Aspiring Software Engineer
Enrolled at Woodbridge High School with the hope of being a future Software Engineer or AI Researcher
Terminal
-npx
I’ve done a software development intership, entailing Python, HTML, and AWS projects. I am currently working on LLM image models, using ensemble methods - (e.x Random Forest). I play tennis and basketball, currently on Woodbridge High School’s tennis team.
EPCVIP inc - Date (June 2024 - August 2024)
Developed web application hosted on AWS (EC2, fargate, lambda, S3 buckets) to analyze financial data to suggest NYSE stocks Analyzed company financials to identify key web app parameters inputs; app-recommended stocks showed a 3-month 30% ROI. Gained experince with the use of yfinance and math operations in Python.
Google - Date (Jan 2025)
Understand the importance of cybersecurity practices and their impact for organizations. Identify common risks, threats, and vulnerabilities, as well as techniques to mitigate them. Protect networks, devices, people, and data from unauthorized access and cyberattacks using Security Information and Event Management (SIEM) tools. Gain hands-on experience with Python, Linux, and SQL.
Google Cloud - Date (Dec 2024)
Analyze and apply cloud security principles in practical scenarios. Develop and implement risk management and compliance strategies. Execute effective incident response and recovery plans. Prepare for a successful career in cloud security.
Amazon Web Services - Date (Jan 2025)
Make informed decisions about when and how to apply key AWS Services for compute, storage, database, networking, monitoring, and security. Design architectural solutions, whether designing for cost, performance, and/or operational excellence, to address common business challenges. Create and operate a data lake in a secure and scalable way, ingest and organize data into the data lake, and optimize performance and costs. Prepare for the certification exam, identify your strengths and gaps for each domain area, and build strategies for identifying incorrect responses.
Leet - Date (Jan 2025)
300+ Problems Solved in Leet Code (Top 7%). Top 15% Competitor for weekly contests, recently ranked 518 out of 28883 (Top 2%).
Irvine and Orange County Science and Engineering Fairs - Date (Sep 2024 - Present)
Earned 2nd Place at Irvine Science Fair and Competed in regional Orange County Science Fair. Currently working on getting papers published
Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by the progressive loss of nerve cells within the brain and spinal cord. ALS affects 450,000 people worldwide with a 20 percent survival rate by year 5. Early detection is critical to improve life expectancy and quality of life. Yet current diagnostic methods, like Electromyography (EMG) and Nerve Conduction Studies, are invasive, costly, and are inaccessible.There is a lack of research for cost-effective, accurate, and simple diagnostic methods. Biomarkers are measurable biological indicators that help detect the presence or progression of diseases. The detection of biomarkers offers a simple yet powerful detection method. For ALS, biomarkers P75NTR and neopterin,typically found in urine, are viable. A lateral flow immunoassay (LFA), enhanced by fluorescent labeling with quantum dots amplified nano-gold/nano-silver shell nanoparticles, offers a novel, sensitive, and specific method for biomarker detection. Biomarker detection is important, but correct interpretation is paramount for diagnosis. Our machine learning model paired with an interactive user interface, incorporates patient-specific factors (e.g., age, sex, ALSFRS-R score) and analyzes the LFA. It provides diagnoses with a 96% accuracy in real life testing. The model is able to intake images of nerve fibers after biopsy, and use nerve fiber/cell analysis to enhance diagnosis. Diagnosing ALS through the use of Machine Learning has rarely been tested, offering a new path in neurodegenerative disease diagnosis. This system offers a cost-effective, accessible, and advanced diagnostic hardware/software tool to address current limitations in ALS early detection.
Technologies Used: Artifical Intelligence, Lateral Flow Immunoassays
My Contribution: AI Development and helped create the diagnostic LFA tool
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations..
Technologies Used: Algorithms, Data Structures
My Contribution: Did a variety of Java based projects with Queues, Stacks, Trees, etc
Basic SMA auto trader for stocks, first file is base version, no logging. Second File is enhanced with logging. Reqiures the creation of a CSV file.
Technologies Used:MetaTrader5, Pandas, json
You can view my full Resume for more details.
View Resume (PDF)Feel free to reach out! You can connect with me via: