My name is Nanthini, and I'm currently working as a Data Scientist at NVIDIA in the RAPIDS team. I'm passionate about Machine Learning and
data science. RAPIDS is an open-source data science library suite for accelerating data science on GPU.
My responsibilities include profiling existing workflows and finding areas of improvements in the process,
debugging issues that arise as a result of testing on large data and identifying the fix.
I have a Graduate Degree in Computer Science from the University of Pennsylvania, where I focused on Data Science related courses and projects to explore concepts. I was the Teaching Assistant for the Big Data Analytics course for two semesters, the responsibilities of this role included desginging new assignments that would help students strenghten the knowledge of processing large datasets by application, holding office hours to clarify conceptual questions. I was also the Vice-President of the Penn Data Science Group, where we focused on conducting workshops and talks to encourage the interest in Data Science and provide the students of the University with resources to develop their skills.
Apart from coding, I like to read books - philosophy, self-improvement and fiction are my favorite genres. I'm also fond of writing and taking photos. Learning and honing new skills like playing Chess, learning about music and history are also of my interest.
Working on accelerating Machine Learning algorithms with cuDF.
Worked on accelerating Data Science workflows on GPU, as a part of an agile development team RAPIDs. Profiled various workflows like Graph Analytics, Recommendation Systems, and suggested improvements to the codebase in order to improve their performance on GPU.
Courses: Introduction to Machine Learning, Big Data Analytics, Computational Linguistics Data Mining for Large Datasets, Internet and Web Systems, Vision and Learning, Software Systems, Software Engineering.
Courses: Analysis and Design of Algorithms, Data Structures, Object-oriented Programming, System Software, Cloud Computing, Wed Development, Object-oriented Deisgn, Computer Networks, Formal Languages and Automata Theory.