Description of field of research:

Solar photovoltaic (PV) energy plays a critical role in reducing the emission of carbon dioxide and other greenhouse gases into the atmosphere. The cost of PV must be further reduced for it to realize its full potential as a major energy source.

We have three projects in our group. The output of these research will further push down the cost of generated electricity with PV. Student can choose one of the three projects based on their interest. The below-mentioned projects can also be extended to a 4th-year project.

Project 1:
We aim to replace the expensive camera with inexpensive ones in combination with a machine learning algorithm. These algorithms are widely used in medical imaging field; however, they are untouched in PV. The student will implement the well-established machine learning technique for PV images.

Project 2:
Nowadays, the solar manufacturer can produce billions of cells a year which generates a huge amount of data. Unlike other manufacturing industries, PV industries are not using data to its full potential in decision making and improving their production line. Advanced analytics and machine learning would be used to produce insightful information from big data to optimize the production line.

Project 3:
The solar photovoltaic industry is growing in leaps and bounds through continuous innovation in manufacturing systems over many years. Advanced analytics and statistical techniques on big data will be used to explore the underlying pattern to help in making informed decisions.

Research Area

Luminescence imaging |
Machine Learning |
Deep Learning |
Statistical techniques |
Advanced analytics |
Big data

The research will be done in one of the most passionate and growing research teams in SPREE. The team consists of five experienced researchers and eight PhD students. The student will receive close guidance from one researcher and three PhDs. High-end workstations with TITAN V and RTX 3080 GPUs will be used to train the algorithms.

Three of our previous ToR won the 'Best Project' Award. Most of them continue to 4th Year project with us and two of them are currently PhD students within the group!

This work will lead to being published in one of the leading scientific journals. These projects have great promise in reducing the cost of solar cell production and further enabling widespread adoption.

Project 1 and Project 2: A basic understanding of python is required. Any experience in machine learning either through courses or projects would be appreciated.
Project 3: A basic understanding of maths and have a strong passion to move things with data.

Moreover, the student is assumed to have gained knowledge about solar cells through the following courses:

  • SOLA2540 Applied Photovoltaics
  • SOLA3507 Solar Cells