About

Suryateja Mudimi is an experienced Senior Data Scientist with expertise in machine learning based product development. He is currently working at Tiger Analytics, where he has been working for several years, and has previously held positions as a Data Scientist at the same company and as Lead of the Data Science Team at TCS. Suryateja has a Master's Degree in Mechanical Design from the Indian Institute of Technology, Madras, and has a strong skillset in the data science stack Python. He has a total of 8.28 years of relevant experience in the field. Throughout his career, Suryateja has worked on a variety of projects, including developing a near real-time streaming data processing engine, web back-end, and online machine learning serving engine for the steel industry. He has also developed a hybrid algorithm for temperature soft sensors based on process events using physics and data science for Ladle furnace and RH-DeGasser, using GradientBoosting, PLSRegression, LSTM+NN, and CNN. Additionally, he has developed a recommendation engine for suggesting operational parameters that use optimum energy without compromising on the quality of output, using GeneticAlgorithm, NSGA-III, and particle swarm optimization. Suryateja has experience in building energy management solutions, and has developed an energy forecasting algorithm for buildings that is used in measurement and validation (M&V) of energy-saving calculations and automated energy consumption alerts. He has also collaborated with TCS Research Labs to develop an industrial chiller scheduling solution that suggests optimal operational parameters for optimal energy consumption, using generalized linear models. Overall, Suryateja is a skilled and experienced data scientist with a strong background in machine learning and product development. He is passionate about using his skills to develop innovative solutions that help companies optimize their operations and improve their bottom line.