Manya R.
About Manya R.
Manya R. is a Machine Learning Engineer Co-Op currently working at Cohere Health and a Graduate Research Assistant at Georgia State University. With a strong background in machine learning and data science, Manya has gained experience through various internships and academic roles since 2021.
Work at Cohere Health
Currently, Manya R. serves as a Machine Learning Engineer Co-Op at Cohere Health, a position she has held since 2024 for a duration of 8 months. In this role, she applies her expertise in machine learning and natural language processing to enhance healthcare solutions. Her responsibilities include developing algorithms and models that improve the evaluation of healthcare clinical notes, leveraging her background in exploratory data analysis and advanced machine learning techniques.
Education and Expertise
Manya R. has a strong educational background in computer science. She is pursuing a Master's degree in Computer Science at Georgia State University, expected to complete in 2024. Previously, she earned a Bachelor of Technology in Computer Science Engineering from IIIT-Naya Raipur in 2022. Her studies have equipped her with a solid foundation in machine learning, deep learning, and natural language processing, alongside proficiency in technologies such as TensorFlow, PyTorch, and Keras.
Background
Manya R. began her academic journey at Delhi Public School in India, where she studied from 2006 to 2016. She then attended Vibrant Academy Kota from 2016 to 2018, before pursuing higher education in computer science. Manya has gained diverse work experience through various internships and assistantships, including roles at Georgia State University, Clintx, Teksands.ai, and Cognistx, which have contributed to her practical knowledge in machine learning and data science.
Achievements
Throughout her career, Manya R. has contributed to significant projects, including a classification project focused on solar flares while at Adobe. This project involved handling large datasets and enhanced her skills in data processing and analysis. Additionally, her hands-on experience in evaluating healthcare clinical notes demonstrates her ability to apply machine learning techniques in real-world scenarios, particularly in the healthcare sector.