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The Outstanding Female Doctoral Student Prize honors one exceptional Ph.D. student each year for her scientific achievements and contributions to the research community.
Birgül Akolpoglu, a doctoral student with Metin Sitti in the Physical Intelligence Department at MPI-IS and at ETH Zurich, won the 2023 Outstanding Female Doctoral Student Prize, a new award initiated by the Max Planck Institute for Intelligent Systems as part of its Gender Equality Plan. In addition, four students received honorable mentions: Martina Contisciani, Nihal Olcay Dogan, Zhijing Jin, and Lea Müller.
The Outstanding Female Doctoral Student Prize honors one exceptional Ph.D. student each year for her scientific achievements and contributions to the research community. The winner receives up to €2,000 to support career-building activities of her choice, such as attending a workshop or conference. A scientific selection committee decides on the winner and the honorable mentions, taking particular care to avoid conflicts of interest with the nominees and their advisors. The 2023 selection committee consisted of Ulrike Cress, Katja Schenke-Layland, and Ingo Steinwart. The winner and the honorable mentions were announced by Katherine J. Kuchenbecker and Leila Masri at the MPI-IS Summer Colloquium on July 14, 2023. The other members of the prize organizing committee were Gunther Richter, Hadiseh Safdari, and Alona Shagan.
"This recognition means a lot to me," says Akolpoglu. "I am truly humbled to be among such accomplished colleagues. I would like to thank the award organizing team for their extraordinary efforts in creating a platform that highlights and celebrates the achievements of female Ph.D. students in our institute. Increasing the visibility of underrepresented groups and promoting gender diversity in academia is a prerequisite for success, and I am honored to have been part of this initiative. I would also like to extend my warmest congratulations to the recipients of the honorable mentions; it is great to share this recognition with such talented individuals."
Birgül Akolpoglu's research focuses on microalgae and bacteria-based microswimmers for medical applications such as on-demand drug delivery. She combines biological agents with synthetic materials to create microrobots that could one day revolutionize the way we diagnose and treat diseases in hard-to-reach areas deep inside the body. The field of medical microrobotics holds great potential to successfully combat a wide range of diseases. Birgül's work in using miniature biohybrid robots with different active control mechanisms and medical functions is an important step in finding new ways to fight cancer, for example. Her research is helping advance this paradigm shift in approaches to medical treatment.
Birgül earned her master's degree in Chemical and Biological Engineering from Koç University in Istanbul, Turkey, where she did research with Prof. Seda Kizilel. Specifically, she studied the biocompatible coating of insulin-secreting pancreatic islets with emulsion-based microgels for the treatment of type I diabetes. Before that, Birgül completed her bachelor's degree in Chemical Engineering at Istanbul University, where she graduated second in her class with a GPA of 3.81/4.00.
Beyond her academic pursuits, Birgül is also part of a start-up venture called "CELLnROLL." Their mission is to create advanced cell-sorting devices that utilize a combination of microrobotics and microfluidics, enabling clinicians to make quick and well-informed decisions. The concept of CELLnROLL originated from the Ph.D. thesis of Birgül's colleague, Dr. Ugur Bozuyuk. In collaboration with another colleague, Dr. med. Erdost Yildiz, the team took part in a bootcamp hosted by MAX!mize, the official start-up incubation program of the Max Planck Society, this year in March. They pitched their idea to a jury and secured project funding of €50,000.
In all of these settings, Birgül knows the value of teamwork, and she takes pride in helping out her colleagues. Her academic strengths are amplified by her outstanding leadership skills. She is also committed to her scientific community, taking the initiative to organize events and previously serving as a Ph.D. student representative on the Max Planck campus in Stuttgart.
"Birgül is a truly worthy winner of the 2023 MPI-IS Outstanding Female Doctoral Student Prize," says Katherine J. Kuchenbecker. "On top of her outstanding research and publications, I am especially impressed with her entrepreneurial achievements and her campus leadership. I'm so glad we could honor Birgül Akolpoglu with the inaugural version of this award! However, it's important to note that the selection committee had a difficult time choosing a single winner from the sixteen nominees. They thus awarded honorable mentions to four other outstanding female doctoral students in MPI-IS."
