Ben Nur

Developed a system for producing call statistics and outlines using LiteLLM and OpenAI GPT-4o. Optimized prompts for existing use cases through Prompt Engineering and added monitoring capabilities for LLM models using LangFuse.

Developed and optimized machine/deep learning models for semantic segmentation and object recognition using PyTorch. Implemented systems for automatic improvement of segmentation models and generated synthetic data using Transformers and GAN.

Created an app for automatic detection and fixing of bugs in Python code using ChatGPT. Built services for fine-tuning LLMs and developed ML models for audio processing and object detection using TensorFlow.

Developed and optimized machine/deep learning models for prediction using TensorFlow and Keras. Created latency-optimized inference code in C++ and built data extraction pipelines using Spark and Airflow.

Developed a SLAM system using MATLAB and C++. Created data pipelines for product label localization using ROS and OpenCV, and developed simulation infrastructure using Python and Gazebo.

Developed new features for the iOS application for the Ava 500 Mobile Robot, including a Video Chat module in Objective-C and new AR Touch Gestures for user interaction.

Rebuilt the FileAdvisor web app using ASP.NET MVC, developing both back-end and front-end components with C#, SQL, and JavaScript, while implementing features using AWS services.

Grade: 3.98

Bachelor of Science in Computer Science and Robotics Engineering with a focus on developing innovative solutions in technology and engineering. Achieved a high GPA of 3.98, demonstrating strong academic performance and understanding of complex concepts.