Devasenah Rammohan
About Devasenah Rammohan
Devasenah Rammohan is a Senior Data Scientist with expertise in machine learning, natural language processing, and deep learning. He has a strong educational background in Mathematics, Computer Science, and Management Information Systems, along with experience in various data science roles.
Work at Gray Matter Analytics
Devasenah Rammohan has held multiple positions at Gray Matter Analytics. He began as a Data Science Intern from 2019 to 2020, where he gained foundational experience in data science. Following this role, he served as a Data Scientist from 2020 to 2022, contributing to various projects that utilized machine learning techniques. In 2022, he advanced to the position of Senior Data Scientist, where he continues to work in Chicago, Illinois. His current role involves leading projects and research initiatives, particularly in the areas of natural language processing and deep learning.
Education and Expertise
Devasenah Rammohan's educational background includes a Bachelor's degree in Computer Science from Sri Sairam Engineering College, completed from 2013 to 2017. He further pursued a Master's degree in Management Information Systems at the University of Illinois Chicago, graduating in 2020. His academic journey began at St. John's English School and Junior College, where he studied Mathematics and Computer Science from 2000 to 2013. He specializes in building machine learning models and has expertise in natural language processing and deep learning.
Background
Before his tenure at Gray Matter Analytics, Devasenah Rammohan worked as a Software Engineer at Prodapt from 2017 to 2018 in Chennai, India. He also gained experience as a Project Intern at The Joint Commission in the Greater Chicago Area from 2019 to 2020. His diverse background in software engineering and data science has equipped him with a robust skill set applicable to various data-driven projects.
Research and Projects
Devasenah Rammohan is actively involved in research projects that focus on human speech recognition using deep learning and TensorFlow. He has engaged in projects that predict pregnancy outcomes through survival analysis and the Cox regression model. Additionally, he has worked on a project aimed at de-identifying patient information utilizing natural language processing techniques.
Technical Skills
Devasenah Rammohan is proficient in various programming languages, including Python, Spark, R, SQL, Java, C#, and jQuery. He is experienced with machine learning algorithms such as decision trees, random forests, SVM, and regression techniques. His technical toolkit includes library packages like NumPy, Pandas, Seaborn, and TensorFlow, as well as tools like Tableau, MS Power BI, and Google Cloud.