ResearchThemes

Research Themes

Brief

The Department of Computing and Technology is engaged in a variety of research activities, which are divided into six distinct areas. Our staff and students have been working hard to come up with innovative solutions to problems in each of these areas. To find out more, please select one of the following research topics:

1) Applied Computer Science

Systems and Networking is a wide-ranging and varied field of computing research that encompasses such topics as systems, networks, and distributed systems, programming languages and software engineering, compilers, databases and data science, security and cryptography, and mobile and wireless systems. The field of Security and Privacy examines the safeguarding of data and systems in a variety of computer science areas: operating/distributed system security, software security, network.

Systems and Networking is a wide-ranging and varied field of computing research that encompasses such topics as systems, networks, and distributed systems, programming languages and software engineering, compilers, databases and data science, security and cryptography, and mobile and wireless systems.
The field of Security and Privacy examines the safeguarding of data and systems in a variety of computer science areas: operating/distributed system security, software security, network security, data security, cryptography, and formal methods.
Theoretical Computer Science (TCS) examines the fundamental questions of computation by constructing formal models of computation and analyzing the resources required to address general and specific algorithmic issues. It investigates the development of efficient algorithms and the computational complexity of various computing tasks that come up in computer science, statistics, economics, and other disciplines.
Research in Artificial Intelligence (AI) investigates the concept of intelligence and how computation can be used to explain and create it. Our faculty research programs involve the use of machine learning, cognitive modeling, language comprehension and production, planning and reasoning, robotics and human-robot interaction, computational journalism, social media analysis, computer audition, computers and education, computational creativity, and legal reasoning. This combination of machine learning and semantic information-processing and knowledge-based reasoning provides a powerful tool for exploring the nature of intelligence.
Human-Computer Interaction (HCI) has been a rapidly expanding area of research and development over the past three decades, revolutionizing how we use computers. This field of study covers a wide range of topics, such as augmented reality, collective action, computer-mediated communication, computer-supported collaborative work, crowdsourcing and social computing, cyber learning and future learning technologies, inclusive technologies and accessibility, interactive audio, mixed-initiative systems, mobile interaction design, multi-touch interaction, social media, social networks, tangible user interfaces, ubiquitous computing, and user-centered design.
We design models, simulate, and construct systems that integrate sensors, displays, and novel optical components to enable new capabilities in cameras and displays for medical, agriculture, and scientific imaging. The same physical models we use to generate images (e.g. camera, material, geometry, and lighting models) can also be used to create algorithms that search through today’s large collections of digital images for more comprehensive scene understanding, leading to smarter, more intelligent cameras that enhance our visual perception. We use analytical tools and machine learning models to teach computers to interpret the visual world through techniques such as feature analysis, image segmentation, object recognition, edge detection, pattern detection, image classification, and feature matching. Computer vision and graphics have a strong relationship with many other areas of computer science such as robotics, human-computer interaction, and machine learning. As a result, many of the algorithms we develop have wide-ranging applications that go beyond simulation, optics, image processing, modeling, and visualization.

2) Data Engineering

Our Data Engineering research group is dedicated to cross-sectoral collaboration in the field of data science. We are focused on the analysis of large, dynamic, noisy and intricate data sets that are present in almost every aspect of modern life, and which have a significant economic and social impact. We combine research and education to achieve our goals. In almost every aspect of modern life, and which have a significant economic and social impact. We combine research and education to achieve our goals.

Our Data Engineering research group is dedicated to cross-sectoral collaboration in the field of data science. We are focused on the analysis of large, dynamic, noisy and intricate data sets that are present in almost every aspect of modern life.
Our Data Engineering research group is dedicated to cross-sectoral collaboration in the field of data science. We are focused on the analysis of large, dynamic, noisy and intricate data sets that are present in almost every aspect of modern life.

3) Informatics

Biomedical and health informatics applies principles of computer and information science to the advancement of life sciences research, health professions education, public health, and patient care. Bridging the gap between humans and computers in the healthcare sector, our Health Informatics research focuses on  the use of health data to enhance patient safety, outcomes, and quality. We use informatics analytics and tools to support clinical decision-making, clinical research, and patient involvement.

