Building systems that think, perform, and look beautiful.

I'm a Graduate Student passionate about building reliable, scalable software systems, spanning modern web frontends, backend services, and cloud infrastructure.

About Me

I'm an engineer with passion for creating intuitive, accessible, and beautifully crafted user interfaces that seamlessly blend thoughtful design with robust engineering. I thrive at the intersection of design and development, where I can build experiences that not only look stunning but are also meticulously optimized for performance and usability.

Currently, I'm Graduate Student at California State University, Northridge, specializing in Computer Engineering. With strong focus on computer science disciplines such as AI, machine learning, and software development. My journey has been shaped by combination of professional experience, academic achievements, online certifications, and hands-on learning through building impactful projects.

In the past, I've had the chance to work on variety of exciting projects, from building dashboards and CMS platforms at LogiNext Solutions. I love creating accessible, high-performing web experiences and enjoy working across both front-end and back-end technologies like ReactJS, NodeJS, and MongoDB. Beyond coding, I've always been passionate about sharing knowledge—whether it's as CSUN Peer Educator or through my involvement in the CSUN Entrepreneurs Club , where I find joy in collaborating with others and exploring new ideas.

In my spare time, I love immersing myself in nature through hiking, diving into captivating books, spending quality time with my friends, cooking, and creating joyful moments with my three playful pet dogs.

Experience

A timeline of roles where I shipped product, scaled systems, and improved performance.

Software Engineer Intern
Marketeq DigitalAug 2025 - Nov 2025
- Created a robust database schema in MarketEQ and integrated it with the application for reliable data storage and retrieval.
- Optimized PostgreSQL performance through query optimization, index redesign, and execution plan analysis, reducing P95 API latency by 26 ms under production traffic.
Teaching Assistant
CSUNJan 2025 - May 2025
- Provided one-on-one and group tutoring sessions to students in computer science subjects, including programming, data structures, and algorithms.
- Assisted students in debugging code and solving technical problems using languages like Java, Python, and JavaScript.
- Led study groups to help students prepare for exams and complete programming assignments effectively.
- Collaborated with faculty to identify common learning challenges and create supplementary learning materials.
Software Engineer
LogiNext SolutionsOct 2021 - Jul 2024
- Delivered a dynamic Form and List Builder spanning React and Java microservices, enabling real-time schema updates and reducing configuration effort by 40% for 100K+ daily users.
- Diagnosed and resolved 500+ critical production bugs, improving system reliability and delivering a ~20% performance gain across core application flows.
- Developed a scalable AWS Lambda–based microservice to retrieve and process order reports for 500,000+ daily orders, reducing manual data collection efforts by 50% and improving reporting efficiency.
- Migrated key application modules from AngularJS to ReactJS, collaborating closely with backend services to ensure seamless integration. Achieved an ~80% performance improvement, significantly enhancing responsiveness and UX.
- Designed and implemented a centralized Redmine Project Dashboard using ReactJS and Java to visualize project metrics, track task progress, and monitor team performance. Reduced report generation time by 60% for 15+ team members, streamlining project workflows.
- CMS Platform Leadership: Led the development of a custom CMS platform with a team of 3 engineers, using ReactJS and NodeJS to manage blogs, articles, and multimedia content. Improved content management efficiency by 35% and reduced publishing time by 25%.
- Built an intelligent Auto Assignment engine for trip management using order locations and saved configuration rules to automatically select optimal trips. Reduced manual assignment time by 20–25% across 10,000+ daily trips, improving operational efficiency.