JavaScript happens to fit my logic, allowing me to build complex, highly refined solutions. My work extends far beyond code. I research AI, social issues, and innovation in longstanding challenges, shaping ideas into whitepapers and new frameworks. As a business-minded creator and lifelong entrepreneur, I approach problems with an economic lens, ensuring that every project carries market potential while fueling my relentless pursuit of new ideas and breakthroughs. Rethink what we think, we already know.
Synopsis: Builds intelligent tools for data analysis, visualization, and AI-driven workflows. Expert in functional JavaScript, algorithm design, and interactive digital solutions.
Programming skills:
Analysis tool:
Sketch/design tool:
Legend:
Links⌗
Power program
Available program (tap to activate)
| Project-name | Project-description |
𝑝 → 𝑴 → 𝑓 : (𝑑𝑡)𝑡∈𝑇 → (𝑶𝑡)𝑡∈𝑇
Where:
𝑇 is an unbounded time index set (e.g., 𝑇 ⊆ ℕ)
𝑑𝑡 is an element from the universal set of heterogeneous data 𝒟
The function 𝑓 is a specific analytic algorithm, derived from a meta-level process.
We can specify this derivation with a meta-algorithm 𝑴
𝑴 is (Underlying relationship amoung data, sentiment analysis, future orientation according to theme, resentment, emotional investment, turnover detection)
Explanation:
A: You start with a high-level goal, specified by the problem specification 𝑝 = (analysis goal)
B: A meta-algorithm (𝑴) takes this specification and, through a complex process of design, produces a specific, fit-for-purpose analytic algorithm 𝑓
C: This tailored algorithm 𝑓 then executes, processing the actual data stream (𝑫) and generating the desired analyzed object 𝑶𝑡.
The algorithm itself is not fixed, but a produced artifact, customized for the specific harvesting and analysis task.
Unintended Data Modeling, also known as Nulta Data Analysis [NDA], represents building algorithms that add new layers of understanding to existing web structures. By harvesting and reinterpreting publicly available signals—such as activity patterns, interactions, or content flow—these models generate insights that go beyond what the platform wanted provided. The value lies in transforming raw traces into actionable knowledge: uncovering trends, mapping relationships, and identifying opportunities that drive smarter decisions, innovation, and competitive advantage. Power it can generate:
| Benefits | Details |
| Transforms noise into knowledge | Converts raw, scattered activity into structured insight |
| Reveals overlooked opportunities | Highlights patterns that can inform strategy, marketing, or product design |
| Augments decision-making | Offers a second layer of intelligence beyond native analytics |
| Custom-fit analysis | Tailored to specific goals rather than generic platform reports |
| Accelerates innovation | Provides early signals of shifts in behavior or emerging trends |
| Leverages existing infrastructure | No need to build a platform, just reinterpret what’s already there |
| Scales effortlessly | Once defined, algorithms can process vast amounts of public data quickly (seconds, milliseconds) |
| Uncovers hidden signals | Reveals trends, behaviors, or anomalies that official metrics miss |
| Independent perspective | Bypasses the biases of platform-provided analytics |
| Real-time adaptability | Can be built and modified faster than waiting for official features |
| Cross-context insights | Combines signals across different parts of a platform (comments, likes, follows, posting times |
| Competitive edge | Provides unique interpretations not available to the majority of users |
| Low barrier entry | Works directly with what’s visible, no privileged access required |
| Flexible goals | Can be tuned for personal, research, or business purposes |