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Jonathan Koch - Software Engineer and AI Researcher

Hello! I'm Jonathan Koch, a dedicated Software Engineer and AI Researcher at the University of South Florida. My expertise lies in Robotics and AI, with a strong focus on object manipulation, audio and image processing, and reinforcement learning. I have a keen interest in predictive models, NLP, multi-agent learning, cognitive science, as well as in music and Brazilian Jiu-Jitsu.

Overview

  • Research Background: Robotics & AI; Object Manipulation, Audio & Image Processing, Perception Modeling, Reinforcement Learning, Transformers
  • Interests: Predictive Models, NLP, Multi-Agent Learning & AI, Cognitive Science, Generative Models, Data Science, Acoustic Guitar, Piano, BJJ
  • Personal Website: Jonathanzkoch.dev/

Education

  • University of South Florida College of Engineering: Pursuing a Bachelor of Science in Computer Science, concentrating in Robotics and AI.

Experience

  • Software Engineering R&D Co/Op at CAE USA R&D Facility, Tampa, FL: At CAE, I have been able to undergo tons of different projects working in different areas of technology. I've developed and configured parallel hardware and lab nodes for simulation and R&D. Additionally, I was able to integrate dozens of untouched repositories into CI/CD pipelines. More recently, I have been working in the R&D side; here I have collaborated on touchscreen sensor mapping driver for a multiscreen device, worked closely with MLOps platforms for AI/ML solutions, and integrated NLP to process natural language commands into executable code. Additionally, I prototyped and developed Generative Agents via finetuned LLMs which were capable of performing actions in simulated environments using high-level reasoning and planning. I incorporated contrastive pretraining paired with new experimental network architectures into text classification improving models from 93% to 98% accuracy. Recently, I've integrated an ensemble model for IOB NER and Text Classification incorporating heuristics, finetuned models, and LLMs for <99% accuracy.

  • Research Scientist at Robot Perception and Action Laboratory, USF: Conducted research on robotic object manipulation and perception, focusing on developing transformer encoders for spatial and temporal representations of graph-based systems. Probabilistically modeled dynamical systems using Graph Neural Networks (GNNs) via contrastive divergence in latent space conditioning, leveraging historical state-action pairs to enhance predictive accuracy and representation quality.

  • Senior Coding Coach and Instructor at theCoderSchool Tampa: Led initiatives to simplify Agent AI concepts for children, developing a Python-based educational library. Allowed students to Black-box creating ML Models for data-driven tasks.

  • Vice Chair, AI Group Founder, VEX Robotics Programming Team Founder at USF IEEE Student Chapter: Organized formal and constructive professional events and workshops, founded an AI group, and worked effortlessly to cultivate popularity and interest in AI.

Projects

  • Teach-A-Bull (AI Tutor): Utilizing LLMs for educational content generation. GitHub
  • CoderSchoolAI: A beginner-friendly Neural Network API and AI tools library. GitHub | Demo
  • Virtual Assistant: An NLP-based assistant for task sequencing. GitHub | Video

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