Sep 2021: 1 paper (poster) accepted to NeurIPS 2021! Sep 2021: 1 new talk on Contextual Reinforcement Learning is available online! Sep 2021: 1 new talk on the Foundations of Data Augmentation is available online! Sep 2021: I will be speaking at the 5th IPM Advanced School On Computing & Artificial Intelligence (2021) about Learning Context Variables in Contextual Reinforcement Learning! Sep 2021: I will give a talk on the Foundations of Data Augmentation at the Amirkabir Artificial Intelligence Summer Summit (AAISS) 2021! Aug 2021: I will be presenting my research on Causal Contextual Reinforcement Learning at the International Interdisciplinary Computational Cognitive Science Summer School! July 2021: 1 journal paper published! May 2021: My research proposal has been accepted to Graphcore Academic Programme! April 2021: 1 paper accepted to SSL-RL ICLR 2021 workshop! March 2021: I have been selected to join the inaugural cohort of Google Cloud Research Innovators (see the news item)! March 2021: Our submission to the Network Anomaly Detection Challenge (NAD2021) achieved the 8th place! March 2021: Received a grant from Google Cloud Credit Research Program for my research project CaRL ($5,000).
Dec 2020: New blog post is out! Nov 2020: Giving a public lecture at CP Lecture series. Nov 2020: 1 paper accepted at Pre-register NeurIPS 2020 workshop. Nov 2020: Received a grant from Google Cloud Credit Research Program for my research project DEVs ($5,000). Sep 2020: Giving an invited talk at the Software Competence Center Hagenberg (SCCH) Open Research Club . Sep 2020: Giving an invited talk at the Cyber-Physical Systems Group, TU Wien. Sep 2020: Attending the Workshop on Equivariance and Data Augmentation. Aug 2020: Attending the Theory of Reinforcement Learning Boot Camp. Aug 2020: I'll be speaking at the Amirkabir Artificial Intelligence Summer Summit (AAISS) 2020. Jul 2020: Attending the Microsoft Research Frontiers in Machine Learning 2020 virtual event. Jul 2020: New preprint on arXiv: On Data Augmentation and Adversarial Risk: An Empirical Analysis. Feb 2020: 1 paper (oral) accepted to "Towards Trustworthy ML:Rethinking Security and Privacy for ML" (ICLR 2020 Workshop).