About me
I’m currently a 4th Year PhD Student at the Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology. I work with Prof. Cristian A. Linte at Biomedical Modeling, Visualization and Image-guided Navigation Lab (BiMVisIGN). Before starting my PhD, I worked at NAAMII (a research institute in Nepal), Zeg.ai (a 3D AI solution startup), and NDS (an embedded systems and IoT startup). I completed my undergraduate in Electronics and Communication Engineering at Institute of Engineering, Pulchowk Campus, Nepal.
Research
My research focuses on data-driven medical image analysis using deep learning, particularly in scenarios with limited or noisy labeled data. I am interested in solving the challenge of how to create robust deep learning models/frameworks for tasks like medical image classification and segmentation when the available data has limited labels or contains noisy labels. Therefore, my research encompasses areas such as active learning, learning with noisy labels, active relabeling, self-supervised learning, and continual learning.
Through my PhD program, I have also built a strong foundation in Imaging Science, gaining expertise in various areas, including image acquisition, camera design, calibration, image processing, imaging display, human vision, and color science.
Interests: Medical Image Analysis, Learning with Noisy Labels, Active Learning, Continual Learning, Active Relabeling, Self-supervised learning, Multimodal Learning, Vision-Languge Pretraining.
News
[Oct 2023] Gave a short talk on my PhD research at PhD Research Showcase, in Industrial Associates Fall 2023 Symposium, Rochester, NY.
[Oct 2023] Attended MICCAI, 2023 at Vancouver, Canada to present our work on “Improving medical image classification in noisy labels using only self-supervised pretraining”.
[Jul 2023] Our paper titled “Improving medical image classification in noisy labels using only self-supervised pretraining” got accepted at Data Engineering in Medical Imaging workshop, MICCAI, 2023.
[Jul 2023] Presented our work on “M-VAAL: Multimodal variational adversarial active learning for downstream medical image analysis tasks” at MIUA 2023, Aberdeen, United Kingdom.
[Jun 2023] Our paper titled “M-VAAL: Multimodal variational adversarial active learning for downstream medical image analysis tasks” got accepted at Conference on Medical Image Understanding and Analysis (MIUA) 2023 for Oral presentation.
[Feb 2023] Attended SPIE Medical Imaging 2023 at San Diego, California, US to present our poster on “Investigating the impact of class-dependent label noise in medical image classification”.
[Nov 2022] Our paper titled “Investigating the impact of class-dependent label noise in medical image classification” got accepted at SPIE Medical Imaging 2023.
[Jul 2022] Joined Biomedical Modeling, Visualization and Image-guided Navigation Lab (BiMVisIGN), Rochester Institute of Technology, to work with Prof. Cristian A. Linte.
[Jan 2022] Joined AWARE-AI NRT program as Rochester Institute of Technology as Trainee.
[Oct 2021] Presented a poster of my work “How does heterogeneous label noise impact generalization in neural nets?” at IEEE Western NY Signal Processing Workshop, Rochester, NY, 2021.
[Jun 2021] Our paper titled “How does heterogeneous label noise impact generalization in neural nets?” got accepted at International Symposium on Visual Computing (ISVC) 2021.
[May 2021] Joined Machine and Neuromorphic Perception Lab (kLab), Rochester Institute of Technology, to work with Prof. Christopher Kanan.
[Aug 2020] Started PhD in Imaging Science at Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology.
[Apr 2019] Joined NepAl Applied Mathematics and Informatics Institute for research (NAAMII) to work as Research Assistant.
[Feb 2018] Started working at Nepal Digital Systems (startup company) as Firmware/Image Processing Engineer.
[Dec 2017] Completed undergraduate in Electronics and Communication Engineering, at Institute of Engineering, Pulchowk Campus, Nepal.