About

Bhuvan Malladihalli Shashidhara is a Senior Applied Scientist at Microsoft with a passion for data science and computing technologies. He is an expert in transforming data into insights to develop innovative products, with a particular interest in the Advertisements, Healthcare, and Sustainability domains. Bhuvan enjoys working in interdisciplinary teams, where he can apply his data science and software engineering skills to build creative products and services. During his 5.11 years of relevant experience, Bhuvan has explored various aspects of computer vision, natural language processing, machine learning, and parallel and distributed computing. He is always eager to explore new domains and a variety of data, enabling him to discover creative applications. Bhuvan's current role at Microsoft as a Data and Applied Scientist II involves working in the COSINE Data Intelligence R&D team. He has also served as a Data Scientist Intern, where he explored and assessed deep learning methods for a problem with an extremely high dimensional sparse categorical feature space. His insights helped in deciding the scope of deep learning methods in rolling out Windows 10 updates. Bhuvan's past experience includes working as a Graduate Student Research Assistant at the University of Washington's Applied Physics Lab, where he worked on generating photo-realistic synthetic image data for augmenting object detection models. He also worked on CamHD Video Analysis, where he developed a hybrid convolutional neural network architecture to perform instance segmentation of deep-sea macro-fauna. Bhuvan published a research paper in WACV 2020 conference, demonstrating the impact of such an autonomous system in creating large-scale marine population data. Bhuvan holds a Master of Science degree in Data Science from the University of Washington and a Bachelor's degree in Information Technology from the National Institute of Technology Karnataka. He is skilled in various technologies, including Python, TensorFlow, Spark, Databricks, OpenCV, and neural networks.