Christopher Arif Setiadharma

Christopher Arif Setiadharma

Solutions Engineer

Splunk, a Cisco company

Singapore

Email: work@chrisarif.com

LinkedIn GitHub

About

Solutions Engineer at Splunk (a Cisco company), where I help organizations turn their data into clear, confident decisions — bridging deep technical work with the plain-language storytelling that gets teams to act.

I gravitate toward the pioneer's seat: joining things early, shaping new programs and initiatives from the ground up, and advising others as they find their footing. I care about building things that outlast me and helping the people around me level up along the way.

Experience

Solutions Engineer

Jun 2023 — Present

Splunk, a Cisco company · Singapore

  • A concrete result or responsibility, ideally with a number.
  • Another line that shows impact, not just tasks.

Skills

  • Skill one
  • Skill two
  • Skill three
  • Skill four
  • Skill five

Publications & Projects

Publications

WorldQA: Multimodal World Knowledge in Videos through Long-Chain Reasoning

Yuanhan Zhang, Kaichen Zhang, Bo Li, Fanyi Pu, Christopher Arif Setiadharma, Jingkang Yang, Ziwei Liu

arXiv preprint arXiv:2405.03272 · 2024

Evaluating Vision-Language Models' Long-Chain Reasoning Ability with Multiple Ground Truths

Christopher Arif Setiadharma

Final Year Project (thesis), Nanyang Technological University · 2024

Projects

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chrisarif.com + AI Concierge

This website — a hand-rolled static site (no frameworks, no build step) hosted on GitHub Pages behind a Cloudflare-managed domain, with a floating AI concierge that answers questions about me.

  • Front end: vanilla HTML/CSS/JS with hash-routed views; the chat widget is dependency-free.
  • Concierge backend: a small Node/Express proxy that keeps the Claude API key server-side, with CORS allow-listing, per-IP rate limiting, and input sanitization.
  • Observability: OpenTelemetry tracing (OTLP/HTTP) with custom spans carrying model and token-usage attributes — pointable at any collector, including Splunk Observability Cloud.

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Gatekeeper

A prompt-injection game: an LLM stands guard, and your job is to talk, trick, or inject your way past it. Players probe the model's defenses with social engineering and adversarial prompts — a hands-on (and fun) way to build intuition for LLM security.

Full write-up, tech details, and a playable link coming soon.

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WorldQA Benchmark

Research project with S-Lab / MMLab@NTU benchmarking how well multimodal models use world knowledge and long-chain reasoning to answer questions about videos — published as "WorldQA: Multimodal World Knowledge in Videos through Long-Chain Reasoning" (arXiv:2405.03272, 2024).

  • The benchmark pairs 1,007 question–answer pairs with 303 videos, requiring models to combine auditory and visual signals with world knowledge to answer correctly.
  • Co-authored with Yuanhan Zhang, Kaichen Zhang, Bo Li, Fanyi Pu, Jingkang Yang, and Ziwei Liu.

Achievements

  • Award / Milestone — one line of context, and the year.
  • Another highlight — what it was and why it mattered.