I am a PhD candidate at the Artificial Intelligence Research Centre, at City, University of London. Currently, I am developing machine learning algortihms for forecasting renewable energy output, specifically on applications for Probabilistic Microgrids optimization, under the supervision of Eduardo Alonso and Dimitra Apostolopoulou.
Before starting my PhD, I was involved in both academia and industry. I worked as a researcher for Iran Power Transmission, Generation and Distribution Company (TAVANIR). I am experienced with different industrial software such as CYMDIST, DIgSILENT, ArcGIS, AutoCAD, NEPLAN, DIALux as well as academic software such as MATLAB and GAMS.
I am also a graduate teaching assistant for different modules such as Mathematics in Computing, Operating Systems, Systems Architecture, Introduction to Algorithms, Power System Design and Engineering Mathematics at City, University of London.
I have published in the International Journal of Electrical Power and Energy Systems, the Proceeding of 12th International UKACC Conference on Control (CONTROL2018), the Proceedings of the IEEE PowerTech 2021 Conference, Energy and Energy Conversion and Management.
I am a PhD candidate at the Artificial Intelligence Research Centre, CitAI at City, University of London, working on computer vision for medical image analysis under the supervision of Giacomo Tarroni and Aidan Slingsby. I work on algorithms to learn medical images representations without using labels (i.e. unsupervised and self-supervised) and with limited labels (semi-supervised) and applications of these algorithms for the detection and segmentation of anomalies and organs. I have a vested interest in problems related to unsupervised learning such as compression, image generation and transfer learning and, given that medical images are generally high-dimensional, I am also researching on data efficient sparse image representations such as point cloud or implicit fields learning.
Before starting my PhD I completed a MSc in Data Science in City, University of London and worked for more than 10 years in consulting supporting businesses on analytics and forecasting projects. In my free time I enjoy reading, cooking, travelling and scuba diving.
I have published my research on unsupervised anomaly detection in conference papers such as IEEE International Symposium on Biomedical Imaging (ISBI 2021) and Medical Image Computing and Computer Assisted Interventions (MICCAI 2021). I also achieved 2nd and 3rd positions in the Medical Out-of-Distribution Challenge held at MICCAI 2020.