Biomedical and health informatics applies principles of computer and information science to the advancement of life sciences research, health professions education, public health, and patient care. Bridging the gap between humans and computers in the healthcare sector, our Health Informatics research focuses on the use of health data to enhance patient safety, outcomes, and quality. We use informatics analytics and tools to support clinical decision-making, clinical research, and patient involvement.

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At the AI & Agricultural Informatics Lab, we conduct design research and technology development to improve resilience in food and agricultural systems The exponential growth in data coupled with the rapid adoption of computing technology have become essential elements in the advancement of digital agriculture. Digital tools are being utilized on a variety of levels, from the field to the cloud. When these data sets are combined with crop and physical models, they create a wealth of information that can be used to gain insight into how intricate crop systems develop and interact with their environment. Research under this theme focuses on the creation, development, and implementation of AI and related technologies to promote scientific understanding and innovation in all areas of digital agriculture, from the molecular scales to the farm scales, and to provide decision support with the help of cloud computing and data analysis. Sample areas include;

  1. AI for Breeding and Crop Management, the use of AI for plant breeding, effective variety selection, and efficient management practices.
  2. Human and AI Collaboration for Agricultural Systems: the development of AI systems with human-in-the-loop capabilities for management and decision making on field.
  3. From Genomes to Phenomes: the development of bioinformatics and statistical capabilities to discover genomes, to associate genes to traits, and to elucidate interactions between genotypes and environments to effect various key phenotypic traits.
  4. Databases: the development of community databases that provide access to field data alongside genomic and phenomic data sets.

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4) Mechatronics and Robotics

Mechatronics & Robotics researchers at Uganda Christian University are eager to explore the boundaries of mechanics, electronics and computing through a variety of pioneering projects. A great deal of this work is focused on robotics; our staff and students are striving to be at the cutting edge of research in robotic applications for automation, advanced manufacturing, agriculture and healthcare in developing countries. Key areas include, Robotics and human interaction, Robotics for manufacturing, Controls and system dynamics,

Mechatronics researchers at Uganda Christian University are eager to explore the boundaries of mechanics, electronics and computing through a variety.

Mechatronics researchers at Uganda Christian University are eager to explore the boundaries of mechanics, electronics and computing through a variety of

5) Computational Transport Engineering

Computational Transportation Engineering is a new field of study and research that combines computer science, engineering, modeling, planning, and economics to improve the safety, mobility, and sustainability of transportation systems. It utilizes information technologies and ubiquitous computing to go beyond vehicular technology and address pedestrian systems on hand-held devices. Additionally, it looks into transport data mining (or movement analysis) and data management.

Computational Transportation Engineering is a new field of study and research that combines computer science, engineering, modeling, planning, and economics to improve the safety, mobility, and

Computational Transportation Engineering is a new field of study and research that combines computer science, engineering, modeling, planning, and economics to improve the safety, mobility, and

6) Computational Sustainability

Computational Sustainability Research focuses on the development of computational and mathematical models, techniques, and tools to assist with decision-making and policy-making related to the management and distribution of resources for sustainable development. It utilizes computing and AI for the benefit of humanity and the preservation of our planet, i.e., it seeks to balance societal, economic, and environmental resources for the future prosperity of mankind using methods from mathematics.

Computational Sustainability Research focuses on the development of computational and mathematical models, techniques, and tools to assist with decision-making and policy-making related to the management and distribution of resources for sustainable development. It utilizes computing and AI for the benefit of humanity and the preservation of our planet, i.e., it seeks to balance societal, economic, and environmental resources for the future prosperity of mankind using methods from mathematics, computer science, and information science fields. Sub-areas of research may include; Green computing, the design, manufacture, use, and disposal of computers, chips, other technology components and peripherals in a way that limits the negative effects on the environment, such as reducing carbon emissions and the energy consumed by manufacturers, data centers.

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P. O, Box 4, Mukono – Uganda