Academically, I learned about the basics of quantum computing, some different algorithms, and got resources to self-study Quantum Machine Learning. I learned about some of the theory underlying modern AI systems today via CS 4365 (Artificial Intelligence), I got to familiarize myself with different LLMs and see how they can be used in combination with AI Agents to drastically improve the output and the quality of work that I would do as a Software Engineering Intern at Atlassian over the summer, via CodePath’s AI101. I got to explore the broad topic of Explainable AI, to get a decent understanding of what it is and how to apply it in different settings.
Research-wise, I got to see how multiple fields can overlap in a single project. I got to lead a project for undergrads, to take direction and initiative with it, similar to what a first/second year PhD student might do. Sadly, I didn’t get a publication from either of the two research experiences that I had over the semester, but hopefully before the start of Fall 2026, one will be submitted to a top CS/SE conference.
I applied to lots of different programs, which include AI4ALL (AI Ignite), Break Through Tech, CodePath AI201, and Algorythm. These programs are good for networking and learning/reinforcing different skill sets (DSA, AI, SWE)
Things I’m doing over the summer
Some learnings that I took from this semester:
i got into AI4ALL and Break Through Tech, hopefully i can compete for those AI/ML or research roles in industry next summer
]]>i’d like the website to have like a unique feel to it, not to modern, but kinda chill? i think i’m going to try to vibe code it, at least i’m going to learn a lot about the using claude code and github copilot to run most of the code while I start thinking more about system design
i’m going to take some inspiration from jkwon.co, leahuriarte.com, haileycheng.com, and minchaechae.github.io
]]>as for my favorite types, i think i liked the gold california roll, chicken teriyaki roll, and the louisana roll. in general, there had to be protein in the roll, and that protein had to be cooked for me to enjoy it usually. soy sauce can either help or mess up the taste test tbh.
i also learned that i gotta upgrade my chopstick game. it was actually frustrating to eat sushi with the chopsticks, so much that i got a fork, and even with the fork sometimes the middle part of the sushi would completely fall out just leaving me with the seaweed and rice
thinking back introspectively, it was pretty funny though. i’d rate sushi like a 6/10, something that i can eat, but definitely nowhere near my first choice
]]>Since we’re moving from 2025 -> 2026, here are some main goals that I have in mind to accomplish:
One of the biggest changes this semester was how much more I engaged with people. I stopped treating outreach as something to do only when I needed a favor and instead started checking in, building relationships, and being genuinely curious about others. Through Code2College, I got my first mentor and picked up a better sense of “why?”—why people make the choices they do, why communication lands or falls flat, and how much body language and confidence shape the way I come across. That mindset carried over into industry and academia, where being more proactive led to more opportunities, from ideathons to research with multiple professors, and reinforced that people really do love talking about themselves if given the space and the right questions.
The sheer intensity of this semester also forced me to get serious about systems. Juggling a heavy course load, research, recruiting, and life meant I had to constantly re‑evaluate how I was managing my time instead of just pushing harder with the same broken approach. After midterms, it became obvious that the foundations I had laid were solid but incomplete—so I made myself iterate: new routines, better planning, and a fixed sleep schedule that made everything else more sustainable. Once those changes kicked in, the “rose growing from concrete” feeling finally started to show up: my grades rebounded, I was more present in class and meetings, and I had enough energy to say yes to things like ideathons and research instead of constantly playing catch‑up.
There were still misses. I fell just short of the all‑A’s semester I was gunning for, got rejected from a lot of companies, and couldn’t get Algoverse AI Research off the ground the way I had hoped. But those “failures” did not cancel out the wins—they sat alongside them: securing a summer internship with Atlassian in SF, winning my first ideathon, doing real research with professors, and solidifying a healthier daily rhythm. The rejections and stalled projects mostly highlighted where my systems, timing, or bandwidth weren’t there yet, not that I was fundamentally incapable.
Looking ahead, grad school is still the big question mark. My CV is strong enough for a lot of master’s programs, but when stacked against applicants for top‑tier Ph.D. and post‑bacc routes, it is easy to fixate on what is missing: no publications yet, a GPA that is passable at best, and projects or research that are still in progress instead of already wrapped up with a bow. At the same time, this semester proved that when the stakes rise, I can adapt, tighten my systems, and actually deliver: nearly all A’s, deeper research involvement, and a growing network across industry and academia. That combination—real growth, a clearer sense of “why,” and the willingness to iterate—is exactly what needs to carry into the next year as I turn this momentum into a profile that feels Ph.D.‑ and post‑bacc‑ready, not just “good enough” for grad school on paper.
1 ideathon
3 certifications
7 classes
19 credit hours
147 notes
165 commits
1208 followers
CS 3345 – Data Structures & Algorithms
CS 3354 – Software Engineering
CS 3377 – Systems Programming in Unix & Other Environments
CS 3341 – Probability & Statistics in CS/SE
CGS 3346 – Python for BioBehavioral Data
ECS 2390 – Professional & Technical Communication
CS 3162 – Professional Responsibility in CS/SE
CS 4341 – Digital Logic & Computer Design
CS 4141 – Digital Logic Lab
CS 4347 – Database Systems
CS 4301 – Fundamentals of Quantum Computing
CS 4365 – Artificial Intelligence
PHYS 4350 - Quantum Algorithms & Software