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Summary:

I am an Atmospheric Scientist with strong mathematical, statistical and programming background. I have 5+ years of working experience in modelling, data analysis and visualization. I am passionate about machine learning and deep learning. I primarily use Python programming language including NumPy, Xarray, Pandas, Scikit-Learn, Matplotlib, NLP, and TensorFlow. However, I am proficient in other languages (e.g. Octave, Matlab, R, SQL, JavaScript and Fortran) as well. I have an excellent understanding of AWS cloud computing system. I strongly believe that learning is a never ending process which always motivates me to be a enthusiastic learner. I enjoy taking challenges, in particular, solving real-world problems that bring a real-change in our communities.

Experience:

As a Research Scientist at the BC ministry of health, I am working on the impacts of climate change on health. I am also teaching Atmospheric and Oceanic Sciences at the School of Environment and Sustainability, Royal Roads University, Victoria, Canada. Recently, I worked on a project “Fight hunger through machine learning-based crop classification” in Uganda where I led the exploratory data analysis (EDA) working group mainly working on extractions, transformations and visualization of data. Previously, I worked as a Research Associate at the Tyndall Center for Climate Change Research, The University of Manchester, UK. At the Tyndall Center, I worked on various projects from grant proposal writing to research and coordination. In particular, I led a project MITAC which was developing a contrail-climate model to quantify the impacts of aviation-induced pollution on climate. Prior to joining the Tyndall Center, I worked as a Climate Modelling Scientist (2013-2018) in the Natural Sciences and Engineering Research Council (NSERC) funded projects at the Canadian Center for Climate Modelling and Analysis (CCCma), the University of Victoria, Canada, where I worked on numerical modelling and statistical analysis of climate, air pollution and vegetation including publications of the results in peer-reviewed journal articles. During my PhD research at Manchester, I led the Himalayan Aerosol Cloud Interaction (HACI) field experiment which was conducted to monitor air quality in the foot-hills of the Nepal Himalayas. The HACI field experiment was complemented by a high-resolution modelling study to model the impacts of air pollution on regional climate. I am actively involving reviewing academic papers from ERL, Climate Policy and MDPI journals.

Credentials:

I have received PhD degree in Atmospheric Science from the University of Manchester, UK, and MSc degree in Environmental Science from the UNESCO-IHE, the Netherlands. The degree programs were fully-funded by the Dorothy-Hodgkin Post-graduate Scholarship Program and the Netherlands Fellowship Program, respectively. I have obtained bachelor’s degree in Civil Engineering from Institute of Engineering, Kathmandu, Nepal. Recently, I have successfully completed a 11-week online Machine Learning course offered by the Stanford University and 4-week Natural Language Processing (NLP) course.

Certifications

Other Links

Rudra Shrestha's Projects

cloud icon cloud

The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.

cnrcwp-project icon cnrcwp-project

As a part of Canadian Network for Regional Climate and Weather Processes (CNRCWP) project, I developed the Fortran codes which disaggregate 6-hourly meteorological data to half-hourly values.

computer-science icon computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

corona_tscs icon corona_tscs

This is the raw data repository (policy record format) of the CoronaNet project on government responses to the COVID-19 pandemic.

cts-smallarea icon cts-smallarea

A tutorial on the case time series design for small-area analysis

data-science icon data-science

:bar_chart: Path to a free self-taught education in Data Science!

deepsentinel icon deepsentinel

Deep learning pretrained model on satellite imagery (Sentinel-2)

elucidate icon elucidate

convenience functions to help researchers elucidate patterns in their data

globsim icon globsim

Using global reanalyses for permafrost simulation

haci-project icon haci-project

Himalayan Aerosol Cloud Interaction (HACI) Project aims to improve our understanding the impacts of climate change over the foothills of the Himalayas using state-of-the-art modelling technology and ground-based observations.

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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