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       <h1>Yuqi Tan</h1>
       I am a computational biologist with rigorous training in both statistical learning and cell molecular biology. My research goal is to design machine learning methods that will drive new biomedical discoveries, such as improving stem cell engineering protocols, discovering novel cell types from single-cell measurements, and inferring developmental trajectories during in vitro reprogramming. I plan to lead a research team to understand the high-dimensional spatial arrangement of cell types and how relationships are disrupted in disease by harnessing the power of single-cell multi-omics technologies and volumetric imaging. In pursuing these research goals, I am dedicated to creating an inclusive and open environment and mentoring a diverse team of young scientists to achieve their research vision.
-      <p> Professional training <br> Postdoctoral Fellow in <a href = "https://www.nolanlab.org/members/" class="external-link"> the Nolan lab </a> at Stanford University <br> BSc(Hons) at Chinese University of Hong Kong 2014 </p>
+    <p> Professional training <br> Postdoctoral Fellow in <a href = "https://www.nolanlab.org/members/" class="external-link"> the Nolan lab </a> at Stanford University <br> BSc(Hons) at Chinese University of Hong Kong 2014 </p>
 
       <a href = "https://scholar.google.com/citations?user=zNOpmasAAAAJ&hl=en" class="external-link">Google Scholar.</a>
 <!--      <p>I will be presenting singleCellNet at <a href="https://www.eventscribe.com/2019/ISSCR/agenda.asp?startdate=6/29/2019&enddate=6/29/2019&BCFO=M&tn=&cpf2=&cus2=&pta=&h=Sat,%20Jun%2029&pfp=FullSchedule" class = "external-link"> ISSCR 2019 consession IVE </a> (14:24 - 14:35pm, Jun29, Room 408B).</p>