2021

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).

2020

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).

2019

Nov 2019: Giving an invited talk at the Intelligent Autonomous Systems Group of the Computer Science Department of the Technische Universitaet Darmstadt.
Oct 2019: Awarded the travel grant for the DL/RL summer school in Edmonton, Alberta, Canada by Amii (Alberta Machine Intelligence Institute).
Jun 2019: Successfully defended (Passed with Distinction) my PhD dissertation entitled "Representation Learning and Inference from Signals and Sequences".
July 2019: Attending the CIFAR's DL/RL Summer School in Edmonton, Alberta, Canada.
Jun 2019: Ranked 3rd in the DCASE-2019 Challenge, Task1.B (acoustic scene classification under distribution mismatch).
Jun 2019: 1 paper (poster) accepted to CVPR 2019!

2018

Sep 2018: 1 paper (oral) accepted to NeurIPS 2018, workshop of Interpretability and Robustness in Audio, Speech and Language!
Sep 2018: 1 paper (poster) accepted to NeurIPS 2018, workshop of Bayesian Deep Learning.
Jun 2018: My research has been featured in Der Standard magazine.