Dr. Amanda Kis

Course: Introduction to Python 2

Amanda is an instructor in the University of Oklahoma’s School of Meteorology and adjunct faculty in the Department of Mathematics. She teaches a variety of non-major and major courses as well as business calculus. Additionally, she developed a series of scientific writing workshops for undergraduate researchers with the National Weather Center Research Experience for Undergraduates program and runs them during summer. In all her work, Amanda aims to help students build confidence in and enjoyment of math and science.

Amanda received her B.S. in atmospheric & oceanic sciences as well as mathematics from the University of Wisconsin and her M.S. and PhD in meteorology from OU. She initially researched nocturnal tornadoes and later studied the career of meteorology.

Sujata Sahu

Course: Data Management in R

Sujata is a dedicated Master’s student pursuing her studies in Data Science and Analytics at the esteemed University of Oklahoma. With over six years of valuable experience as a Data Analyst, she has contributed her expertise to several multinational companies. Currently, she is engaged as a Research and Teaching Assistant, where her focus lies in conducting research and supporting educational endeavors. Her thesis centers on utilizing machine learning algorithms to analyze LMS (Learning Management System) data and predict student retention in courses. This research holds significant importance in the field of education as it aims to enhance the understanding of factors influencing student success and aid in the development of strategies to improve course retention rates.

Nasrin Akter

Course: Introduction to Python: Part 1

I am currently pursuing a PhD in Electrical and Computer Engineering at University of Oklahoma. Prior to that I have completed a Bachelor in Electronics and Telecommunication engineering , and a master’s in computer science and engineering.

My research journey has been driven by a passion for projects encompassing classification, predictive modeling, digital signal processing, biomedical signal processing, and image processing. Spanning over 8 years, my versatile experience has ranged from roles as a Machine Learning Consultant to a Network Operation Coordination/Transmission Engineer, all of which have cultivated my passion for teaching and research. Proficient in Python, C/C++, MATLAB, and deep learning frameworks like Keras and TensorFlow, I also possess expertise in various networking technologies and data visualization tools. As a machine learning individual contractor at a non-profit organization, my ongoing research focuses on developing data-driven tools using machine learning for hearing loss treatment, reflecting my commitment to making a meaningful impact in the real world.

McKenna Burns

Course: Introduction to Genes and Evolution, Intro to Python Part 2

McKenna is a PhD candidate in the Physiological Ecology Laboratory at Miami University. She studies integrative biology where stress physiology, adaptation, and gene expression meet. She has worked with multiple state and federal agencies during her dissertation work.

Anil Upreti

Course: Gene Expression

Anil is a PhD candidate at the University of Miami, Ohio and is a member of the Developmental Genetics of Vertebrate Eye Development Lab. He studies genetics, transcriptomics, and developmental biology, specifically the role of FOXE3 in eye development and differentiation.

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Paula Cimprich (She/her)

Course: Introduction to R, Part 2

Paula is a PhD Candidate in Biology at the University of Oklahoma. She studies migration behavior, in particular, bird migration through the lower atmosphere using high resolution GPS tracking tags.

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