My Personal Statement

While hiking to Machu Picchu, I saw the stars blazing like beacons in the transparent, free-from-light-pollution, high-altitude sky. Like many others, the stars sparked my fascination for physics. However, after gaining perspective during my Bachelor's degree at the University of Manchester, I found astrophysics to rely too heavily on experimentally derived constants without theoretical explanation. This is likely a cause of the difficulty in acquiring valuable data due to the vast distances and limitations in observational technology. Consequently, I shifted my focus to theoretical quantum physics, which has the opposite concern; abundant data makes it challenging to find a framework that unifies all the findings.

I will pursue a master's degree to delve deeper into quantum field theory and general relativity, with a particular interest in studying neutrinos, and I plan to follow this with a PhD. In light of the current state of physics, where theories like SUSY and String Theory have faltered due to their reliance on mathematical beauty over testable results, I believe it is time to return to the fundamentals. That means analysing experimental data again to address discrepancies in the Standard Model, such as the puzzle of neutrino masses, without needing hypothetical colliders the size of continents, as required by proposals like the seesaw mechanism. In this context, while machine learning algorithms are already employed in research to analyse data and detect anomalies, I expect there is still significant potential for modern learning algorithms to be utilised more extensively. These algorithms could not only refine anomaly detection but also rigorously test and validate theoretical frameworks, bridging the gap between experiment and theory. I have been closely following the IceCube Neutrino Observatory's experiments, which aim to detect high-energy neutrinos from astrophysical sources.

Alongside studying neutrinos, I am eager to explore data visualisation and simulations, which are among the most effective tools for understanding physics. My theory computation project, a semester-long coding project, was about traffic simulations using cellular automata, enabling me to achieve just that. It allowed users to input the road setup and parameters to experiment and find the most efficient designs. It also generated useful graphs so they could analyse the efficiency of their different setups. This project deepened my coding skills and enhanced my ability to present complex information. The final presentation went remarkably well, demonstrating my confidence in public speaking and delivering technical content effectively.

I took Python, HTML, CSS, and Mathematica lessons, earning certificates in the latter three. However, these courses formed only a part of my overall proficiency, primarily self-taught. I am also fluent in JavaScript, which can be seen from this website. My coding skills enable me to manage complex data sets with multiple uncertainties and automate data analysis, reducing the risk of confirmation bias by minimising manual intervention.
As an extension of coding, I engage in 3-D modelling and graphic design, having learnt to use Blender, Fusion360, and Affinity Designer. These enhance my capacity to create clear, information-rich graphs and pertinent figures.
I also learnt to use Desmos to create interactive graphs, which helped me better visualise concepts and equations, specifically in relativity and quantum physics.
In my free time, I watch videos from creators such as Richard Behiel and 3blue1brown. I also read books such as Lost in Math by Sabine Hossenfelder, which made me question pursuing research, as they highlight the current disarray in physics. Yet, I remain hopeful that this buildup will soon lead to an explosive burst of discoveries. Additionally, reading What is Life? by Erwin Schrödinger impressed me with the efficiency of his reasoning, as he discards anything that cannot be proven.

Multiple trips, including to the Kennedy Space Centre and Star City Cosmonaut Training Centre in Moscow Oblast, have fostered my interest in physics. I met two cosmonauts and multiple engineers working on the next-generation Soyuz spacecraft, the Orel. I have attended conferences by Jean-Pierre Luminet and Lia Merminga. During high school, I wrote my EPQ on the neurological impact of space travel, primarily caused by fluids' behaviour in microgravity.

Running a global Minecraft server and managing a team of seven honed my leadership, technical problem-solving, and collaboration skills, which will be valuable in research and group projects during my master's studies.

I am driven to advance the field of theoretical physics by tackling unanswered questions in quantum field theory and general relativity, mainly through the study of neutrinos. Pursuing a master's degree will equip me with the skills and knowledge to contribute meaningfully to this pursuit, and I am eager to follow it with a PhD to make a lasting impact.