a Ph.D. in Human-Technology Collaboration with George Washington University. Prior to her Ph.D., Dr. Henderson spent a decade as a public-school teacher in the US where she taught high school social studies courses and, later, mentored teachers in areas of educational technology. Her research interests include topics of AI in education focusing on human agency and decision-making during human-computer interactions, the impact of GenAI on academic research, and pathways of responsibility and accountability for AI systems in education. Dr. Henderson is honored to be a part of the initial LEAD AI cohort with the Centre for the Science of Learning and Technology (SLATE) at the University of Bergen. |
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| Lisa Haarer works in the field of Medicinal Chemistry and she did her PhD at University of Tuebingen focusing on the synthesis of covalent inhibitors targeting protein kinases. As a part of LEAD AI Lisa Haarer will do her research at the Department of Chemistry, where she and her research group work on new chemical molecules to treat diseases, especially infectious disease. With the rise of antibiotic resistance, bacterial infections are predicted to become a main cause of death (again). Therefore, the need for new antimicrobial treatment options is increasing, to overcome the resistance and maintain the current health standards. The aim of her research project is to identify new chemical structures that can be used to treat bacterial infections. Therefore, they will design, synthesize and test new promising molecules. |
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UiB
| Lars M. Salbu has a PhD in Mathematics with a focus on foundations of Topological Data Analysis (TDA) from UiB. As a LEAD AI fellow he is joining the Machine Learning Group at the Department of Informatics working with Nello Blaser. His research concerns questions about the foundation of machine learning with a special focus on topological and geometrical methods. A main focus is the study of Reeb graphs as a way of reducing the dimensionality of complex data, and the development of approaches to find properties of the data from properties of these graphs. Lars also applies machine learning methods to TDA and explores their robustness. As part of the LEAD AI fellowship, he will visit the University of Seville in Spain. |