Born in the 80s, grew up in the 90s.

Mapping the Matrix: Malaysia's Corporate Network

The complex interconnections that define modern society are readily visible in our Facebook or LinkedIn networks. But what about the corporate world? I recently began mapping the web of cross-shareholding among Malaysia's listed corporations. Using Social Network Analysis (SNA), I visualized the ecosystem to identify key "communities" and power brokers. The goal? To see if a company's position in this web predicts its financial destiny. The State of Play (2015) Figure 1: Malaysia's Corporate Network in 2015 (Created via Gephi) The map above visualizes the network as of 2015. While I have excluded specific company names, the "super-nodes" (the largest circles) represent the most connected shareholders in the economy—primarily government-linked investment companies (GLICs), fund managers, and international asset managers. A Decade of Growing Complexity ...

Mapping the Blast Radius: What Happens When the "World's Factory" Stops?

In global trade, "efficiency" often masks "fragility." We know that China is central to the global electronics supply chain, but how central? And if that node were to go dark, who would feel the shockwaves first? To answer this, I moved beyond standard trade statistics and built a network simulation using the OECD Inter-Country Input-Output (ICIO) Tables (2023 Edition) . This dataset maps the DNA of the global economy, tracking every dollar of input across 66 countries and 45 industries. 1. The Blast Radius: Tracing the Contagion I treated the global economy as a directed graph and simulated a total supply shock to Chinese Electronics (CHN_C26) . By tracing the flow of inputs across three tiers of buyers, I visualized the "Blast Radius" of this disruption. Fig 1: The Supply Chain Cascade. The shock originates in China (Red) and immediately hits "Tier 1" assembly hubs (Dark Blue) before cascading to global consumers...

The Labor Market Impacts of AI in Türkiye: Beyond Occupational Exposure Analysis

Beyond Exposure AI and Labor Markets · Türkiye Occupational exposure to AI identifies where technology may affect work, but not whether employment will contract, reorganize, or expand. Applying the Richmond (2026) AI Jobs Transition Framework to Türkiye's 2024 Household Labour Force Survey, the dominant high-exposure archetype is not automation. It is reorganization. Mpumelelo Nxumalo and Dhushyanth Raju · Summary of the working paper Beyond Exposure: AI and Labor Market Reorganization in Türkiye Most discussion of AI and jobs runs on a single number: how much of an occupation's task content a model can perform. That number identifies where technology reaches. It does not say what happens next. An exposed occupation may shed workers, or it may keep them while the work itself is rebuilt around the technology. Those are different outcomes, they call for different policy, and exposure alone cannot tell them apart. Applying the Richmond (202...