Kiran Bandi
Full-stack developer with a passion for Ruby on Rails, React, and machine learning. Startup-hardened, detail-oriented, and always learning — currently exploring Go for backend systems.
Building and maintaining web applications using Ruby on Rails and React. Full-stack work — API design, database modeling, frontend features, and deployments. Learned to move fast in a startup environment.
Graduated with a focus on machine learning and software engineering. Completed ML research projects: CycleGAN-based medical imaging, audio denoising with UNet, and face recognition systems.
Ride-sharing Android app with real-time location tracking, authentication, and payments.
Deep learning system removing noise from audio using UNet architecture and spectrogram transforms.
Translates MRI scans to CT scans using CycleGAN — enabling non-invasive diagnostic alternatives.
Research comparing LDA and CDLDA for face recognition, achieving higher accuracy with CDLDA.
Android ride-sharing app with real-time location and payments.
UNet-based deep learning model for audio noise suppression.
CycleGAN pipeline to translate MRI scans to CT scans.
Comparison of LDA and CDLDA for face recognition accuracy.
Full-stack apps with Rails backends, React frontends, and production-ready APIs.
Android-native applications and cross-platform mobile experiences.
Deep learning models for image, audio, and predictive analytics tasks.
Scalable APIs, database modeling, and backend architecture in Rails and Go.
Reach out via email or drop a message below.