**Angelos Filos** **************** * .---. * * | α +---+ * * '--^' | * * ^ | v * * | | .-----. * * | +-+ | * * | | φ | * * +---+ | * * '-----' * **************** Education =================================================================== 2018–Present : *DPhil Candidate at University of Oxford*, Oxford UK :
_Department of Computer Science_ : - *Supervisor*: Yarin Gal at Oxford Theoretical and Applied Machine Learning (OATML) group. : - *Thesis*: Learning Sequential Strategies Under Non-Stationary Dynamics. : - *Research Interests*: Meta-Reinforcement Learning, Multi-Agent Systems, Online Learning, Imitation Learning. 2014–2018 : *MEng at Imperial College London*, London UK :
_Department of Electrical and Electronic Engineering, top student of the final class list_ : - *Dissertation*: Reinforcement Learning for Portfolio Management (arXiv, GitHub), supervised by Danilo P. Mandic. : - *Courses*: Optimal Control Theory, Signal Processing, System Identification, Mathematics of Machine, Reinforcement Learning. : - *Teaching Assistant*: Multivariate Calculus (EE1-10), Complex Calculus (EE2-08A), Probability Theory and Elements of Statistics (EE2-08B), Semiconductor Devices (EE1-03), Digital Design with Verilog (EE2-LABE), High-Level Programming (EE3-22). 2013–2014 : *Panhellenic Exams*, Athens Greece :
_3rd General Lyceum of Neo Iraklio_ : - Science Stream 19.603/20.000. : - *Courses*: Science Mathematics (20), Science Physics (19.8), Chemistry (19.6), Science Biology (19.8), Elements of Statistics and Probability (19.8), Modern Greek (17.4). Experience =================================================== 2018–Present : *Quantitative Researcher at JPMorgan Chase & Co.*, London UK :
_Part-time employed during DPhil_ : - *Mechanism Design for Fair Markets*: $n$-players differentiable market games with convergence guarantees and fairness. : - *Explicit Opponent Modeling in Auction Markets*: Analysis of the impact of opponent modeling on eponymous auction markets. : - *Learning from Expert Demonstrations to Market Make*: Inverse reinforcement learning for limit order book derivatives trading. : - *Systematic Derivatives Trading*: Portfolio optimization for equity derivative markets. 2017 : *Data Scientist at JPMorgan Chase & Co.*, London UK :
_Six months internship_ : - *Anomaly Detection*: State-space time-series modeling for automated regime-switching and anomaly detection. : - *Implied Volatility Prediction for Illiquid Assets*: Predictive modeling with conditional Generative Adversarial Networks (GANs) for forecasting implied volatility for illiquid assets, using financial indicators (e.g. fundamental factors). : - *Analytics Platform*: Data visualization & monitoring platform build on web technologies and GitHub Electron. 2017-2018 : *Head of Talent Development at Imperial College Data Science Society* :
_Volunteering work_ : - *Workshops*: Demystifying Artificial Intelligent concepts and teaching practical skills. : - *Mentoring*: Leading and training the Imperial Advanced Data Science Team, participating in Hackathons and partnering with industrial sponsors to provide intelligence in their problems. 2016 : *Mixed Signal Engineer at Dialog Semiconductor*, Swindon UK :
_Summer internship_ : - *Asynchronous Design*: Functionally described the operation of a legacy PMIC Buck Converter digital controller. Implemented a new digital controller using Petrify and MPSAT asynchronous logic design. Functionally verify the operation of the controller using UVM. Publications =============================================================== + *Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?*
*Angelos Filos*♮, Panagiotis Tigas♮, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal.
_Under review_.
Paper + *Invariant Causal Prediction for Block MDPs*
Amy Zhang♮, Clare Lyle♮, Shagun Sodhani, *Angelos Filos*, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup.
_arXiv preprint arXiv:2003.06016_.
Paper + *Robust Imitative Planning: Planning from Demonstrations Under Uncertainty*
Panagiotis Tigas♮, *Angelos Filos*♮, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal.
_Machine Learning for Autonomous Driving NeurIPS 2019 Workshop_.
Paper + *A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks*
*Angelos Filos*, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal.
_Spotlight at Bayesian Deep Learning NeurIPS 2019 Workshop_.
Paper Code + *On the Importance of Opponent Modelling in Auction Markets*
Mahmoud Mahfouz♮, *Angelos Filos*♮, Cyrine Chtourou, Joshua Lockhart, Samuel Assefa, Danilo Mandic, Tucker Balch, Manuela Veloso.
_Robust AI in Financial Services NeurIPS 2019 Workshop_.
Paper + *Generalizing from a few environments in safety-critical reinforcement learning*
Zachary Kenton, *Angelos Filos*, Owain Evans, Yarin Gal.
_SafeML ICLR 2019 Workshop_.
Paper Blog + *Towards Inverse Reinforcement Learning for Limit Order Book Dynamics*
Jacobo Roa-Vicens, Cyrine Chtourou, *Angelos Filos*, Francisco Rullan, Yarin Gal, Ricardo Silva.
_Contributed Talk at AI in Finance: Applications and Infrastructure for Multi-Agent Learning Workshop at ICML 2019_.
Paper Open Source =================================================================== bdl-benchmarks
ML Benchmark : Bayesian deep learning benchmarks with a transparent, modular and : consistent interface for the evaluation of deep probabilistic models. qtrader
Algo Trading : Reinforcement learning for portfolio management. : MEng dissertation at Imperial College London, supervised by Danilo P. Mandic. Service ================================================================== Conference Workshop Organizing ------------------------------------------------------------------ - Multimodal Brain Tumor Segmentation (BraTS) Challenge @ MICCAI 2019 - Emergent Communication: Towards Natural Language @ NeurIPS 2019 Program Committees and Reviewing ----------------------------------------------------------------- - Bayesian Deep Learning @ NeurIPS 2018 - International Conference on Machine Learning (ICML) 2019 - BrainLes @ MICCAI 2019 - Conference on Neural Information Processing Systems (NeurIPS) 2019 - Bayesian Deep Learning @ NeurIPS 2019 - International Conference on Machine Learning (ICML) 2020