Lindau Nobel Laureate Meeting (2016)

Research fellow at the University of Oxford. Arrykrishna did his PhD at Imperial College London, where he was working in Statistical Machine Learning. During his PhD, his research was based on building emulators using Gaussian Processes for accelerating computations in Cosmology. He is also keen to address global challenges in sustainability using Machine Learning.

He has an avid passion for technology and zealous to learn new tools. Since his background is in Physics, he is passionate about solving problems in a meticulous and principled way, which will benefit the community at large. In the same spirit, Mathematics, the universal and common language amongst scientists and engineers, allows him to develop a deep understanding of the topics he is interested in. When he is not doing research, he enjoys reading and watching soccer.

"You can't connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future." - Steve Jobs

Academic Background

2017 - 2021: PhD in Physics (Imperial College London)

He did his PhD at the Imperial Centre for Inference and Cosmology, ICIC, working with Prof. Alan Heavens, Prof. Andrew Jaffe and Dr. Florent Leclercq on weak lensing, data compression and Gaussian Processes.

2015 - 2016: MSc in Astrophysics and Space Science (University of Cape Town)

Prior to joining Imperial College, he did a Masters in Astrophysics and Space Science at the University of Cape Town. In 2015, after completing the coursework component of NASSP (National Astrophysics and Space Science Programme), he did the research part (which was based on radio astronomy and Bayesian Statistics) at AIMS under the supervision of Prof. Bruce Bassett and Prof. Martin Kunz.

2011 - 2014: BSc (Hons) Physics with Computing (University of Mauritius)

From 2011 to 2014, he did his undergraduate study in Physics with Computing at the University of Mauritius where he worked on the analysis of X-ray cavities (see here) with Dr. Somanah and Dr. Oozeer.

Professional Experience

Research fellow (University of Oxford)

His work is related to developing computational methods which will accelerate Bayesian Inference for current and future cosmological surveys. Moreover, he is also working on probabilistic techniques to infer redshift distributions of galaxies for weak lensing surveys.

Postdoc Researcher (University of Oxford)

His research is focused on using Machine Learning techniques for finding unusual objects in the universe.

Consultant - Data Science (Metrixs)

His work at Metrixs focused on developing Machine Learning algorithms for analysing consumers' data. In parallel, he also worked on testing and verifying an analytical model for investigating psychometric data.

Consultant - Data Science (Voxcroft Analytics)

At Voxcroft, he was involved in two projects related to Natural Language Processing. The first project involved the analysis of Twitter data while the second project was on speech-to-text analysis.

Consultant - Data Science (Arcturus ESG)

His work was primarily focused on developing a methodology for rating companies. He also had the opportunity to work on a diverse set of problems including the development of a dynamic model, name-matching algorithm, web scraping, Natural Language Processing and geospatial data analysis using Computer Vision.

Lead Data Scientist (Vensy)

Much of his work at Vensy was to investigate a Twitter database in order to understand the engagement rate of atheletes, which eventually helps in driving the business forward.

Data Scientist (Gimmer)

Part of the RnD team, working on predictive analysis and statistics, to build both data pipelines and machine learning algorithms to produce insightful metrics while designing ways to integrate these algorithms as tools within an automated crypto-trading platform.

Private Tutor (Mauritius)

Taught Mathematics, Physics, Additional Mathematics and Further Mathematics to more than 150 O-Level and A-Level students in Mauritius over a course of 4 years (2011 to 2014).