Divye Singh
About Divye Singh
Divye Singh is a Senior Application Developer specializing in AI and machine learning at Thoughtworks, with a strong background in statistical modeling and machine learning techniques. He has previously worked at various institutions, including the Centre for Modeling and Simulation and QuEST Global, and holds degrees in Aerospace Engineering and Mathematical Modelling.
Work at ThoughtWorks
Divye Singh has been employed at ThoughtWorks as a Senior Application Developer specializing in AI and Machine Learning since 2019. His role involves leveraging advanced machine learning techniques to develop applications that meet client needs. With a focus on innovative solutions, he applies his extensive knowledge of statistical modeling and machine learning algorithms to enhance project outcomes.
Previous Experience in Engineering and Research
Before joining ThoughtWorks, Divye Singh worked at several notable institutions. He served as an Engineer at QuEST Global from 2015 to 2017, where he contributed to engineering projects in Bengaluru. Additionally, he completed a summer internship at the Indian Institute of Science Education and Research (IISER) in Pune in 2018. His early experience includes a master’s student role at the Centre for Modeling and Simulation at Savitribai Phule Pune University from 2017 to 2019.
Education and Expertise
Divye Singh holds a Master of Technology (M.Tech) in Mathematical Modelling and Simulation from Savitribai Phule Pune University, where he studied from 2017 to 2019. He also earned a Bachelor of Technology (B.Tech) in Aerospace, Aeronautical and Astronautical Engineering from SRM University, completing his degree in 2014. His educational background provides a strong foundation in statistical modeling techniques and machine learning.
Technical Skills and Specializations
Divye Singh possesses a robust skill set in machine learning and statistical modeling. He is proficient in various algorithms, including regression techniques, support vector machines (SVM), random forests, and clustering methods such as k-means and density-based clustering. He has hands-on experience with time series forecasting and stochastic optimization techniques, which enhance model selection processes.
Research Interests
Divye Singh is interested in exploring graph-based approaches to address data and knowledge modeling challenges. His research interests align with his expertise in unsupervised machine learning techniques, particularly in clustering neuronal activity data, which reflects his commitment to advancing the field of AI and machine learning.