Founder of UnsupervisedBias
I assist leaders in bringing their AI ambitions to life by crafting intelligent solutions that streamline
business operations and position them at the forefront of their industries.
With over eight years of experience in Artificial Intelligence and Data Science, I have worked across a
variety of sectors, including Aerospace, Medicine, Supply Chain, and numerous United States Government
agencies. My expertise lies in swiftly developing prototypes and Proof of Concept (PoC) projects for
groundbreaking initiatives.
My services include:
Founder & Freelance AI Engineer
UnsupervisedBias
December, 2022 - Present
I empower organizations and individuals to turn their AI aspirations into reality, developing
intelligent solutions to run those business more effectively — empowering them to lead the future of
their industries.
I deliver reliable data solutions, build business automations, and create automated data funnels,
often powered by custom large language and video detection models.
Senior Data Scientist
Expression
April, 2023 - Present
At Expression, I integrate AI into classified projects for multiple US government agencies, and I
pioneered bringing automated workflows powered by LLMs to Expression. As the company's LLM and
Computer Vision expert, I guide our teams through implementation of Object Detection, Tracking, and
Counting, LLM workflows, assist in procuring future work, and present weekly technical demos to
potential customers alongside our C-suite. I also collaborate with the business development team on
white papers and proposals.
I create synthetic data to emulate confidential datasets, enabling secure development and testing of
ML models, and I manage the ETL that streams data from government sources into AWS, transforms that
data within Databricks, and finally loads that data into ElasticSearch for use by our government
applications.
Finally, I monitor and maintain high standards in documentation and information management, reducing
rework and improving team efficiency.
ML/NLP Teaching Assistant - Master’s Program in CS
University of Chicago
September, 2021 - March, 2024
As a TA for the Master’s Program in CS, I facilitated courses in Machine Learning, NLP, Advanced
Data Analytics, Cloud Computing, and Computer Systems. My duties included leading hands-on ML
tutorials, deep-learning GPU training sessions, and developing and grading course materials. This
role required a deep understanding of theory and the ability to communicate complex ideas to
students clearly.
Senior Machine Learning Engineer
QuayChain Technologies
September, 2021 - April, 2023
As the lead MLE at an early-stage SaaS start-up, I specialized in developing and deploying custom
deep learning and computer vision models. Collaborating closely with our Data Engineer, I played a
pivotal role in constructing our AWS pipeline, tackling complex multi-camera problems to enhance
traffic flow predictions.
My expertise in analyzing raw video data involved the use of OCR, hierarchical clustering, and
advanced object detection/tracking techniques. This enabled the extraction of crucial data such as
license plates, shipping container numbers, and vehicle counts for comprehensive traffic analysis.
Our AI-powered web application revolutionized supply chain management by providing executives with
enriched video data of their trucks, incorporating essential details like time, location, and
various identification numbers. This innovation not only streamlined port deliveries across the
country but also served as an automated and reliable proof of delivery system.
Machine Learning Engineer
UChicago Medicine
January, 2020 - September 2021
As an MLE at UChicago Medicine, I developed sophisticated language models leveraging the hospital's
extensive patient database. My custom BERT model was specifically trained to assist in the accurate
suggestion of ICD codes for physicians, significantly enhancing their paperwork efficiency and
accuracy.
Additionally, my work focused on creating predictive models to identify patients at high risk of
cardiovascular diseases. This not only involved advanced data preprocessing and XGBoost analysis,
but also close collaboration with medical experts to ensure the models were clinically relevant.
Through these initiatives, we achieved a notable improvement in patient care by facilitating early
intervention strategies and more personalized treatment plans, while also adhering to stringent
healthcare data privacy regulations.
Machine Learning Scientist
Argonne National Laboratory
May, 2019 - January, 2020
As an ML Researcher at Argonne National Laboratory, I was part of a team focused on advancing water
quality monitoring technologies. I addressed the issue of drifting pH and voltage measurements in
water contamination sensors using GPU-powered Bayesian inference to develop a compensation solution.
This innovation enhanced the reliability and precision of at-home water sensors, particularly
benefiting the Flint, Michigan area. Our work significantly improved water quality monitoring,
providing a dependable tool for communities facing water safety concerns.
Senior FEA/HPC Aerospace Engineer
Boeing
June, 2016 - May, 2019
On the commercial side, I played a pivotal role in small, specialized engineering teams responsible
for a range of critical projects. This included analyses of the design, construction, fatigue, and
repairs of Boeing’s 777X and 787 Dreamliner aircraft. My contributions were instrumental in
enhancing the structural integrity and performance of these advanced aerospace systems.
On the military side, I was involved in a confidential project for the U.S. Department of Defense,
where I applied my expertise in Bayesian inference, linear regression, stress analysis, and
engineering to develop a high-priority aerospace structure. This work required a rigorous approach
to problem-solving and innovation, adhering to strict industry standards and governmental
regulations.
Computational Fluid Dynamics Researcher
Syracuse University
May, 2015 - May, 2016
As a Researcher, I conducted an innovative study analyzing dolphin movement and its emulation
through my 3D-printed fin designs. Key to this research was experimenting in a water tunnel. I
employed planar laser-induced fluorescence, a technique where dye is injected in alignment with a
laser beam, to vividly capture the vortex patterns in the wake of the fins. By recording these
phenomena at various heights in the water tunnel, I developed a program to interpolate and stitch
these 2D recordings into comprehensive 3D visualizations. The experiments, repeated under varying
water velocities and swimming patterns, were crucial in identifying the optimal Strouhal number for
swimming efficiency.
This work earned me the esteemed George M. Berry Award for Outstanding Design Achievement in
Engineering at Syracuse University, recognizing the impact of my contributions to fluid dynamics
research.
AirBnB Host
Airbnb
September, 2018 - March, 2020
Purchased a 3-bedroom home and became a self-employed AirBnB "Super Host" sustaining a 5-star
rating with over 80 bookings.