Three ISTA Doctoral Students Win Google PhD Fellowships for Artificial Intelligence

Three doctoral researchers at the Institute of Science and Technology Austria—Riccardo Cadei, Jiale Chen, and Nikita Kalinin—have been awarded Google PhD Fellowships for their innovative work in artificial intelligence. Because European academic institutions are subject to an annual limit of three nominations each, the selection of all three ISTA applicants in this cycle marks an exceptional institutional achievement. The outcome highlights both the high caliber of the research institute’s early-career scientific talent and the overall strength of its artificial intelligence initiatives. Across the international computational community, these highly competitive fellowships are designed to recognize outstanding doctoral candidates whose foundational research in computer science and related disciplines possesses substantial potential to shape the future of technology, delivering direct institutional support to help them advance their ongoing scientific investigations.

Under the terms of the grant announcement, Cadei, Chen, and Kalinin will each benefit from up to $120,000 in research funding provided through Google.org. On an international level, the three ISTA doctoral candidates are among an incoming global cohort of 148 new fellows selected across 38 countries, representing an aggregate funding commitment of $13 million from Google.org. Selection for the fellowship requires a formal nomination submitted directly by a candidate’s home institution, with eligible universities and research centers across Europe and several other regions worldwide strictly capped at three nominations per year. The selection of all three candidates builds upon a continuing institutional tradition at the Institute of Science and Technology Austria, where two other doctoral students had previously secured Google PhD Fellowships during earlier application cycles.

The individual honors awarded to the three researchers reflect distinct specializations across computer science and artificial intelligence foundations. Riccardo Cadei and Jiale Chen were each named recipients of a 2026 Google PhD Fellowship in Machine Learning and ML Foundations, recognizing their contributions to core theoretical models and algorithmic systems. In parallel, Nikita Kalinin was awarded a 2026 Google PhD Fellowship in Privacy, Safety, and Security, reflecting his distinct focus on safeguarding user data within machine learning frameworks.

Riccardo Cadei conducts his doctoral research as an active member of ISTA’s Causal Learning and Artificial Intelligence research group, which is directed by Assistant Professor Francesco Locatello. Cadei’s primary scientific work focuses on explaining cause and effect through the development of algorithms and analytical models capable of identifying and explaining cause-and-effect relationships from complex empirical measurements gathered in scientific experiments.

In developing and evaluating his causal inference algorithms, Cadei engages in interdisciplinary collaborations with scientists across diverse scientific domains, spanning biology, neuroscience, and development economics. His practical investigations explore, for instance, the behavioral effects associated with genetic mutations linked to autism, while also examining why targeted anti-poverty programs provide measurable benefits to some recipients more than others. Cadei joined the Institute of Science and Technology Austria in 2024, having previously studied applied mathematics, machine learning, and causal inference at Politecnico di Milano, EPFL, and Harvard University. Reflecting on the award, Cadei stated that the fellowship gives him the freedom to tackle more ambitious research questions and pursue scientific discoveries with real-world impact.

Working within ISTA’s Deep Algorithms and Systems Lab, led by Professor Dan Alistarh, doctoral student Jiale Chen directs his investigations toward making large language models faster and more efficient. Large language models represent the foundational technical architecture powering modern artificial intelligence assistants, yet these expansive models demand enormous amounts of computer memory and processing power, making their deployment and routine operation exceptionally expensive. To mitigate these operational barriers, Chen develops mathematical methods and efficient algorithms designed to decrease these demanding hardware and computational requirements while rigorously preserving the predictive and operational accuracy of the underlying models.

Chen’s specific algorithmic investigations center on compressing artificial intelligence models and accelerating their computational routines, supporting a broader goal of making powerful artificial intelligence technologies more affordable, energy efficient, and widely accessible across society. Before beginning his doctoral program at the Institute of Science and Technology Austria in 2023, Chen completed his master’s degree at ETH Zurich and earned a bachelor’s degree from Wuhan University. Commenting on the recognition, Chen expressed that the fellowship serves as a wonderful encouragement to continue exploring new ideas for making advanced artificial intelligence both more computationally efficient and broadly accessible to the wider research and user community.

Nikita Kalinin is a fifth-year doctoral candidate in ISTA’s Machine Learning and Computer Vision group, directed by Professor Christoph Lampert, where he focuses his research on privacy-preserving machine learning. Possessing an academic background in applied mathematics and computer science, Kalinin develops algorithmic methods designed to train artificial intelligence models while protecting the personal privacy of users and keeping the resulting models as useful and accurate as possible. This technical research can be applied by technology organizations such as Google that train large-scale computational models on user data, helping them protect individual privacy. Kalinin noted that seeing his research recognized means a great deal and encourages him to strive for even higher quality research in his field.

Subject of Research: Artificial intelligence research and 2026 Google PhD Fellowships

Article Title: Google PhD Fellowships: Triple Success for the Institute of Science and Technology Austria (ISTA)

Article References: Google PhD Fellowships: Triple Success for the Institute of Science and Technology Austria (ISTA). Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: Institute of Science and Technology Austria, Google PhD Fellowships, Riccardo Cadei, Jiale Chen, Nikita Kalinin, Machine Learning, Causal Inference, Large Language Models, Privacy-Preserving Machine Learning, Google.org, Deep Algorithms and Systems Lab, Computer Vision, Model Compression, Francesco Locatello, Dan Alistarh, Christoph Lampert, Algorithmic Efficiency