• Development of deep learning methods to target formerly "undruggable" diseases through circular RNA therapeutic design

• Development of deep learning methods for protein/RNA folding and design• Responsible for mentoring undergraduate and graduate thesis projects

• Development of deep learning methods for protein/RNA structure prediction and design• Development of physics & statistical methods for protein structure prediction and design• Design and experimental validation of therapeutic proteins targeting important pathways involved in cancer and COVID-19• Served as web master for the Zhang Lab server system, which has been used by more than 160,000 users from 158 countries and territories

• Development of imaging technology for in vivo dosimetry during external beam radiation therapy• Cherenkov radiation detection using silicon photomultipliers• Software design for Monte Carlo verification of radiation therapy treatment plans

• Creation of paper-based diagnostic tests for tuberculosis and temperature-dependent kill switches for bacteria• Leader of public outreach team• Received silver medal recognition at the International Genetically Engineered Machine (iGEM) competition in 2016 and bronze medal recognition in 2017

• Novel HSP90 small molecule inhibitor discovery and pharmacological profiling• Performed viability assays to determine the EC50 values of numerous novel HSP90 inhibitors• Investigated the synergistic effect of combination therapy through Western blot analysis of proteins involved in the mTOR pathway, heat shock response, translation initiation, EMT transition, and apoptosis• Carried out quantitative RT-PCR to assess the efficacy of combination therapy in attenuating the unfolded protein response