Peng Wang
I follow questions.
Peng Wang is based in Greater Vancouver. Over 20+ years he has moved between engineering, data and finance: an MSc in computing science, ERP consulting, a CPA, a 3D/VR startup, people analytics, data platforms, and now leading an engineering team that builds with AI.
Chapter 1 · 2000–2007
What can a machine figure out on its own?
At UNB I wrote my honours thesis surveying quantum computer architectures and algorithms. At the University of Alberta, my MSc thesis used graphical models to predict protein function across the Gene Ontology’s hierarchy.
Chapter 2 · 2008–2016
How does a business actually run?
Grad school gave me a strong interest in business, so I chose consulting to learn as many businesses as possible, fast. Numbers were the backbone of each. Inspired by my CFO, I spent two years of weekends earning my CPA.
Chapter 3 · 2016–2018
Can I build it myself?
I co-founded Magic Beans to build 3D VR/AR showcases for complex products: packaging machines, aircraft interiors, home interiors. I led an offshore dev team, talked to hundreds of people at trade shows, and gave live demos onsite.
- How much time will it take to cross the border at Peace Arch?
- How many bikes will be shared in Vancouver next week? (part 1)
- Why so many wildfires in BC lately?
- How many bikes will be shared in Vancouver next week? (part 2)
- A simple skill-based job recommendation engine
- Web app for border-crossing wait-time forecasts, part 1
- Web app for border-crossing wait-time forecasts, part 2
Chapter 4 · 2018–2023
If the data is big enough, will it tell the truth?
Not by itself. It takes the right questions, metrics and business context. At Visier, I cut customer onboarding from about six months to one. At Clearly, I moved on-prem systems to an AWS data platform for real-time insights.
- AWS Certified Solutions Architect – Associate
- On-prem → AWS data platform
- Ad hoc report requests −30%
- Organizational network analysis
- Credit card fraud detection using SMOTE
- Exploratory spatial data analysis: spatial autocorrelation
- People analytics: attrition predictions
- Things employees like and dislike about their companies
- 2019 HR Tech conference on Twitter, part 1
- 2019 HR Tech conference on Twitter, part 2
- Who are the top HR analytics influencers on Twitter?
- What people tweet about #coronavirus, in one minute
- COVID-19 Power BI dashboard
- Trump and Trudeau on Twitter during COVID-19, part 1
- Trump and Trudeau on Twitter during COVID-19, part 2
- Can you tell someone’s gender based on tweets?
Chapter 5 · 2023–now
How do you lead a team to build better with AI?
I built a team from 0 to 10 engineers in 12 months, behind a grants management product used by 400+ universities and research institutions. We brought Cursor and Claude Code into everyday engineering work.
- −40% customer issue triage time, with a RAG-based triage assistant
- −30% incident backlog in 6 months
- I also launched and host an office-wide AI learning series.
Chapter 6 · Aug 2024–now
How do you serve your community with AI?
Since August 2024 I’ve served on the board of Connections Community Services Society, bringing practical AI to a community board. I also give AI talks in local schools, and build games with my kids.
Chapter 7 · Next
What’s the question now?
I’m exploring new questions now. Stay tuned.