Software developer & M.S. Artificial Intelligence student
I turn ideas into working applications, with a focus on natural language processing, deep learning, and thoughtful user experiences. Explore the projects behind my graduate studies and independent work.
I'm Rabilal Kharel, but most people call me Rob. I'm a software developer based in New York City and a master's student in Artificial Intelligence at the University of the Cumberlands. I enjoy taking an idea, figuring out how it works, and turning it into something people can use.
My background is in computer systems, networking, and information security. Studying AI has given me a new way to build on that foundation, especially through natural language processing, neural networks, and deep learning. I learn best by building, testing, and working through the details when something doesn't behave as expected.
My projects include an AI Resume Analyzer, a chatbot that answers questions from uploaded documents, and AI Trivia Battle, a multiplayer game for learning AI concepts with friends. Each project gives me a chance to connect what I study with practical decisions about software, data, and user experience.
I'm looking for opportunities to contribute to AI and software development projects, learn from experienced teammates, and keep improving my skills. I care about understanding the tools I use and building applications that are useful and easy to navigate.
From deep learning frameworks to cloud platforms — here's what I work with.
A selection of AI and software projects from coursework and personal exploration.
A live AI knowledge challenge for 2–8 players. Join by room code, answer 10 timed questions, and compete on a shared leaderboard. Each reveal explains the answer, combining learning with friendly competition.
A fully deployed AI web application that analyzes resume-job fit using NLP and Machine Learning. Upload your resume PDF, paste a job description, and instantly get your ATS score, keyword match analysis, skill gap breakdown by category, and personalized improvement tips. Built and deployed end-to-end.
A conversational AI chatbot built from scratch — evolving from a Python terminal script to a full GUI desktop app with voice output, scrollable chat history, user profiles, and a Flask web interface. Packaged as a Windows .exe using PyInstaller.
Integrated Microsoft Azure AI Language services into a chatbot pipeline — connecting a cloud NLP endpoint to analyze user intent, sentiment, and key phrases in real-time. Configured and deployed on Azure Free Tier with a custom language resource.
Trained a character-level LSTM language model on Alice in Wonderland text using TensorFlow/Keras on Google Colab with T4 GPU acceleration. The model learns writing style, sentence structure, and generates new text in the style of Lewis Carroll.
Critical review and deep analysis of seminal NLP papers — Sutskever et al. (2014) sequence-to-sequence models and Wu et al. (2016) Google Neural Machine Translation system. Analyzed attention mechanisms, encoder-decoder architectures, and translation quality improvements.
Open to ML engineering roles, data science positions, and interesting collaborations.
I'm actively seeking roles in machine learning engineering and data science. Whether you have a position, project, or just want to connect — reach out.
Professional certifications and currently pursuing credentials.