Jan 2024 – Jan 2025 · 1 yr · On-site

• Spearheaded AI education and innovation by organizing hands-on workshops on AI and Deep Learning, fostering technical skills and collaboration among students.
• Coordinated and executed coding competitions, including a campus-focused vision challenge where participants developed an image classifier with over 98% accuracy on private test datasets, showcasing real-world AI applications and advanced model development.
• Led engaging lab tours, AI seminars, and industry-focused events, connecting students with cutting-edge trends and fostering a vibrant AI community.
• Promoted teamwork and creative problem-solving through initiatives encouraging members to explore and implement state-of-the-art AI techniques.

Aug 2023 – May 2025 · 1 yr 9 mos · On-site

• Collaborated with researchers from Stanford and Princeton to develop GANs & Diffusion Models, improving image restoration accuracy by 20%.
• Worked in the Raptor Robotics research lab of Dr. Jingdao Chen.
• Spearheaded ML deployment by developing CI/CD pipelines with Docker and Kubernetes, enabling automatic container orchestration on AWS EC2 with the help of Apache Airflow.

Feb 2023 – Aug 2023 · 6 mos · Victoria, Australia · Remote

• Developed a Large Vessel Occlusion(LVO) detection system using computer vision and deep learning skills compared to traditional techniques.
• Deployed developed model with serverless configuration as API, which leads to improvement over inference time and is highly scalable.
• Led Proxmed AI team as team lead and worked closely with the physician, which led to an improvement in LVO detection system accuracy compared to other competitors.

Feb 2022 – Apr 2022 · 2 mos · Singapore · Remote

• Led AI research team on synthetic datasets generation from limited genuine disease images using Dataset-GAN and start-of-art few-shot GAN architectures, enhancing data availability for model training in data-scarce scenarios.
• Boosted disease classification accuracy by 7.25% by training on synthetic datasets generated via few-shot GAN architectures.

Dec 2021 – Jun 2023 · 1 yr 6 mos · Kathmandu, Bāgmatī, Nepal

• Instructed undergraduate courses in Machine Learning, Cloud Computing, and Advanced Java.

Oct 2020 – Oct 2021 · 1 yr · Bellevue, Washington, United States · Remote

• Researched, developed Deep Learning Medical Image Diagnosis Model: Diabetic Retinopathy, Skin Lesion and Lung Disease Detection model.
• Implemented FocusNet paper and made Skin Lesion Segmentation Model with state-of-art
• accuracy.
• Developed UIs for Machine learning Disease Detection with React, HTML, and CSS and deployed
• with docker in AWS instance.
• Led end-to-end development of ML solutions, transitioning research concepts into production healthcare products.
• Designed Machine Learning Pipeline for Medical Image Diagnosis data related to any disease for
• automatic Training of Machine learning models actually by the user online.

May 2020 – Sep 2020 · 4 mos · Nepal

• Worked as Deep Learning , Computer Vision Engineer.
• Made video summarization and scene finding project using state-of-art Deep Learning model.

Feb 2020 – Jun 2020 · 4 mos · Nepal

• Research In Computer vision as Multi-lingual Handwritten Recognition System
• Worked under the Prof. Dr. Suresh Manandhar
• Worked on training CNN, LSTM, Sequence Models, GANs on GCP, AWS using Pytorch, Tensorflow and Keras.
• Study what progress is on the current research and develop a new one method to work on.
• Implemented cycle GAN/ Text2Image GAN to synthesis handwritten generation.