Research · Engineering · Mathematical inquiry
Building systems that make difficult ideas visible.
I am an unbounded operator fitting the world at the full gradient.
Current inquiry
I work where mathematical structure meets computational systems. My current questions move between Python, Reinforcement Learning, and Event Planning—fields connected by a shared interest in representation, inference, and what can be known from incomplete information.
Question 1
Computer vision
How can systems recover structure, depth, and meaning from images when the evidence is incomplete?
Selected work
Reliability Event Detection Case Study
An unlabeled reliability-analysis case study that turns operational logs into daily impairment signals, systemic-event hypotheses, diagnostics, and an interactive review dashboard.
MTA Strategy Optimizer
A 25-person advertising-analytics project where I became the de facto integration lead, delivered a reproducible synthetic-data baseline in two days, and produced the implementation selected by the mentor as the best match for the project expectations.
Washington University Chinese Groundbreakers
Event planner who took ownership beyond assigned duties to keep a 300+ member WashU community active, informed, and responsive through graduation.
TestLover (IMSB personality test)
An AI-assisted Next.js entertainment experiment shipped in four hours and visited by about 2,000 unique users in its first week.
Cobalt-4
An active two-person rhythm-game prototype where I lead visual/UI work and advise note-judgment algorithms, supported by a public calibration experiment.
ImGenHCT
A one-step text-to-image pipeline that maps text directly into compressed 1D TiTok image tokens and reached a 0.79 VQA score.
Pathways
Connected work · 7
ImGenHCTproject · A one-step text-to-image pipeline that maps text directly into compressed 1D TiTok image tokens and reached a 0.79 VQA score.CSE 5519 (Advances in Computer Vision)course · Fall 2025 · GraduateATTPDRLproject · A two-person trailer-truck DRL study where straight control converged, 90-degree steering failed, and the failure clarified why DRL should be a bounded local controller rather than an end-to-end trajectory-free driver.CSE 5100 (Deep Reinforcement Learning)course · Fall 2025 · GraduateMon3trproject · A solo MASt3R and Smooth-Diffusion experiment whose complete 2D-inpainting-to-3D loop ran but failed because plausible images were not geometrically consistent across views.CSE 561A (Large Language Models)course · Fall 2024 · GraduateRobot Open Autonomous Racing (ROAR)project · A three-person ROAR team using a manually tuned PID controller that placed second and recorded the fastest lap in Fall 2020.A working definition
I am an insatiable learner, always looking for challenges that force a change in how I think. I believe meaning is made while realizing the potential of intelligence and while interacting with other minds.
Axiom 1
The universe, to the best of our knowledge, is a playgroundWorking definitionA place where we exist, live, experiment, and eventually die. that enables different stories, beliefs, and interpretations.
There are many gamesWorking definitionSystems of goals, constraints, narratives, and shared rules that we create and inhabit. that we can create, play, and share. There is no standardized meaning, evaluation function, or final rule except the law of physics: the mathematical model that continues to survive observation.
Axiom 2
Time is a non-commutative operator acting on the universe. It is generally neither computable nor invertible. The past never fully dies; irreversible actions constantly turn parts of us into history. We live physically in the present, perceive it imperfectly, and act through predictions of the future.
Axiom 3
LifeWorking definitionA subsystem that actively interacts with and changes its environment through connection, entropy, and impact. is not only an optimization process, but a relationship-making process.
Humans become themselves through memory, language, care, tools, institutions, and other intelligences. AI should be treated in that relational field: neither an oracle that replaces judgment nor a passive instrument without consequence, but a cognitive partner whose value depends on how honestly it extends agency, responsibility, creativity, and attention.
The goal is not human versus AI. The goal is a better human–AI ecology: machines amplify exploration and precision while humans keep authorship, moral context, taste, and the courage to choose.