The recipients of the honorable mentions are:
Martina Contisciani, a doctoral student with Caterina de Bacco in the Physics for Inference and Optimization Group at MPI-IS, has a background in theoretical and applied statistics and is now working on the analysis of network data using statistical tools – so-called statistical inference on network data. In particular, her work on community detection has been widely cited and has received considerable attention in the field. She has developed novel algorithms and models for community detection in complex networks, leading to important applications in areas as diverse as social network analysis and biological networks. Her work has laid the theoretical foundations for three substantial lines of research: first, by incorporating metadata into multilayer networks; second, by handling complex dependency structures in standard latent variable models; and third, by introducing scalable and theoretically grounded probabilistic models for hypergraphs, structures with higher order interactions that generalize networks. She earned her master's degree in Data Science and her bachelor's degree in Statistics for Business and Economics from the University of Padua in Padua, Italy.
Nihal Olcay Dogan is a doctoral researcher with Metin Sitti in the Physical Intelligence Department and at ETH Zurich. Her research aims to improve the capabilities of medical microrobots by introducing a personalized medicine approach. She combines patient-derived biomaterials with microrobots for cancer treatment: she uses blood plasma, blood proteins and immune cells as patient-derived biomaterials to fabricate immune-responsive microrobots for medical applications. By using biomaterials that the body recognizes as its own to make microrobots, these microrobots can perform their intended tasks with excellent efficiency and without side effects. Her pioneering work represents a significant advancement towards in vivo medical applications of mobile microrobots by implementing a personalized medical treatment approach. Nihal received her master's degree in Chemical and Biological Engineering from Koç University in Turkey, where she studied chitosan-based carriers for drug and gene delivery applications to one day battle cancer. In 2019, she received the "Academic Excellence Award" from Koç University for her outstanding academic performance among all graduate students. She earned dual bachelor's degrees in Chemical Engineering and Molecular Biology and Genetics from Istanbul Technical University in Turkey.
Zhijing Jin, a doctoral student with Bernhard Schölkopf in the Empirical Inference Department at MPI-IS and at ETH Zurich, is working on the causal reasoning abilities of Large Language Models (LLMs). Zhijing is broadly interested in making natural language processing systems more useful to humans. Specifically, she uses causal inference to improve the robustness and explainability of LLMs, and to make language models more aligned with human values. Previously, Zhijing received her bachelor's degree from the University of Hong Kong, during which she spent semesters at MIT and National Taiwan University. She was also a research intern at Amazon AI. In 2022, Zhijing became a Fellow of The Future of Life Institute. She received a grant to conduct research on the safe development and deployment of AI. Also in 2022, Zhijing was awarded the Open Philanthropy Ph.D. Fellowship. She and the other fellows were selected for their academic excellence, technical knowledge, careful reasoning, and interest in making the long-term, large-scale impact of AI a central focus of their research.
Lea Müller is a Ph.D. student with Michael Black in the Perceiving Systems Department at MPI-IS. Her computer vision research focuses on social touch: how people interact using a learned generative model of human "proxemics", i.e., how people behave in close proximity. For example, Lea created a training set of high-quality 3D poses of people touching each other, and used them to train a novel diffusion model that can synthesize 3D people interacting – a problem that is largely unaddressed in computer vision. In another project, Lea worked on estimating accurate body shape from an image of a person in arbitrary clothing. To do this, she took a novel approach and collected a dataset of images of people with linguistic shape attributes such as 'slim', 'pear shaped', 'round', 'feminine', etc. She did the same for 3D scans of people with known body shapes and built a regressor from attributes to shape parameters (and vice versa). The resulting method was published at CVPR 2022 and was a candidate for the prestigious best paper prize. She earned her master's degree in Computational and Data Science from Friedrich Schiller University in Jena, Germany, and her bachelor's degree in Mathematics with the application subject of Psychology from Ruprecht Karls University in Heidelberg, Germany.