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djpalumb/README.md

David Palumbo

Education:

  • Computer Science BS - University at Buffalo, Dec 2021
  • Computer Science MS - Columbia University, Dec 2023

Professional Experience

Lasertron, Buffalo, NY

Lead Project Developer -- May 2023 – Present

  • Spearheaded development and direction as sole developer for arcade style racing game utilizing Unreal Engine
  • Oversaw entire development cycle from concept to release, placing a priority on an enjoyable family experience
  • Coordinated with artists and designers to supply a modern and natural user experience

Computer Vision Intern -- Mar 2022 – Aug 2022

  • Led team of four to research and engineer a computer vision system to automate scoring for axe-throwing games
  • Utilized OpenCV framework interfacing with Intel Realsense cameras to capture and process both RGB and depth data
  • Integrated pre- and post-processing algorithms to reduce data noise and increase accuracy and reliability

Embedded Systems Intern -- May 2020 – Aug 2020

  • Utilized Microchip/Atmel real-time embedded microprocessors in C, for hardware components used in laser-tag
  • Developed interrupt-driven software for timing and serial communication between different components
  • Optimized function execution time in resource scarce development environment

MOOG Inc., East Aurora, NY

Machine Learning Intern, Innovation Team -- May 2021 - Aug 2022

  • Constructed an image classification pipeline with OpenCV and Tensorflow for factory part quality control
  • Engineered OCR system to streamline handwritten file organization and search process, drastically reducing manual task
  • Altered Azure Synapse PySpark pipeline to automate data and error logging, increasing debugging efficiency
  • Collaborated with multiple teams, participating in agile development processes to deliver IT projects

Academic Project Experience

Decision Transformer (DT) Model Boosting -- Feb 2023 – May 2023

  • Investigated recent development in transformers, conventionally applied in NLP, for reinforcement learning problems
  • Implemented custom transformer and DQN models, for problem space, from scratch utilizing PyTorch framework
  • Generated thousands of trajectories from both DQN and random model, to be used for DT batch offline training
  • Tuned hyper-parameters and benchmarked performance increase from DT model trained on generated trajectories

Modified Code as Policies (MCaP) -- Sep 2022 – Dec 2022

  • Explored cutting-edge developments with NLP models trained to perform AI code generation for robotics tasks
  • Integrated closed-loop concept from “Inner Monologue” into system from Google’s “Code as Policies” project
  • Embedded new low-level functionality into system to allow for new prompt keywords and objectives

Interests and Experience With:

  • Machine Learning
  • Data Science
  • Computer Vision
  • Robotics
  • Embedded Systems
  • Parallel Processing
  • Reinforcement Learning
  • Natural Language Processing

Pinned

  1. Applied-Machine-Learning Applied-Machine-Learning Public

    Python Notebooks from class assignments in Applied Machine Learning Course

    Jupyter Notebook

  2. djpalumb djpalumb Public

    Config files for my GitHub profile.

  3. haraldger/DRL-DecisionTransformer haraldger/DRL-DecisionTransformer Public

    Research project for Deep Reinforcement Learning using Decision Transformer

    Python 7

  4. ztlaistn/MegaMindz ztlaistn/MegaMindz Public

    CSE 442 Project

    JavaScript