Piyush Pandita
Staff Engineer at GE Aerospace
Cambridge, Massachusetts, United States
Summary
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Senior🎓
Top SchoolPiyush Pandita is a Staff Engineer in Cambridge, MA with 11 years of experience building probabilistic and machine learning systems for high-impact engineering domains. He designs agentic AI frameworks and scalable probabilistic models that translate field data into reliable fleet-level forecasts and cost projections for aerospace applications. At GE Research he led development of Bayesian and sequential experimental-design methods and production Python tooling used across aviation and manufacturing projects; he now applies those skills to high-throughput field-data ML at GE Aerospace. With a PhD from Purdue focused on Bayesian design and non-stationary processes, he combines deep theoretical expertise with hands-on software engineering and a track record of turning expensive experiments and simulations into efficient, decision-ready insights. An unexpected throughline in his career is early practical exposure to manufacturing and lean processes, giving him a pragmatic systems viewpoint when moving models from research to operations.
11 years of coding experience
5 years of employment as a software developer
High School, High School at St Anne's Convent School, ChandigarhDoctor of Philosophy (PhD), Research on Novel Probabilistic Approaches for Stochastic Optimization and Bayesian Active Learning, Doctor of Philosophy (PhD), Research on Novel Probabilistic Approaches for Stochastic Optimization and Bayesian Active Learning at Purdue UniversityBachelor of Engineering (Honors), ENGINEERING, Bachelor of Engineering (Honors), ENGINEERING at Punjab Engineering College
Stackoverflow
1reputation
0reached
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Github Skills (4)
bayesian8
gaussian-processes7
python6
pymc2
Programming languages (2)
Github contributions (5)
piyushpandita92/pydes
Sep 2018 - Dec 2019
Contributions:36 commits, 42 pushes, 1 branch in 1 year 3 months
piyushpandita92/bode
Oct 2018 - Jan 2022
Bayesian Optimal Design of Experiments
Contributions:1 release, 19 commits, 1 PR in 3 years 4 months
bayesian
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