About

I am a mechanical engineering student from Nepal studying at Arkansas State University. My work crosses mechanical systems, software development, research, robotics, learning science, and technical communication.

• Mechanical engineering student
• Full-stack software builder
• Researcher exploring behavioral evidence and learning
• Engineering and systems communicator
• Builder of public knowledge systems

I am drawn to systems where the important property cannot be observed directly. I try to separate what is visible from what is inferred, make assumptions explicit, and preserve uncertainty instead of hiding it behind confident language.

• Causality
• Non-linear systems
• Latent variables
• Uncertainty
• Evidence
• Context
• Upgraded questions

I am pursuing a Bachelor of Science in Mechanical Engineering at Arkansas State University. My academic work includes mechanics, thermodynamics, fluid systems, control systems, mathematics, programming, engineering design, and research.

• Statics and dynamics
• Thermodynamics and fluid mechanics
• Control systems
• Differential equations and engineering mathematics
• Programming and data analysis
• Mechanical design and SolidWorks
• Environmental and engineering research

My projects are practical experiments in building reliable systems under uncertainty. They are connected through shared questions about evidence, context, system behavior, and decision-making.

• TechShortsApp — credibility-first learning and ranking
• TechXEng — engineering, robotics, and systems thinking
• GlobalBriz — immigrant information and community infrastructure
• Personal knowledge system — connected projects, research, frameworks, writing, and media

I develop frameworks when recurring questions need a reusable structure. These models are not presented as permanent theories. They are current tools that can evolve as stronger evidence appears.

• SIGNAL — analyzing systems and their uncertainty
• Evidence of Learning — evaluating whether learning occurred
• Sufficient Understanding Framework — deciding when understanding is sufficient to act
• Behavioral evidence and credibility research
• Context-dependent interpretation of signals

My long-term direction is toward robotics, autonomous systems, reliable information infrastructure, and institutions capable of building under uncertainty. I am willing to develop that understanding over decades rather than force premature certainty.

• Robotics and human-like mechanical systems
• Autonomous and intelligent systems
• Reliable information and learning systems
• Research-driven engineering organizations
• Institution building

I try to build without pretending uncertainty has disappeared. I would rather fail while asking the right question than succeed by optimizing the wrong assumptions.

• When stuck, question Version 0 assumptions
• Decrease one uncertainty and expect two upgraded uncertainties
• Failing right can be more valuable than succeeding wrong

Niraj Kumar Chaurasiya is a mechanical engineering student, software builder, researcher, and technical communicator from Nepal. His work explores how engineering, software, learning, and information systems behave when truth is latent, signals are noisy, and decisions still need to be made. He is currently building TechShortsApp, TechXEng, GlobalBriz, and a connected public knowledge system while developing research and frameworks around evidence, learning, context, systems, and sufficient understanding.

AI should enhance and expand human capability, not replace human agency. Humans should remain the authors of their own lives.