What I build
End-to-end measurement pipelines for applied research. Built for rigor, reuse, and transparency, so results are reproducible and limitations are clear.
I build monitoring‑grade pipelines that turn messy signals into traceable evidence, decision‑ready products, and ultimately, actionable insights. The work is systems‑first: research design, deep learning + information retrieval (RAG/KB patterns, AI‑assisted), algorithm design, geo + time analytics, and evaluation harnesses that stay attached in production.
R&D: RQ → op-sigs → baselines → fail modes
arch: conn → parse → schema/patch → lineage
K/R: embed → vec+KB → hybrid RAG
mdl: multi-head → cal+unc → decision policy
LLM: synth rules | assist labels | doc→schema | err triage
ship: agg → dash/maps → alerts/briefs | API
SRE: drift | health | audit | ver | rollback
Design systems that can pivot across contexts. From research to production, build with modularity, transparency, and robustness baked in.
When politics fractures, we stay grounded—and build a better vision.
End-to-end measurement pipelines for applied research. Built for rigor, reuse, and transparency, so results are reproducible and limitations are clear.
Designed to stay dependable: clean inputs, sturdy pipelines, and frequent sanity checks, so the output doesn’t fall apart when things shift.
If you’re building mission‑driven products (research labs, NGOs, policy, or industry), I’m happy to talk. Low‑friction contact here.
A few papers and notes that reflect the research direction—kept brief and preview-only.
Event detection + interpretable early‑warning signals for shifts in protest, restriction, media pressure, and advocacy activity — designed for frequent refreshes and evidence traceability.
Tracks influence patterns across channels (diplomatic / economic / information / cyber) with consistent task definitions, careful normalization, and transparent aggregation.
Detects environmental shocks and social responses using multilingual event modeling + geo grounding, with downstream time‑series signals for monitoring and analysis.
Map‑first monitoring at subnational resolution, wired to two‑stage geo reconciliation (country → ADM1), standardized counts, and surge detection for rapid scanning and drill‑down.
These are representative, not exhaustive — the emphasis is on reusable infrastructure that transfers to new domains and stakeholders.
Previews only (first 2 pages) — to avoid circulating full drafts. Public versions are linked when available.
If you’re exploring collaborations, I can share additional technical notes (evaluation harnesses, sampling QA playbooks, schema/patch patterns).
Typical problem spaces these systems support.
Low‑friction ways to reach me or explore artifacts.
Best for collaboration notes, dataset/tool questions, and applied AI opportunities.
Pipelines, experiments, and artifacts that support monitoring‑grade AI systems.
Where a lot of the public‑interest systems work lives.
Useful work still benefits from a little life.
Taiwanese by origin, culturally curious by default. I travel through food and the stories people tell through what they cook. Off the clock: dancing, handcrafts, and graffiti-inspired lettering—creative outlets that keep me energized.