What Iām Doing Now
A snapshot of what Iām currently studying, building, and preparing for.
Academics @ USC
I am currently an undergraduate student at the University of Southern California, focusing on data systems, machine learning, and mathematically rigorous foundations that support large-scale computing.
- DSCI 351 ā Foundations of Data Management
Data modeling, relational databases, indexing, NoSQL systems, distributed file systems, and parallel computation for large-scale analytics. - DSCI 352 ā Applied Machine Learning and Data Mining
Practical application and evaluation of machine learning models in data-intensive scenarios, with emphasis on real-world performance and trade-offs. - MATH 458 ā Numerical Methods
Numerical linear algebra, root finding, eigenvalue problems, approximation, and numerical solutions to differential equations, with attention to stability and error. - MATH 408 ā Mathematical Statistics
Hypothesis testing, confidence intervals, maximum likelihood estimation, likelihood ratio tests, and non-parametric methods. - MATH 430 ā Theory of Numbers
Prime factorization, congruences, primitive roots, number-theoretic functions, and Diophantine equations, strengthening mathematical reasoning and rigor. - CSCI 104 ā Data Structures
Core data structures including linked lists, balanced trees, heaps, hash tables, and probabilistic analysis of algorithms.
Preparing for TikTok SRE
I am actively preparing for my upcoming Site Reliability Engineering internship at TikTok. My focus is on strengthening system-level understanding and operational thinking, beyond coursework.
Currently Learning
- Ansible ā infrastructure automation, configuration management, and reproducible deployments.
- Observability ā metrics, logging, alerting, and understanding system behavior under failure conditions.
- Distributed Systems Internals ā reliability trade-offs, failure modes, and operational best practices.
Current Projects
I am working on small, focused projects related to infrastructure automation, data pipelines, and system reliability, with the goal of turning them into well-documented case studies.