Kenny X. Van

Astrophysics PhD Graduate

University of Alberta

About

Hi I’m Kenny and I have a passion for analytics and machine learning. I recently graduated with a Ph.D from the University of Alberta under the supervision of professor Natalia Ivanova. My research involved using a numerical simulations, statistical analysis and data visualization to model stellar systems resulting in numerous scientific publications. Throughout my graduate research I gained experience in machine learning, data analysis, and high performance computing. I am currently looking to start a career in data analytics or machine learning.

Image from Jakub Ostrowski Photography.

Interests

Machine learning
Data Analysis
Data Visualization

Skills

Stellar Simulations

I have extensive knowledge in using and modifying the stellar evolution code MESA. My research has used this code since the beginning of my Master’s research, and I have been a teaching assistant for a graduate level course requiring the use of the code and at the MESA summer school itself.

Data Visualization

Using Python and its modules such as matplotlib, numpy and pandas I can create clear and useful figures from the huge quantity of data produced by simulations. I also have experience in creating scientific posters to present my research at conferences through powerpoint and LaTeX. Examples of these posters and figures can be found in my research

Scientific Computing

I regularly use modifications made to MESA written in Fortran to test different physical systems. I have experience in using and making changes to scientific codes as well as diagnosing issues involved in this process. In addition to familiarity with scientific programming languages I frequently use the high performance compute provided by Compute Canada to do research.

Education

PhD Student

University of Alberta

Sep 2017 – Aug 2021 Canada

The current research builds upon the work done during my MSc and expands on the magnetic braking prescriptions tested. For current results see the publications in the publication section

MSc Student

University of Alberta

Sep 2015 – Aug 2017 Canada

Working under professor Ivanova, my thesis was ‘Select Topics in Mass Transfer and Magnetic Braking’. This work focuses on the stability of mass transfer in low mass X-ray binary systems with a neutron star accretor and the effects of magnetic braking.

Projects

Titanic - Machine Learning from Disaster

A Jupyter notebook predicting if a passenger survived.

Game of Thrones Kill Dashboard

An interactive dashboard showing Game of Throne Kills

Tableau Sales Map

Tableau Dashboard showing sales informationa cross the USA

House Prices - Advanced Regression Techniques

A Jupyter notebook analyzing housing prices.

Neighbourhood Analysis

Edmonton neighbourhood analysis using Python and FourSquare

Flower Classification on TPU

Classifying flower images using Python

Featured Publication

K.X. Van, N. Ivanova

September 2019 ApJl

Evolving LMXBs: CARB Magnetic Braking

We derive and introduce a new magnetic braking scheme which can effectively reproduce a sample of well studied observed LMXBs.

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Recent Publications

Evolving LMXBs: CARB Magnetic Braking

We derive and introduce a new magnetic braking scheme which can effectively reproduce a sample of well studied observed LMXBs.

K.X. Van, N. Ivanova

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Low-mass X-ray binaries: the effects of the magnetic braking prescription

A study of the most commonly used magnetic braking prescription and how effectively this prescription can reproduce observed LMXBs. We definitively show that the most commonly used prescription fails to reproduce observed systems and should not be used.

K.X. Van, N. Ivanova, C.O. Heinke

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Low-mass X-ray binaries: the effects of the magnetic braking prescription

Formation of Black Hole X-Ray Binaries with Non-degenerate Donors in Globular Clusters

Showed that there is a range where mass transfer from massive giants onto a black hole is stable. This significantly reduced the simulated BH-BH binary formation rate to fall in line with LIGO observations.

N. Ivanova, C. A. da Rocha, K. X. Van, J. L. A. Nandez

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