Benjamin Zheng

Benjamin Zheng
Home Institute: University of Toronto
Supervisor: Dr. Kieran Campbell 

Hello, my name is Ben, and I am a biochemistry/chemistry student at the University of Toronto currently in my fourth year of study (graduating this coming May 2021). I am very interested in medicinal chemistry and design, optimization and synthesis of new drugs. Since childhood, I have been interested in combatting infections pathogens and hope to be able to contribute to this field in the future through creating therapeutically active compounds. Outside of school and research, I enjoy going to the gym, running and watching anime. I am currently on the University College Dragonboat team and, although many competitions have been cancelled over the past year, I hope to be able to compete with my team soon. 

Project Title: Making clinical machine learning from gene expression ore robust via data augmentations.  Although my prior research experience has primarily revolved around revolved around wet-lab expression of proteins and determination of function or the synthesis of novel small molecules for therapeutic purposes, I am excited to try something new in the Campbell lab this summer. My project for the summer will be based around increasing the robustness of clinical machine learning models from gene expression data to a range of perturbations through clinically plausible data augmentation. Due to the importance of machine learning models currently being used as biomarkers for treatments of patients, it is important to ensure that increase the robustness of the models to data that may be different from what was used to train the AI.

Conducting this machine learning project will be a great way for me to learn to code and to be able to apply this new skill to a research project.  In particular, this project will help guide my decision on whether I would like to pursue a graduate degree and career on the more computational side of chemistry and open new career options for me. I am particularly excited for the Amgen program because I will be able to network with a variety of talented scientists from all different backgrounds and expand my connections and knowledge base.