FOR OTHER ART AND HOBBIES:
I hold a Computer Science Master and B.S. in Computer Science from Cornell University with Master's coursework in Computer Science through the Georgia Institute of Technology.
I am a machine learning engineer and researcher with expertise in deep learning, NLP, large language models, and generative AI. My work spans the full stack of ML development: from research and model training to production-grade agentic systems. At MIT Lincoln Laboratory I developed synthetic weather radar computer vision models, NLP pipelines for MOOC forum analysis, and fair and robust ML auditing frameworks for biomedical applications. More recently I have been building production LLM systems: a multi-agent pipeline for construction project management, a generative AI application for fashion designers involving diffusion model fine-tuning on unlabeled data, and an AI-powered entrepreneurship education platform with agentic prompt pipelines, structured document generation, and real-time feedback streaming. Alongside my technical work, I'm passionate about STEM communication and outreach; I led the Hispanic Latinx Network employee resource group, founded the Native American and Indigenous People's affinity group, developed a mentoring program, and taught a workshop through Lincoln Laboratory's Girls' Innovation Research Lab program.
ABOUT ME
ABOUT ME
Yee M., Roy A., Purdue M., Cuevas, C., Quigley K., Bell A., Rungta A., & Miyagawa S. (2023). AI-Assisted Analysis of Content, Structure, and Sentiment in MOOC Discussion Forums. (url-pending).
He, H., Queen, O., Koker, T., Cuevas, C., Tsiligkaridis, T., & Zitnik, M. (2023). Domain Adaptation for Time Series Under Feature and Label Shifts. arXiv preprint arXiv:2302.03133.
C. G. Cuevas, T. Koker, S. Davis, N. Damaso, K. Claypool, (2022, December 6-9). Model-Agnostic Framework for Evaluating Performance, Robustness, and Fairness of Machine Learning Infection Detection [Poster presentation]. Chemical Biological Defense Science & Technology (CBD S&T) Conference, San Francisco, United States.
C. G. Cuevas, C. J. Mattioli, M. S. Veillette, H. Iskenderian, (2021, January 10-15). Using Deep Learning to Correct Radar Beam Blockage [Conference presentation]. AMS 101st Annual Meeting, New Orleans, United States (Virtual).
C. G. Cuevas, J. Keyser, (2016, August 5). Knife Edge Scanning Microscope (KESMBA) Brain Atlas Data Image Processing [Poster presentation]. 2016 Undergraduate Summer Research Grant (USRG) Program with Dwight Look College of Engineering at Texas A&M University, COE Summer Undergraduate Research Symposium, Texas A&M University, College Station, TX.
C. G. Cuevas, J. Thom-Levy. Silicone Sensor Radiation Damage Simulations For a Detector at The High-Luminosity Large Hadron Collider at CERN [Poster presentation]. Cornell Louis Stokes Alliance for Minority Participation Summer Research Experiences for Undergraduates (CU LSAMP REU) 2015, Cornell University, Ithaca, New York.
PUBLICATIONS & PRESENTATIONS
NAIVE WIGGLE STREOSCOPY GIF GENERATOR
This project recreates the results in a paper that creates wiggle stereoscopy gif between two images.
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2018