CV

Education

• Masters in Computer Science
  • University of California, Davis - 2022
• Bachelors in Computer Science and Engineering
  • Minor: Mathematics
  • University of Nevada, Reno - 2020
• Associates in Physics, Mathematics, and Natural Science
  • Sierra College - 2017

Academic and Research Experience

• Graduate Student Researcher - Computational Linguistics Lab, University of California, Davis - Sept 2020 - July 2022
  • Efficient Neural Semantic Parsing for Low-Resource Languages: Developed a methodology to generate efficient neural models for semantic parsing in the zero-shot setting. Models generated using this methodology demonstrated competitive results to the current state-of-the-art work while requiring just 3% of the computational resources.
• Undergraduate Research Assistant - Robotics Research Lab, University of Nevada, Reno - Aug 2018 - Aug 2020
  • Camera-to-2D-LiDAR Calibration Method: Developed a new method of feature correspondence between lidar and rgb camera sensors capable of calibrating a multi-sensor system from a single sample without a priori information about the calibration target geometry.
  • Intent Recognition System for PR2 Robot: Assisted in developing an artificial intelligence human-intent recognition system to enable socially aware navigation of robotic platforms in a multi-agent setting.
  • Pioneer3-DX Gazebo/ROS simulation: Designed simulation and control code, as well as a custom simulation model, for a Pioneer3-DX in Gazebo.
• Undergraduate Researcher - Summer 2019
  • Research Experience for Undergraduates - University of Nevada, Reno - Human Robot Interaction
    • Perceptions of Computer-Generated Speech for Social Robotics: National Science Foundation sponsored research to investigate the existence of vocal-pitch-based stereotypes of social robots in human robot interaction.

Skills

• Programming:
  • Comfortable: C/C++, Python, PyTorch, NumPy, Git, LaTex, Linux, Bash
  • Familiar: Java, Swift, Keras, Tensorflow, OpenCV, Robot Operating Sytem (ROS), Gazebo

Accepted Publications

Simple Camera-to-2D-LiDAR CalibrationMethod for General Use

A. Palmer, C. Peterson, J. Blankenburg, D. Feil-Seifer, M. Nicolescu, "Simple Camera-to-2D-LiDAR Calibration Method for General Use." in International Symposium on Visual Computing (ISVC), Jul. 2020.

Teaching Experience

• Teaching Assistant - Mar 2022 - Jun 2022
  • MAT 17B: Caculus for Biology and Medicine II - UC, Davis
    • Weekly discussion sections to review course materials; review sessions before exams; proctoring and grading exams, including extensive feedback and post-exam follow up to encourage students to learn from mistakes; bi-weekly office hours; and bi-weekly tutoring hours to help students with a wide range of topics such as beginner algebra, calculus, linear algebra, and differential equations;
• Teaching Assistant - Jan 2022 - Mar 2022
  • MAT 17A: Caculus for Biology and Medicine I - University of California, Davis
    • Weekly discussion sections to review course materials; review sessions before exams; proctoring and grading exams, including extensive feedback and post-exam follow up to encourage students to learn from mistakes; bi-weekly office hours; and bi-weekly tutoring hours to help students with a wide range of topics such as beginner algebra, calculus, linear algebra, and differential equations;
• Teaching Assitant - Sep 2020 - Dec 2020
  • ECS 122A: Algorithm Design and Analysis - University of California, Davis
    • Independently preparing weekly discussion sections to teach course material; exam prep and review sessions; preparing exams and solutions; grading exams, including extensive feedback and post-exam follow up to encourage students to learn from mistakes; and 5 hours of private and public office hours per week.
• Teaching Fellow - Fall 2019
  • CS 482/682: Artificial Intelligence - University of Nevda, Reno
  • Led review sesssions, validated course materials, and graded assignments and exams for an undergraduate/graduate level course (approx. 65 students).

Other Projects

• SoundsLike: A multi-approach text-classifier which uses phonological features to determine word sentiment and similarity; Python, OpenNMT

• NLP with Disaster Tweets: A neural text-classifier to help first responders determine if tweets about a disaster are real or fictitious; Python, PyTorch

• GhostOS: A POSIX-compliant kernel and Operating System, as well as a small game, to run on RISC-V architecture; C, Assembly, Docker

• Minerva: An iOS application utilizing Apple’s CoreML framework to enable deployment of GPU-based TensorFlow Style Transfer models onto mobile devices for CPU-based inference; Swift, TensorFlow, CoreML

• Parallel Optimizations to Genetic Algorithm solutions for the Chinese Postman Problem: An efficient cache-based optimization for a GPU-accelerated Genetic Algorithm-based solution to the k-Chinese Postman problem, with a resulting 2.5x speedup; Python, C++, CUDA

Honors & Awards

• GE Coding Competition Award for Intermediate - Second Place