AI PhD & Postdoc Spring Symposium
Juni 12 - 13:00 - 17:30
Mondai | House of AI is happy to host AI PhD & Postdoc Spring Symposium, together with the TU Delft AI Initiative and the AI PhD Committee!
(De voertaal van dit event is Engels)
Are you a PhD or postdoc researcher at TU Delft working on AI-related topics? You are cordially invited!
We are excited to announce the next edition of the Spring Symposium dedicated to the AI PhD & postdoc community, including the yearly Poster Event! Hosted on June 12th (13:00 – 17:30) at Panorama XL@Mondai | House of AI, the event includes poster pitches, an interactive panel discussion on interdisciplinary publication, keynotes from final year PhDs, and the ever-important borrel. It’s an excellent opportunity to present your research and network with fellow AI-focused scholars across campus.
Programme (preliminary) 13:00 – 17:30
- Keynotes & talks from final year PhDs working in/with AI at TU Delft
- Panel discussion on interdisciplinary research & publications
- Poster market: You are invited to contribute to this event with your own poster! See poster requirements on below. Final deadline for participating with poster: June 4th
The afternoon session will end in a casual manner with drinks, refreshments and an opportunity for networking. More details to be announced so keep an eye on this page for more updates on speakers and panellists.
Posters
Researchers at all stages of their PhD and working in all different areas of AI are welcome:
- Machine learning and foundational AI techniques
- Human-centered AI systems
- Application of AI
- Fairness, bias, legal, and ethical considerations of AI
- Education and AI
- Design with AI
- Reflexive and critical research on AI
- And more…
Requirements
- A0 size – printing available via AI Initiative
- PDF (Portrait mode, 300 DPI)
- The reuse of existing A1 or A0 posters is allowed
- Submissions can be made via the registration form available on this page
Register & submit your poster by Wednesday, 4 June.
Any questions? Please contact the AI PhD Committee at AI-PhD-Committee@tudelft.nl
Speakers
Keynotes & talks from final year PhDs
Alexander Garzón is a final-year Ph.D. candidate at the AIdroLab, at the intersection of AI and water engineering. Over the past few years, he has been developing machine learning models—mainly graph neural networks—to help simulate drainage infrastructure more efficiently. In this talk, he will share some of the highs and lows from his PhD journey, the tools that made a difference, and what he wishes he knew when he started.
Shenglan Du is a last-year PhD candidate from the Architecture faculty. She has a background in remote sensing and Geo information science from Wuhan, China. Her research interests include deep learning for 3D data analysis, 3D segmentation, and 3D modelling.
Vera van der Burg is a designer and researcher pursuing her PhD at the Technical University in Delft’s Designing Intelligence Lab, where she challenges conventional AI narratives by repositioning these systems as reflective tools rather than mere optimization machines. Viewing AI as a material to be disentangled and explored, she emphasizes annotation and training phases as spaces for designers to examine their own practices and subjectivities. Through publications, workshops, talks, and installations, she reveals AI’s potential to create productive friction in creative processes, reimagining human-AI interactions beyond automation.
Carolina Centeio Jorge (pronunciation [kɐɾulˈinɐ] [sẽ tˈɐju] [ʒˈɔɾʒɨ]) is a PhD candidate in the Interactive Intelligence, focusing on mental models in the context of human-AI teams. Her goal is to enable interactive and intelligent agents (e.g., robots) to understand their human teammates and respond to them transparently and effectively. Specifically, she has been investigating the concept of artificial trust in decision-making within human-AI teamwork, particularly in modelling context-dependent human trustworthiness for collaboration scenarios.
Panel on AI-related interdiscplinary research & publishing
Panelists
The aim of this panel is to give insights in AI-related interdisciplinary research. It can be challenging to find the right conferences or journals to publish such work, for example because it is difficult to completely fit in one corner of the research scope. Join us to learn from the experiences of our panelists in finding suitable outlets for publishing AI-related interdisciplinary work, finding the right narrative styles based on your audience (when facing people from either of two disciplines), and related research challenges.
