Ernesto Rivera
Bridging Tech and Industry: Innovating Solutions, Inspiring Change.
Professional Portfolio
I am a driven technologist with a passion for leveraging artificial intelligence, data architecture, and innovative solutions to solve real-world problems. With over five internships, a research assistant role, and two startups under my belt, I bring a wealth of experience in consulting, development, and leadership across industries such as construction, education, and technology.
As a Data Architecture Engineer and Full-Stack SWE/AI Developer at Whiting-Turner, I restructured a database of over 1 billion data points into job site-specific databases, reducing query times by 80% and enabling scalable, efficient workflows. I also led the development of a task management system that reduced scheduling delays by 12% and mentored junior interns to foster sustainable growth. My consulting efforts included introducing artificial intelligence applications, such as a resume scanner proof-of-concept, to demonstrate the potential of AI in construction management.
In the startup space, I served as a Founding Engineer at MyTA, where I developed an AI-powered educational chatbot that integrated cutting-edge technologies like Meta AI's Nougat and Pinecone, improving content delivery by 50%. Collaborating with over 14 universities, I helped scale this platform to provide 24/7 personalized academic support to students, demonstrating my ability to build impactful, scalable solutions.
At the GLOB~S Lab at Boston University, I worked as a Research Assistant to analyze a 32GB dataset from the US Patent Directory. My work focused on uncovering innovation trends related to disasters like Hurricane Katrina, streamlining workflows with advanced tools such as NumPy and Dask to extract key insights and inform policy strategies.
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Hackathon Projects
Church & AI Hackathon, Best Concept — $15,000 Prize
At the 2024 Church & AI Hackathon, I led the creation of Generosity, an AI-driven platform designed to unlock $50 billion in annual church donations. Leveraging AI-powered donor-cause matching algorithms, we increased donation growth by up to 53% and utilized Digital Twin technology to optimize initiative success across large member bases. The platform featured a real-time feedback loop for donors, transforming engagement and transparency through a dynamic AI dashboard.
Church & AI Hackathon, Best Technology — $50,000 Prize
In 2023, I contributed to building an AI-powered MetaHuman backend using Inworld AI and Unreal Engine for immersive 3D interactions. This project pioneered personalized AI faith-based counselors, reducing costs by 100x through targeted ads and search engine tools. I played a pivotal role in crafting the technical infrastructure and business strategy, establishing a strong foundation for Gloo's collaboration.
Cornell Health Hackathon Finalist
As a finalist in 2023, I developed an AI-powered VR/AR therapy app to help individuals overcome phobias. I also integrated GPT-3's API to create personalized prompts for immersive 360-degree environments using Stable Diffusion, showcasing innovation in therapeutic applications.
NASA Space Apps Global Nominee
At the 2022 NASA Space Apps Hackathon, I engineered an AI system to analyze over 22,500 datasets from public NASA archives. By implementing GPT-3 and Stable Diffusion, I made complex datasets easily accessible for the general public and researchers alike, earning global recognition for advancing AI-powered data exploration.
Personal Projects
I've always loved building projects, whether at hackathons, for work, or on my own time to solve personal challenges. One of my favorite projects is an OCR Digit Classifier, where I developed a custom K-Nearest Neighbors (KNN) machine learning model to recognize handwritten digits using the MNIST dataset. The classifier achieved 95% accuracy through optimized preprocessing and feature extraction methods, and I enhanced it with a user-friendly GUI built in Python using Tkinter, PIL, and Numpy, enabling real-time digit recognition. This project not only demonstrated the potential of machine learning but also deepened my understanding of OCR and classification techniques.
Currently, I'm working on an AI Interview Bot designed to assist individuals like myself in preparing for technical and behavioral interviews. Using OpenAI, Flask, Next.js, and WebSockets, the bot provides real-time feedback, grades responses, and tailors questions to specific industries, companies, and job positions. It's a project I'm incredibly excited about and hope to release a version by the end of January 2025. Stay tuned for updates!
Whether it's automating email responses based on LinkedIn activity or creating tools to improve productivity and learning, my personal projects allow me to explore new technologies and solve meaningful problems.
