Sarthak Mahapatra
Data Science Associate
New Haven, Connecticut, United States
Summary
👤
Senior🎓
Top SchoolSarthak Mahapatra is a data science professional with nine years of experience who blends academic rigor (MS in Applied Data Analytics, GPA 3.92) with hands-on research and production work in GenAI, ML optimization, and analytics. He has driven efficiency gains across projects—from demonstrating a custom Conjugate Gradient Descent optimizer that reduced training epochs and battery use to deploying dashboards that improved taxi scheduling accuracy and revenue in real-world settings. Comfortable across Python, PyTorch, TensorFlow, SQL, PySpark and BI tools, he moves models from experiments to lightweight, resource-conscious deployments. At Boston University he led teams and comparative studies showing CGD’s benefit over standard optimizers, and now applies that applied-research mindset at Yale as a Data Science Associate. His background in electrical engineering gives him an edge in signal- and sensor-focused ML, evidenced by an 85% accuracy gas-type model and time-series feature engineering work. Colleagues describe him as a data storyteller who builds memorable dashboards and squeezes extra performance out of models when resources are limited.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Technology - BTech Electrical and Electronics Engineering, Bachelor of Technology - BTech Electrical and Electronics Engineering at Delhi Technological University (Formerly DCE)High School Diploma, High School Diploma at Delhi Public School Vasant KunjMaster of Science - MS Applied Data Analytics, Master of Science - MS Applied Data Analytics at Boston University
Github Skills (8)
provisioning2
simulation1
cuda1
gpu-programming1
scheduling1
python1
high-performance1
gpu1
Github contributions (5)
BU-CS-CE-528-2017/HIL-QUADS
Mar 2017 - Mar 2017
Contributions:20 commits, 20 pushes in 15 days
adityanarayan1191/DNA-Sequence-Mapping-on-FPGA
Dec 2016 - Dec 2016
Contributions:5 commits, 5 pushes in 1 day
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