Ayushma Pudasaini

Designed a CNN-based deep learning pipeline to classify keyboard keystrokes from acoustic emissions and evaluated generalizability under real-world domain shift conditions. Achieved 82.50% accuracy on unseen environments and used Grad-CAM for interpretability and Optuna for hyperparameter optimization.

Developed CNN-based deep learning pipelines in PyTorch for detecting and classifying keyboard keystrokes from acoustic emissions, achieving 82.50% accuracy on unseen environments. Built an end-to-end ML workflow including audio onset detection, mel-spectrogram feature engineering, Optuna hyperparameter optimization, and Grad-CAM interpretability.

Designed and maintained production-grade full-stack web applications using Python, Django, and Django REST Framework, including RESTful APIs for React.js frontends. Implemented secure authentication, role-based access control, and deployed applications to production environments.

Resolved a failing spell-check CI pipeline by removing a non-alpha accented character from the allowlist configuration. Updated the accented term to its plain English equivalent to ensure the CI spell-checker accepted all allowlist entries.

Taught Modern Software Engineering, HTML/CSS, React.js, and Python backend development to junior students. Mentored students on deep learning and machine learning projects and provided hands-on feedback for React.js frontend and Django backend work.

Fixed a year offset bug in the PCF8563 real-time clock driver within Zephyr RTOS by correcting an epoch offset calculation. Followed Zephyr’s contribution workflow and documented the root cause, fix, and testing methodology with a LaTeX case study report and presentation.

Designed posters, social-media creatives, and event branding using Figma. Produced consistent layouts aligned with brand guidelines and delivered graphics on tight deadlines in collaboration with a team.

Activities and societies: Key modules: C/C++, OOP, DSA, Python, Django, React.js, AI/ML, Embedded Systems, DBMS, OS.

Pursuing a Bachelor of Computer Engineering at Pulchowk Campus under IOE, Tribhuvan University (expected 2027). Focus areas include deep learning, React.js frontend development, and full-stack web applications using Python, Django, and FastAPI.

Grade: GPA 3.5 (Biology: A, Physics: A+, Chemistry: A, Mathematics: B+)

Completed Higher Secondary (+2) in Science at United Academy, Kumaripati. Earned a GPA of 3.5 with top grades in Biology, Physics, and Chemistry.

Completed SEE at Shree Shivalaya Secondary School, Nuwakot.