Research Projects

This project focuses on aiding IPV research to understand the nature and prevalence of online IPV and to build foundations for detecting potential IPV

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This project aims to research and develop AI-assisted VIA screening using mobile-captured photos to build a more consistent and accurate smartphone-based

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This project aims to develop object detection models to detect diarrhea cysts from vegetables, stool, and water samples using images captured from a smartphone microscope.

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The main goal of this project is to do a landscape mapping of understanding and approaches to AI Ethics in Nepal among three key stakeholders: Technology

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The project involves (i) detecting all mutations in a large cohort of WGS (Whole Genome Sequence) data of Mycobacterium tuberculosis (Mtb), (ii) investigating

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The objective of the study is to design a geometric deep learning approach to identify whether a person is suffering from some sort of neurological disorder or

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The aim of this research is to build comprehensive techniques for detection, localization and segmentation of anomalies present in GI organs (not a

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CT scans are often taken to visualize internal body organs, diagnose pathologies and for surgical planning. These devices provide better visualization than X-ray

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We will first do a comprehensive review of the current state-of-the art of NLP tools and techniques developed for the Nepali language. The study will cover the areas

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This research aims to study the existing Nepali dialogue corpus (if any), identify their limitations, and create a new Nepali dialogue benchmark.

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We aim to design and implement a deep learning-based algorithm to classify different dystonia types and predict their severity by detecting patients’ gaits

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Water-borne diseases due to parasites such as Giardia and Cryptosporidium are still an important problem in Low-Income Countries like Nepal. Traditionally,

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Semi-supervised segmentation of medical images.

Supervised deep learning methods have seen tremendous progress with several successful applications since the resurgence of neural networks in the beginning

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2D US is the most common imaging modality for cardiovascular diseases and fetal scans. The portability and relatively low-cost nature of Ultrasound (US)

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Idiopathic scoliosis is one of the most common spinal deformities that can be potentially lethal if not intervened early enough. Cobb angle that provides a

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“My room” is an exclusive feature in Explorug, a product of Alternative Technology, that can overlay 3D objects onto a single RGB image. The feature uses

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Artificial Intelligence, Machine Learning and Deep Learning has been around for a while. Everyone is fascinated by them. In fact, hypotheses quoting them

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This is a multi-disciplinary research with an aim to empower everyone to be able to measure pesticide concentration present in the vegetables and fruits

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