This panel is moderated by Fatemeh Mostafavi (PhD at AiDAPT Lab and Faculty of A+BE) and other members of the AI PhD Committee
Jie Yang is an assistant professor at TU Delft and the manager of the ICAI Lab GENIUS on Generative AI development and usage in large organizations. Before joining TU Delft, Jie was a scientist at Amazon (Seattle) and a senior researcher at the University of Fribourg (Switzerland). His research interests span computer science, AI ethics, and human-computer interaction, with a focus on developing human-centered computation for robust AI systems, especially for natural language processing (NLP) systems. His work has received six “best paper” awards or nominations at premier AI and information systems conferences, including ACM TheWebConf/WWW (both 2022 and 2023), AAAI/ACM AIES (2023), AAAI HCOMP (2022), ACM SIGIR (2024), and ACM HT (2017). His work finds application across a wide range of societal domains, via collaboration with medical centers, libraries, and industrial companies, and funded through national and international projects. Jie serves as an associate editor for the Journal of Human Computation and Frontiers of Artificial Intelligence, and regularly serves on the senior program committees of TheWebConf/WWW, AAAI, and CIKM.
Cristina Zaga is an Assistant Professor of Human-Centred Design group and DesignLab at the University of Twente. Cristina’s research aims to develop methodology to foster societal transitions towards justice, care, and solidarity. She has developed Responsible Futuring, a transdisciplinary approach to imagine future worth wanting and foster more-than human communities of belonging. She is currently working on approaches to Design for Resistance to contest and re-imagine the future of work and care with robots and AI. She leads the JEDAI network, a transdisciplinary collective, working towards mitigating the dehumanizing effects of AI and promoting social and environmental justice. Her award-winning work has received many accolades, including the NWO Science Price for DEI initiatives (2022), the Dutch High Education Award (2022), and the Google Women Techmaker Award and scholarship (2018). She was selected as top 3 Diversity Leaders in AI in the Netherlands.
Martin Sand works as an Assistant Professor of Ethics and Philosophy of Technology at TPM. He is interested in a broad range of topics from technological utopianism and justice to the problems of responsibility and moral luck in innovation. His work falls uncomfortable between philosophy and ethical research, Science and Technology Studies, Utopian Studies and Technology Assessment.
Seyran Khademi is an Assistant Professor at the Faculty of Architecture and the Built Environment (ABE) at TU Delft, where she also serves as co-director of the AiDAPT Lab. Her interdisciplinary research integrates computer vision into architectural design, focusing on how data and deep learning can be applied to architectural representations—including drawings, renders, photographs, 3D models, and maps. In 2020, she was awarded a Research-in-Residence Fellowship at the Royal Library of the Netherlands, where she developed visual recognition tools for the children’s book collection. Prior to that, in 2017, she joined the Computer Vision Lab as a postdoctoral researcher on the ArchiMediaL project, developing computer vision and deep learning methods for the automatic detection of buildings and architectural elements in archival and street-view imagery. Seyran earned her Ph.D. in statistical signal processing and optimization from TU Delft in 2015. She continued her postdoctoral work in intelligent audio and speech algorithms before joining the computer vision lab. She holds an MSc in Signal Processing from Chalmers University of Technology in Gothenburg, Sweden, awarded in 2010.
Luciano Cavalcante Siebert is an assistant professor at TU Delft’s Faculty of Electrical Engineering, Mathematics, and Computer Science (INSY department/Interactive Intelligence group). His research focus is on Responsible Artificial Intelligence. Luciano serves as the director of technology at the the Centre for Meaningful Human Control and co-director of the AiBLE lab. His interdisciplinary research aims to develop practical methods to ensure AI remains under meaningful human control. By integrating ethical and human behavior theories, Luciano proposes interactive approaches that enable agents to elicit and align with human values and norms, while empowering humans to maintain control and responsibility.
Arkady Zgonnikov is an interdisciplinary cognitive scientist specializing in cognitive modeling of human behavior in human-robot interactions, with a particular focus on automated driving. He earned his MSc in Applied Mathematics from Saint Petersburg State University in 2009 and his PhD in Computer Science and Engineering from The University of Aizu in 2014. His early research concentrated on the mathematical modeling of intermittent motor control in human operators. In 2015, Arkady joined the Department of Psychology at the University of Galway as an Irish Research Council Postdoctoral Fellow, where he studied the response dynamics of decision making. In 2017, he returned to The University of Aizu to explore the interplay between decision making and motor behavior. In 2019, he joined the Department of Cognitive Robotics at Delft University of Technology as a postdoctoral researcher and was promoted to assistant professor in 2020. Arkady’s current research aims to understand human cognition in traffic interactions through both mathematical and data-driven modeling. He is deeply concerned with the ethical and societal impacts of robotics and AI technology, striving to develop concrete methods that empower humans to meaningfully control artificial intelligent systems.
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