Trajectory / build history
Software engineering led to technology leadership. Leadership made operational constraints unavoidable. Applied AI made evaluation unavoidable. Doctoral research makes the human and institutional consequences unavoidable.
Foundation
Computing and software engineering established the practical base: web applications, APIs, databases, geolocation, debugging, and the discipline of turning requirements into working systems.
BSc (Hons) Computing · First Class HonoursLeadership
More than three years in CTO-level technology leadership shifted the problem from code alone to architecture, operations, workflows, stakeholders, GIS, automation, prioritisation, and commercial constraints.
Picpoint Nepal · CTO · technology strategy and digital operationsApplied AI
The Master of Information Technology in Artificial Intelligence expanded the technical range into retrieval, computer vision, robotics, reinforcement learning, temporal learning, data science, and AI ethics—while industry R&D at Truuth forced reliability questions into production reality.
Macquarie MIT (AI) · Truuth AI/ML R&D · Distinction major projectResearch
The current doctoral direction asks how intelligent systems can extend human capability while keeping judgement, oversight, privacy, traceability, and accountability meaningfully human and testable.
Charles Darwin University · responsible GenAI · human agencyNow
The throughline is now explicit: build what can be inspected, measure before claiming, connect technical performance to organisational reality, and treat governance as part of system design rather than paperwork after deployment.
Applied AI · digital systems · research · technology leadershipWorking principles from the trajectory
Architecture, operations, people, incentives, data, interfaces, and failure handling all shape whether a technical system works in practice.
A convincing demo is not the same as a reliable system. Measurement, error analysis, deployment conditions, and evidence need to travel with the work.
Human oversight, privacy, traceability, accountability, and safe boundaries are more useful when designed into workflows rather than added after deployment.
What this means now
The point is not to claim breadth. It is to make the connective tissue visible—technical work, research, leadership, writing, experiments, limitations, and the decisions behind them.