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Automated Pest Detection in PlantsIntern: Ernest Arinzechukwu Uch-EzeDegree course: Computer Science LinkedIn Profile
I have a deep passion for academic research. As a maths lover, it was clear to me which degree course would complement my strength. However, I chose my degree because I'm interested in developing computing skills to solve major problems, more specifically related to promoting environmental sustainability. My interest lies in AI/ML engineering, and I'm keen to develop my skills in that domain through exposure to real datasets and continuous learning. Outside academic studies, I apply my developing skills within the Software and AI team for the Lancaster Rocketry Society and an advocate for sustainability. Why did you apply for this internship?I saw this internship as an opportunity to build on my experience with classification models and enhance my problem-solving skills in a research environment.What do you hope to gain in completing this project?Upon completing this project, I hope to develop transferable research skills that enhance my ability to investigate problems and give actionable insights. Alongside refining how I communicate these findings, I also look forward to gaining experience with interdisciplinary collaboration and ultimately learn how to drive progress across domains.
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Revisiting the Risk Elicitation Puzzle: A Machine Learning ApproachIntern: Anand ChavaliDegree course: BSc Computer Science and Mathematics |
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GEM: a Domain-Specific Modelling Language for Disease Outbreak ModelsIntern: Crystal LeongDegree course: MSci (Hons) Mathematics and Computer Science As someone who loves problem solving, Mathematics and Computer Science was a perfect fit for me. One of the advantages of doing this particular course is the diversity in which you can apply yourself. The analytical and practical skills you learn build a strong foundation for a range of academic and industry careers, such as finance, cybersecurity and modelling. I personally find the use and development of libraries for specialised statistical purposes and broader machine learning to be particular areas of interest, and would love to pursue research or applied work in this field. Why did you apply for this internship?I applied because it is a great opportunity to further develop academic skills. The chance to be able to receive guidance and work collaboratively with experts in my field of interest is incredibly valuable. I was interested in this specific project and working with GEM because it aligns well with my interest in statistics and probabilistic programming. The GEM library stood out to me as it is both a powerful research tool and accessible to users, allowing epidemiologists to rapidly develop models while also providing a clear interface for statistics students learning to use modelling and inference methods. Being able to contribute to a unique project like this is what makes the opportunity particularly worthwhile.What do you hope to gain in completing this project?Through this project, I am hoping to gain hands-on experience with the design and implementation of an intermediate representation, low-level programming and GPU computing. More broadly, I am also looking forward to refining rigorous software engineering practices, which will be invaluable to me as an applied mathematician. I am actively considering undertaking a PhD in research programming, and this internship is a great opportunity for me to gain clarity of my future.
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Toward better energy and marginal carbon inten- sity data for research and teachingIntern: Luke NeedleDegree course: BSc Software Engineering |