Apurva Mulay is a Machine Learning Engineer with 9 years of software experience and 5+ years focused on ML and research, blending production-grade web and distributed systems with academic rigor. He has built adtech solutions for advertisers, publishers and agencies, and led the creation of the first multimodal COVID-19 fake news dataset, co-authoring a CIKM 2020 paper. His MS research at Syracuse emphasized graph representation learning and GNNs, and his toolset spans Python ML stacks, NLP, active learning, cloud platforms (AWS/GCP/Azure), containerized deployments and full-stack web technologies. Comfortable moving projects from POC to production, he brings both data-science research experience and hands-on engineering discipline, with an eye for data visualization and KPI-driven product impact.
9 years of coding experience
Bachelor’s Degree, Computer Engineering, First class with Distinction, Bachelor’s Degree, Computer Engineering, First class with Distinction at MKSSS Cummins College of Engineering for Women
Master of Science - MS(Research in Machine Learning), Computer Science, Master of Science - MS(Research in Machine Learning), Computer Science at Syracuse University
Contributions:15 pushes, 1 branch in 2 years 8 months
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