About

Tanmay Kulkarni is a highly skilled and motivated individual with a strong background in computer science and machine learning. He is currently pursuing his Master of Science in Computer Science at Carnegie Mellon University, where he is working as a Research Assistant. Tanmay has a proven track record of success in his field, with over 1 year of relevant experience. Tanmay's expertise lies in the areas of Deep Learning, Computer Vision, and Causality in Machine Learning. He is passionate about data-driven decision-making and has a deep understanding of how data can be used to make tangible business decisions. At Carnegie Mellon, Tanmay has been experimenting with different transformer-based backbones for Semantic Segmentation and researching and analyzing various approaches for unsupervised domain adaptation. He has also applied prompt engineering to language and image-text models, further showcasing his technical proficiency. Prior to his current role, Tanmay worked as a Software Engineer at Microsoft, where he deployed an event-based concurrency model for ensuring consistency across Teams meetings. He also developed a controller for Directory Service API, which handled batching and parallel requests with a 99.9% availability rate. Tanmay also configured and deployed monitors to test the availability of deployed services and developed an HTTP Retry Client to improve the stability of service-to-service communication. Before that, he worked as a Software Engineer Intern at Microsoft, where he ported the Document Library within Microsoft Teams to ReactJs from AngularJs and integrated telemetry to monitor service performance. Tanmay holds a Master's degree in Economics and a Bachelor's degree in Computer Science from Birla Institute of Technology and Science, Pilani. He is proficient in various technologies, including Research Scientist, ML, Object detection, Android, Tensorflow, and more. Tanmay is a highly motivated individual with a passion for technology and a drive to succeed. He is always looking for new challenges and opportunities to learn and grow in his field.