Elham Rahimi

• Spearheaded the development of deep neural network (DNN) models
to solve a wide range of differential equations, including Ordinary
Differential equations, Partial Differential equations, and systems of
ODE’s and PDE’s.
• Pioneered a new approach to combine multiple DNNs to solve a
single problem, resulting in unprecedented accuracy levels exceeding
known solvers.
• Presented research findings through powerful data visualization tools
like Power BI in conferences and meetings, effectively
communicating complex ideas to diverse audiences.
• Demonstrated exceptional leadership skills by training and mentoring
new team members in Python, R, and SQL

Spearheaded the development of deep neural network (DNN) models to solve a wide range of differential equations, including Ordinary Differential equations, Partial Differential equations, and systems of ODE’s and PDE’s.
Pioneered a new approach to combine multiple DNNs to solve a single problem, resulting in unprecedented accuracy levels exceeding known solvers.
Presented research findings through powerful data visualization tools like Power BI in conferences and meetings, effectively communicating complex ideas to diverse audiences.
Demonstrated exceptional leadership skills by training and mentoring new team members in Python, R, and SQL.

Designed and implemented Python-based simulations for cosmological research, simulating streams of stars for dark matter studies using MobaXterm and PuTTY.
Managed large datasets using supercomputers such as ’Compute Canada’, running and collecting data from thousands of simulations with high efficiency and accuracy.
Analyzed, cleaned, and organized complex datasets using statistical methods and visualization tools, drawing meaningful insights and conclusions.
Collaborated with interdisciplinary teams of physicists and engineers, leading weekly meetings to present and discuss findings and solve challenges together.

Collaborated closely with a team of physicists to analyze and interpret astrophysical data using Python and MATLAB.
Effectively communicated research results to various stakeholders using cutting-edge data visualization software such as Power BI and Tableau.
Collected, cleaned, and managed large data sets in multiple formats, including npy, CSV, HDF5, and GCS files.
Demonstrated exceptional teamwork and problem-solving skills by holding weekly meetings with the team to discuss roadblocks and ensure progress towards goals.
Developed models and algorithms to predict future trends or behaviors.

Spearheaded the development of deep neural network (DNN) models to solve a wide range of differential equations
Pioneered a new approach to combine multiple DNNs to solve a single problem
Presented research findings through data visualization tools like Power BI
Demonstrated exceptional leadership skills by training and mentoring new team members in Python, R, and SQL

Designed and implemented Python-based simulations for cosmological research
Managed large datasets using supercomputers like 'Compute Canada'
Analyzed, cleaned, and organized complex datasets using statistical methods and visualization tools
Collaborated with interdisciplinary teams of physicists and engineers

Collaborated closely with a team of physicists to analyze and interpret astrophysical data
Effectively communicated research results to various stakeholders using data visualization software
Collected, cleaned, and managed large data sets in multiple formats
Demonstrated exceptional teamwork and problem-solving skills by holding weekly meetings with the team