Tiejun is in his third year of PhD at Queen Mary University of London and now full-time based at The Alan Turing Institute. After receiving a B.Sc. degree in pharmaceutical science from Peking University, he continued his master’s study in the field of drug discovery at University College London. With great interest in machine learning he is eager to find a new way to implement advanced analytical methods to the quantum chemistry field. Currently he is leading a project focusing on the structural influence on carotenoid excited state properties, which potentially has a great impact understanding photo-protection.
Tiejun is currently leading his own research implementing machine learning and other advanced statistical analysis to quantum chemistry study. Specifically, his project focus on discovering possible molecular structural influences on the excited state properties of carotenoids. Those ubiquitous pigments carry out the dual function of harvesting light as well as defending against high light by quenching excess energy. The latter one has been intensively studied for decades and the key to the problem still lies within the carotenoid excited states. Tiejun’s research involves diverse computational techniques spanning across quantum chemistry, computational biology and biophysics. Revealing this mechanism not only improves our understanding in quantum chemistry but also has great impact on agricultural and photovoltaic studies.