# Rami P. > Trying to build something useful Location: New York City Metropolitan Area, United States Profile: https://flows.cv/ramip I am passionate about leveraging cutting-edge technology to solve complex problems and deliver impactful results in a collaborative team environment. ## Work Experience ### Software Engineer, Founding Team @ ConductorAI Jan 2024 – Present | New York, New York, United States AI for getting to yes ### Teaching Fellow @ Yale University Jan 2024 – Jan 2024 | New Haven, Connecticut, United States Teaching Fellow for Database Systems. In charge of designing, releasing, and grading programming assignments for students. Assignments covered embedded sql, normalization algorithms, indexing, deadlock detection, and serializable schedules ### Teaching Fellow @ Yale University Jan 2023 – Jan 2023 | New Haven, Connecticut, United States Teaching Fellow for Probability Theory. Topics include probability spaces, random variables, expectations and probabilities, conditional probability, independence, discrete and continuous distributions, central limit theorem, Markov chains, and probabilistic modeling. ### Lead Software Engineer @ Zinnia Health Jan 2022 – Jan 2024 Led all product engineering development for Zinnia Health, managing a team of up to 10 engineer over multiple product development lifecycles. Products included innovative AI solutions, complex healthcare workflows translated into internal tools, and SEO & marketing website work. ### Software Engineer @ Zinnia Health Jan 2022 – Jan 2022 Built and managed a team of Engineers through the launch of new internal tools for company metrics, analytics, and insights ### Software Engineer @ Cognex Corporation Jan 2022 – Jan 2022 | Natick, Massachusetts, United States - Worked on the advanced vision team to develop cutting edge embedded deep learning solutions ### Associate Software Engineer @ Cognex Corporation Jan 2020 – Jan 2022 | Greater Boston - Built the pipeline for connecting machine vision sensors from the factory floor to the the cloud in C# - Worked on the advanced vision team to run experiments on R&D deep learning solutions (Python) - Developed flask API that allowed for R&D deep learning solutions to be tested by and presented to internal users and upper management - Assessed different internal deep learning solutions and their effectiveness to appropriately market products and prevent cannibalization - Performed market research to determine upcoming product positioning and placement for deep learning technologies ### Space Systems Design Studio Research Assistant @ Cornell University Jan 2020 – Jan 2020 | Ithaca, New York, United States Applied deep learning to develop a general state-estimation method for relative kinematics applicable to spacecraft missions that involve multiple environments. The network draws upon the abilities of scene-representation and normalizing-flow neural networks to learn conditional, implicit, domain representations in a feed-forward manner. Given a known context scene, an inversion of a trained network creates state measurements, i.e. position and attitude, of the spacecraft relative to its scene. The network evaluates on simulated mission scenarios of spacecraft operating in close proximity to small bodies, such as asteroids. ### Teaching Assistant @ Cornell University Jan 2020 – Jan 2020 | Ithaca, New York, United States Teaching assistant for ECE 3100: Probability and Inference for Random Systems and Signals. Topics: - Probability models (countable and uncountable sample spaces) - Combinatorics, - Discrete/Continuous random variables - Expectation and variance - Independence and correlation - Conditioning and Bayes rule - Concentration inequalities - Limit theorems (law of large numbers, central limit theorem, etc) - Monte Carlo methods - Random processes - Statistical inference ### Student Researcher @ Cornell University Jan 2019 – Jan 2019 | Ithaca, New York Area Characterized evaporation ducts within the marine atmospheric boundary layer using Gaussian process regression. Additionally, built a binary classifier for classifying whether a set of propagation factors came from evaporation or surface ducts ## Education ### Master of Science - MS in Statistics and Data Science Yale University Jan 2022 – Jan 2024 ### Bachelor of Science - BS in Electrical and Computer Engineering, Mathematics Cornell University Jan 2016 – Jan 2020 ### High School Diploma South Anchorage High School Jan 2012 – Jan 2016 ## Contact & Social - LinkedIn: https://linkedin.com/in/rpellumbi --- Source: https://flows.cv/ramip JSON Resume: https://flows.cv/ramip/resume.json Last updated: 2026-03-23