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Department of Computer Science and Technology

  • PhD Student

I am a PhD student in the computer Laboratory, focusing on topics at the interface of stochastic control and inference.


- MPhil in Advanced Computer Science (CS Theory + ML Focus) , University of Cambridge, UK.

- BSc Computer Science (Minor in Physics), The University of Edinburgh, UK.



Overall the nature of my research is predominantly applied and experimental with a particular interest in data assimilation across the natural sciences. Here are some of the main themes I have recently been interested in learning about / exploring:

- Gaussian Processes

- Filtering in SDEs (Kalman-Bucy Filter)

- Dynamic / Entropic Optimal Transport (Schrodinger Bridges)

- Stochastic Control (HJB Equation)

- Computational Bayesian Inference

- Grey Box models (Semi mechanistic modelling / Data assimilation)

- Signal Processing / Kernel Methods 

- ML approaches to formal langauge generation and verification


- Mathematics 1A, Natural Science Tripos, 2020-2021.

- Datascience, Computer Science Tripos, 2020.

- Programing Language Semantics, Computer Science Tripos, 2020

- Undergraduate Research Project, 1 student , 2020-2021

Professional Activities

- Google Deepmind, Research Scientist Intern, Fall 2022

- Google-X, AI Research Intern, Fall 2021

- Amazon Alexa Research, Applied Scientist Intern , Summer 2020

- Babylon Health , Machine Learning Scientist - 2018-2019

- Computational and Biological Learning Lab, University of Cambridge, UK, Research Asistant - 2017-2018

- Blackrock, Site Reliability Engineer, 2016-2017


1. F. Vargas ,  A. Ovsianas, et al. Bayesian Learning via Neural Schrödinger-Föllmer Flows, Fourth Symposium on Advances in Approximate Bayesian Inference, 2022.  

2. F. Vargas , P. Thodoroff, A. Lamacraft, N. D. Lawrence, Solving Schrödinger Bridges via Maximum Likelihood, Entropy 2021, Selected from 139 articles as front cover of the September issue.

3. F. Vargas and R. Cotterell, Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation, EMNLP 2020.

4. S Ravfogel, F Vargas, Y Goldberg, R Cotterell, Adversarial Concept Erasure in Kernel Space. Preprint, under review.

5. H Xuanyuan, F Vargas, S Cummins,  Efficient Representations for Privacy-Preserving Inference. Preprint, under review.

6. DL Fernandes, F Vargas, CH Ek, NDF Campbell, Shooting Schrödinger’s Cat. Fourth Symposium on Advances in Approximate Bayesian Inference, 2022.

7. F. Vargas et al, Multilingual Factor Analysis, ACL 2019.

8. F. Vargas, K. Brestnichki, and N. Hammerla, Model Comparison for Semantic Grouping, ICML 2019.

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