I am a Senior Research Associate at the Institute of Astronomy, University of Cambridge, where I have been since 2020. My expertise spans astrophysics, intensive data science, and advanced computational methods, with a strong focus on developing scalable pipelines and data analysis tools for complex and extensive datasets. I obtained my Ph.D. in Astrophysics from the Institute for Research in Fundamental Sciences (IPM), Iran, in 2016. Prior to joining Cambridge, I held postdoctoral positions at IPM [2016-2018], the Instituto de Astrofísica de Canarias (IAC) [2018-2020], and the University of Oxford [2020-2022].
I am part of the Cambridge Centre of Excellence for Astronomical Data (CAMCEAD), formerly known as CASU (Cambridge Astronomical Survey Unit), where we specialise in processing and analysing large-scale astronomical datasets. My work contributes to multiple astronomical instrumentation projects, including AF2+WYFFOS, INOLA, WEAVE, 4MOST, and MOONS where I have primarily served as the Lead/Senior Developer, focusing on data-intensive processing, AI-driven analytics, and pipeline design/development.
Additionally, I am a member of the Cambridge Centre for Data-Driven Discovery (C2D3), an interdisciplinary initiative at Cambridge dedicated to advancing data science research, machine learning, and AI applications across scientific domains.
Beyond astronomy, I have been involved in medical imaging and data science initiatives, notably the IMAXT project, where our team led the development of data processing pipelines. Currently, I am involved in the Spatial Profiling and Annotation Centre of Excellence (SPACE)—a next-generation initiative built upon IMAXT’s technological advancements. SPACE is part of the Cancer Grand Challenges, a global initiative led by Cancer Research UK and the National Cancer Institute (NCI), bringing together interdisciplinary teams to tackle some of the biggest challenges in cancer research. The project aims to develop a cutting-edge spatial biology platform, enabling researchers to explore tumor microenvironments in 3D with unprecedented resolution. By integrating AI-powered data analysis with large-scale biomedical datasets, SPACE seeks to transform our understanding of cancer progression and therapeutic responses.
My astrophysics-focused research explores observational diagnostics of galaxy formation and evolution, leveraging high-dimensional datasets and state-of-the-art computational techniques.
I specialise in intensive data science, high-performance computing, and AI-driven analytics, ensuring robust and scalable solutions across multi-disciplinary scientific challenges.
