ART
&
TECH
Jason Lee

JASON LEE

I graduated from UC Berkeley with a dual major in Computer Science and Art Practice, alongside the EECS Honors Program, a selective track designed to push engineers beyond the bounds of their own discipline and into broader intellectual territory.

While most of my peers stayed within a single discipline, I was among the few actively bridging CS and art, an intersection that remains largely underexplored, and the space that became my calling.

My vision is to bridge the worlds of art and technology. I believe we are on the edge of a new realm of entertainment, one built not just on LLMs, but on deeper, less explored fields like deep computer vision and reinforcement learning. The future of creative experience lies in systems that can perceive, adapt, and respond, not just generate.

Outside of work, I'm drawn to exploring cuisine and fine dining, hunting down collectibles, golf, and bouldering.

Art Practice

2023 — 2025
Wastelands 2

Wastelands 2

Acrylic on canvas · 2′ × 3′ · 2024
Wastelands 3

Wastelands 3

Acrylic on canvas · 2′ × 3′ · 2024
Wastelands 4

Wastelands 4

Acrylic on wood, silkscreen Lokta paper · 18″ × 12″ · 2024
Wastelands 5

Wastelands 5

Acrylic on wood · 18″ × 12″ · 2024
Sultry 1

Sultry 1

Acrylic on canvas, collage · 18″ × 12″ · 2023
Sultry 2

Sultry 2

Acrylic on canvas, collage · 18″ × 12″ · 2023
Sultry 3

Sultry 3

Acrylic on canvas, collage · 18″ × 12″ · 2023
Sultry 4

Sultry 4

Acrylic on canvas, collage · 18″ × 12″ · 2023
2020 — 2023
Pour

Pour

Gouache on wood · 2′ × 4′ · 2022
Cyanotype 1

Cyanotype 1

Cyanotype on watercolor paper · 7″ × 18″ · 2021
Cyanotype 2

Cyanotype 2

Cyanotype on watercolor paper · 7″ × 18″ · 2021
Cyanotype 3

Cyanotype 3

Cyanotype on watercolor paper · 7″ × 18″ · 2021
Hide 1

Hide 1

Hand-made pigments on paper · 8″ × 11″ · 2021
Hide 2

Hide 2

Hand-made pigments on paper · 8″ × 11″ · 2021
Stomach

Stomach

Ink on Washi paper · 2′ × 4′ · 2021
Sketch 1

Sketch 1

Alcohol markers and ink · 2020
Sketch 2

Sketch 2

Alcohol markers and ink · 2020
Sketch 3

Sketch 3

Alcohol markers and ink · 2020
Experiment

Experiment

Hand-made pigments on Washi paper · 2020
Woodprint

Woodprint

Woodblock print with ink · 2020
2018 — 2020
Glowstone

Glowstone

Collage, alcohol markers, pen · 8.5″ × 11″ · 2019
Head in the Clouds

Head in the Clouds

Collage, alcohol markers, pen · 8.5″ × 11″ · 2019
Insomnia

Insomnia

Collage, alcohol markers, pen · 8.5″ × 11″ · 2018
Turtle

Turtle

Collage, alcohol markers, pen · 8.5″ × 11″ · 2018
2015 — 2018
Graphite Work 1

Graphite Work 1

Graphite on paper · 12″ × 18″ · 2017
Graphite Work 2

Graphite Work 2

Graphite on paper · 12″ × 18″ · 2017
Graphite Work 3

Graphite Work 3

Graphite on paper · 12″ × 18″ · 2016
Graphite Work 4

Graphite Work 4

Graphite on paper · 12″ × 18″ · 2016
Watercolor

Watercolor

Watercolor on paper · 12″ × 18″ · 2015

Machine Learning

Reinforcement Learning PyTorch OpenAI Gym

Reinforcement Learning Agent

Designed and trained a deep RL agent using policy gradient methods. The project explored reward shaping, environment design, and the challenge of sparse feedback — bridging mathematical optimization with emergent intelligent behavior. Training from scratch revealed how much architecture and hyperparameter choice govern what an agent can learn.

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Fine-Tuning LoRA Transformers

LoRA Fine-Tuning

Applied Low-Rank Adaptation (LoRA) to fine-tune a large language model on domain-specific data. Investigated the efficiency-performance tradeoff between parameter-efficient training and full fine-tuning, achieving strong results with a fraction of the compute and memory footprint — a meaningful finding for resource-constrained deployment.

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