Chapter 1: The Dangers of Pigeon-Holing

Pigeon-holing individuals is a limiting and absurd practice.

I’ve successfully transitioned from theoretical physics (PhD) to structural biology, then to startups, thermal/mechanical systems engineering, epidemiology, and ultimately to consulting as an NLU AI engineer/data scientist. Each of these shifts was made significantly more challenging due to the skepticism of employers who preferred to categorize me narrowly.

The initial employers in each of these roles deserve commendation for their willingness to consider unconventional candidates. I found fulfillment in each of my diverse careers. My interests spanned theoretical physics, engineering, startups, aerospace, AI, and a burgeoning fascination with biology—ultimately earning my place as a structural biologist in the tradition of Watson and Crick.

Despite my wide-ranging interests, I once turned down a job offer in aerospace because the position focused on electric drive-train systems for fixed-wing drones instead of avionics, which I had hoped to work on. In hindsight, that was a mistake. Nonetheless, I currently thrive in the realm of NLU AI, while still holding on to my identity as a physicist.

These fields present intellectually stimulating challenges. I’ve had the privilege of working across five distinct domains. My PhD in physics was crucial in a country—Australia—where opportunities for physicists were nearly nonexistent during the 1990s. It was disheartening to sift through job listings with no prospects for physicists.

Many people underestimate the versatility of physicists; we possess a broad skill set that includes coding, electronics, mathematical modeling, data science, simulation, experimental design, and even dabbling in chemistry and biology. I often had to navigate my way into roles, sometimes downplaying my background.

My journey began as a young enthusiast of microprocessors and an NLU coder on an Apple II in the 1980s, long before NLP/ NLU became mainstream. I had an equal passion for NLU, electronics, aerospace, and physics, which led me to explore protein folding—an even deeper dive into my interests.

My career choices were largely influenced by the lack of opportunities available in Australia, a country that undervalues the physical sciences and has organizations and leaders who fail to recognize the contributions physicists make. The pigeon-holing of my profession is indeed frustrating.

Had I known how arduous it would be to secure my first programming role after my time in physics and biophysics, I might have prepared differently. Despite having been coding since age 15, transitioning into a different field proved complex. However, this journey allowed me to explore nearly all of my interests over three decades, and I wouldn’t change a thing about my path.

Initially, I often felt like a fraud, yet I was incredibly fortunate. The sensation of being a career nomad has lingered, but I usually settle into new roles within weeks, surrounded by exceptional colleagues and supervisors—though they often fail to grasp the depth of my experiences.

Within weeks of being a PhD particle physicist, I found myself addressing a group of biologists about stroke recovery, 3D protein structures, marine biology, and drug design. I was amused when someone remarked on the hiring of a particle physicist in the structural biology lab.

This playful masquerade allowed me to immerse myself in biology, and most people were unaware of my true background—except those who examined my CV. Through my explorations in physics, biology, and AI, I encountered Nobel laureates and had the chance to visit the underground experimental halls of CERN, where groundbreaking discoveries like the W and Z bosons and the Higgs boson were made.

I even had the honor of sharing a meal with the last astronaut to step on the moon and the sole geologist from the Apollo missions, as well as lunch with the Deputy Director of the CDC. My journey also intersected with the individual who first solved a protein structure using NMR and the pioneer of X-ray crystallography.

In my early career, I developed an entire data entry operating system for my Motorola 6800 microprocessor board in 1981, which took me 18 months to complete. This was all before the internet era, relying on scarce resources like magazines for guidance. I learned how to program the EPROMs and successfully booted my OS, marking a significant personal achievement.

These were lonely yet profound moments that few truly understood. Over the years, I received some validation for my efforts, but often, my journey felt unrecognized. It became clear that I needed to find my own worth.

In 1980, I first encountered an Apple II at school, igniting my fascination with AI—much like HAL from "2001: A Space Odyssey." While other students played video games, I was busy creating my own and coding NLU applications. I believed then that NLP/ NLU would eventually lead to AGI, even without quantum computing.

Fast forward 40 years, and I am now an AI engineer and data scientist specializing in NLU, AGI, and Retrieval Augmented Generation. The initial challenge of securing a position as a self-taught data scientist was daunting, but I persevered, learning the nuances of cloud engineering and data science.

I faced the daunting whiteboard tests, where I struggled to navigate linked lists and tree structures in pseudocode—skills I had never needed until then. After many failed interviews, I taught myself to succeed in these challenges, as well as mastering various machine learning concepts.

Ultimately, I landed my first data science role by showcasing my own implementation of Naive Bayes for a customer churn problem I addressed for a friend's startup. The advancements in AI, computing, and cloud engineering have been remarkable, far beyond what I anticipated earlier in my career.

There was a prolonged period of stagnation in the fields of AI, physics, aerospace, and green technology. However, the recent explosion of innovation has been exhilarating. I’m enthusiastic about Tesla, SpaceX, and the rapid advancements in AI like GPT.

In my own startup focused on desktop search, I experienced a moment akin to that of Steve Jobs, receiving a standing ovation for our software, which vastly outperformed existing solutions. Unfortunately, we never got further development support, and our product was overshadowed by Microsoft Windows.

After taking a two-year sabbatical to work in green technology as a mechanical/thermal systems engineer, I played various roles in a startup that developed an eco-friendly evaporation technology. This small company allowed me to wear many hats—designing, managing projects, and engaging in sales—across Australia and China.

Yet, the challenges associated with being pigeon-holed as "just a physicist" remained. The lack of opportunity and proof of my capabilities nearly derailed my ambitions. These stories illustrate the hurdles faced when one's potential is underestimated due to a singular professional identity.

The missed opportunity of not completing an engineering minor compounded these challenges. My choice to pursue Applied Math instead of Electronics Engineering was a significant error, one that led me to wish for a different path. Later attempts to rectify this only reinforced the difficulty of changing course.

I've also navigated various roles, including an epidemiologist during a pandemic modeling phase, as well as diverse jobs like courier driver and chef's assistant. The quest for an aerospace position in Australia continues, with the latest setback being a rejection from Lockheed Martin.

Chapter 2: Embracing Opportunities and Overcoming Challenges

In this chapter, we delve into the experiences that shaped my understanding of the tech landscape and how to seize the moment in an ever-evolving field.

Through these experiences, I’ve learned that the road less traveled can often lead to the most rewarding destinations.