San Francisco, California, United States
I’m a junior Computer Science major at Minerva University, passionate about using technology to solve real problems and eager to grow in fast-paced, impact-driven environments. I have experience across AI/ML, backend, and full-stack development, with proficiency in Python, JavaScript/TypeScript, Next.js, Node.js, Firebase, and SQL. In past roles and internships, I’ve contributed to AI-powered applications and scalable backend systems, always with a focus on learning quickly, adapting to new tools, and delivering outcomes that matter. What I bring to any workplace: ● Fast learning & adaptability – I pick up new technologies and concepts quickly, turning them into concrete results. ● Collaborative energy – I’m communicative, open, and proactive in building strong teamwork. ● Purpose-driven mindset – I care about meaningful impact and align my work with broader goals. ● Positive ownership – I take responsibility, stay curious, and contribute to both team performance and culture. My aspiration is to keep growing in fast-paced, growth-oriented environments, where I can build, learn, and contribute to teams that are pushing boundaries.
Central Asian Ladies Initiative (CALI) is a forum for women from Central Asia in Silicon Valley, where they can connect, develop professional skills, empower each other, and contribute to the community. - Built virtual (multipage website) and physical platforms in the form of monthly events and workshops (30–40 attendees each) for 550+ women; - Developed a responsive UI and increased the mobile visits to 50% in the first 2 months
- SpoilSense: Developed end-to-end AI app using OpenAI API to predict product spoilage from image inputs. Integrated geolocation, weather API (temperature, humidity), and user-defined storage data. Built with Next.js, Firebase; implemented image-based inference, data persistence, and notification system. - Devastation: Built a satellite image analysis app to detect disaster damage and suggest emergency actions. Integrated custom ML models, geolocation, satellites real-time image API, and OpenAI API for automated damage reports. Tech stack: Flask, Next.js.
- Implemented end-to-end API encryption using AWS KMS and envelope encryption to protect international student records from 3+ South Korean universities - Built secure key management with CMK/DEK separation and JavaScript encryption logic - Ensured GDPR compliance and reduced development time using trusted libraries
Food Spoilage App is an AI model that allows users to predict how a fruit will look in 24 hours, see how temperature affects it, identify if a fruit is rotten or not, and share products with other users. - Worked on Hyperparameter tuning using Optuna - Expansion of the LSTM model on different fruit types such as melon and watermelon - Handled business side of the project by strategically reaching out and negotiating with sustainability startups in the USA
Employed web scrapper tools such as Selenium and BeautifulSoup to build a Python code for professors to access editable data in Forum (our proprietary LMS) Workbooks outside of the system as PDF zip files
Used UI and UX principles to redesign key features, including 1000+ student opportunity databases and search engine