“Pick one or two areas you’re truly passionate about and go deep. Talk to professors early, build side projects that solve real problems, and don’t hesitate to apply to opportunities even if you feel underqualified.”
Contact Information: anant24@seas.upenn.edu
Degree(s) M.S.E. in Data Science, University of Pennsylvania
Hometown: Delhi, India
What field of Data Science are you interested in?
Natural Language Processing
What drew you to study Data Science at Penn?
The opportunity to work with leading researchers and access real-world datasets through interdisciplinary collaborations across schools made it the perfect environment.
What are some classes that you have particularly enjoyed and why?
Algorithms and computation and Big Data Analytics have been standout courses, each strengthening your fundamentals and equipping you with the skills you need for the industry.
What internships have you had? If you know your post-graduation plans, please include them here.
Currently working as an AI Engineer at GPT Integrators, where I’ve built a full-stack agentic AI assistant with document RAG. Previously, I was a Machine Learning Researcher at Threws, publishing 7 peer-reviewed papers, and a Data Scientist at Ultrafast Tools, improving fraud detection and customer retention. I plan to pursue applied AI roles in product-driven environments post graduation.
What advice do you have for new students?
Pick one or two areas you’re truly passionate about and go deep. Talk to professors early, build side projects that solve real problems, and don’t hesitate to apply to opportunities even if you feel underqualified.
What classes have you taken?
Applied Machine Learning, Big Data Analytics, Human Computer Interaction, Algorithms and Computation, Statistics for Data Science, Python for Data Science and AI.
Share a little bit about yourself.
I began coding in school, took Harvard’s CS50 online in my first year of undergrad, and worked part-time throughout my undergrad while publishing research on medical diagnostics and sustainability. Outside work, I’m Equal parts adrenaline junkie and couch potato, I’ll skydive in the morning, scale a wall by noon, then marathon movies, shows and video games till sunrise. Throw in some dance floors, bar crawls, night clubs, and spontaneous adventures in the woods and you’ve basically unlocked my natural habitat.