Teaching
With curiosity and wonder, Dr. Suresh strives to instill concepts related to solving problems through instrumentation for agriculture, biological engineering, and animal sciences in educating students. With a firm belief that only through transdisciplinary efforts, complex societal problems can be addressed, it becomes essential for Prof. Suresh to infuse multi and cross-disciplinary approaches in teaching and education.
Big Data & Sensor Technologies for Animal Science
Course Aims:
Introduce and teach basics of data analysis and sensor technologies for Animal Science students. Applications involve data science and machine learning in animal omics analyses . The major goal is to provide the students with hands on experience in turning raw and unstructured sensor-based data in to valuable insights through statistical tools and visualization methods designed for practical applications in the animal science and veterinary industries.
Learning objectives:
- Discuss computer vision and sensor technologies used in animal production systems, and their possibilities and constraints.
- Discover unrecognized opportunities for optimizing animal health, production efficiency, and well-being
- Apply techniques to visualize and analyze basic features of sensor data.
- Interpret processed results based on advanced Artificial Learning approaches in the context of animal science.
- Report on data processing, analysis, and results.
- Recommendation systems, Decision support platforms development based on animal science sector case studies
Group Projects:
As part of the course requirement, the bioengineering and animal science students are expected to present their projects that solves a real-life practical animal sector problem based on the course lectures, assignments and the learning that happened during the laboratory training.
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BSc – Supervisor of BSc thesis students.
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MSc – Supervisor of MSc thesis students.
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Internship – Supervisor of Internship students.
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PhD – Supervisor of PhD thesis projects.