Round Corner
Department of Computer and Information Science

Prosjekt 2023

Prosjektønsker kan registreres fra 1. april 2023.

Velg hva du ønkser å vise prosjekt for.





Faglærere (6)

Sorter etter:

Oppgaveforslag (9)

Artificial Intelligence in the Healthcare sector

Advanced forms of analytics and aritificlai intelligence are becoming increasingly deployed to support the work of healthcare workers. Medical doctors, nurses, and administrative staff either use, or are aided by sophisticated technologies which are posed to radically change the nature of their work. For example, radiologists now rely increasingly more on machine learning techniques to and other applications of AI to diagnose patients, while a lot of procedural and repeptive tasks are being done by machines. The objective of this project is to understand how the nature of work for health practitioners is changing, and what positive and negative consequences they experience.


Faglærer: Patrick Mikalef     Status: Valgbart     Egnet for: En student     Lenke: plink

Blockchain-based Data Marketplace

The European regulations about privacy, the GDPR, is changing people’s understanding and attitude towards data/information they own and those the others own. The ownership of data/information has always been a concern but with GDPR there will be more awareness as well as more obligations related to data collection and sharing.

Faglærer: Hai Thanh Nguyen     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Climbing Mont Blanc Back-Ends and Energy Efficiency Analysis

Climbing Mont Blanc (CMB) is a system for training and competitions in energy efficient programming of small processors. CMB has been using a heterogeneous multicore (MPSoC, Exynos from Samsung) in more that five years. The chip is accessed via an Odroid XU3 board that has integrated energy monitors. These boards are no longer produced, and the energy measurements are not as precise as we would like. The goal of the proposed project is to be able to use one or two newer single board computers (SBC) as CMB back-end and the Lynsyn system to achieve more precise energy measurements. The project can be continued as a master thesis project in the spring semester.

Faglærer: Lasse Natvig     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Decentralized AI

Nowadays, big tech giants, such as Google, Facebook, Amazon, IBM and Microsoft, are dominating the AI market by offering cloud-based AI solutions and APIs. They are collecting user data in one place through free services and systems, analyze it for insights and resell to third parties, such as advertisement companies. This model is centralized AI, which is working fine now. But in the long-run it could lead to monopolization of the AI market. This could also cause unfair pricing, lack of transparency, interoperability, privacy issues and excluding smaller companies from AI innovation. Fortunately, there is the emergence of a decentralized AI market, born at the intersection of blockchain, on-device AI and edge computing/IoT.
In this project, we will investigate the possibility to build a proof-of-concept of a decentralized AI application through blockchain, such as Ethereum. AI agents will train and learn models from their own data. The decentralized AI application to be developed in this project then can combine multiple algorithms/models (developed by different agents) performing different sub-tasks. One of possible applications is Decentralized Autonomous Cars. 1 - 2 students.

Faglærer: Hai Thanh Nguyen     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Deep Learning to combat with micro-plastic pollution

An estimated 275 million tonnes of plastic waste was produced on a global scale in 2010, with 8 million of those tonnes being introduced to the oceans - about 3% of global annual plastics waste. Once the plastic reaches the oceans, it is broken down into smaller particles(micro-plastic) by being exposed to ultra violet (UV) radiation and mechanical abrasion from wave actions [1].The quantity of plastic waste floating at the ocean surface in 2013 was estimated to be approximately 269,000 tonnes (small macro- to micro-plastic), this estimate does not include plastic in-depth or at the seafloor). The plastic debris can affect the wildlife in multiple ways, such as entanglement- entrapping, encircling, or constricting,ingestion- accidental ingestion or ingestion of prey containing plastic, and interaction- being in contact with plastic debris [1].It is therefore important to be able to detect and collect the plastic waste in nature,before it reaches the oceans. Once plastic waste has reaches a micro-stadium, it is near impossible to collect it and remove it from the water. An analysis on deep sea locations(range from 1176 to 4843m) showed that there was an average abundance of 1 micro-plastic per 25cm3(particle sizes ranging from 75 to 161μm) [2]

Faglærer: Hai Thanh Nguyen     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

General Data Protection Regulation (GDPR) and opportunities it brings: analysis of my all-data and generating insights

After enforcement of GDPR (General Data Protection Regulation) (May 2018), all companies and institutions collecting data about individuals are obliged to deliver to people the data they collected about them (e.g., whatever facebook, google, amazon, insurance companies etc collects about me shall deliver the data they collected about me when I asked for it). GDPR will give a chance for people to look into her/his data stored by those companies.
So, what people can do with so much (and rich) data about themselves? It would be super hard for them to analyze, extract insights and even look into the raw data downloaded from Facebook, Google, etc..

Faglærer: Hai Thanh Nguyen     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Machine learning for reverse engineering of unknown instruction set architectures and custom virtual machines

Reverse engineering (RE) is the process of discovering features and functionality of a hardware or software system. RE of software is applied where the original source code for a program is missing, proprietary, or otherwise unavailable. Motivation for RE ranges from extending support of legacy software to discovery of security vulnerabilities to creating open source alternatives to proprietary software.

Faglærer: Donn Alexander Morrison     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Sporing av sau ved hjelp av enkel radioteknologi

Sporing av sau ved hjelp av enkel radioteknologi

Faglærer: Svein-Olaf Hvasshovd     Status: Valgbart     Egnet for: Gruppe     Lenke: plink

Volume rendering on a mixed reality device

The project will investigate the possibility of implementing volume rendering techniques directly on a mixed reality headset (e.g. Microsoft HoloLens). Main purpose is to visualize patient-specific ultrasound data and/or computed tomography scans and combine them with geometric models representing structures of interest.


Faglærer: Gabriel Kiss     Status: Tildelt     Egnet for: En student     Lenke: plink
NTNU logo