AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
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Meet Hanyang Li, Ph.D. Candidate Who is Seeking a Research Job in Atmospheric Science
HANYANG LI, The Ohio State University
Abstract Number: 208 Working Group: Meet the Job Seekers
Abstract I am a Ph.D. candidate in Civil Engineering with an emphasis in atmospheric aerosols at The Ohio State University. I hold a MS (2016) in Mechanical Engineering from University of Colorado Boulder. I expect to complete my Ph.D. by May 2020 (if not sooner) and look forward to becoming a research scientist in the field of atmospheric science (e.g., a postdoc in either industry or academia). My primary career goal is to conduct high-quality and independent research with the help of advanced statistical or machine learning methods (such as deep neural networks).
The primary focus of my current research is constraining uncertainties in light absorption and black carbon (BC) measurements. Accordingly, my research objectives are to: 1). Quantify potential differences among the BC measurements and examine any systematic relationships between aerosol chemical/optical properties and observed differences; 2). Develop a generic correction algorithm for any filter-based absorption photometer to constrain BC estimates between different instruments; and 3). Predict BC optical properties utilizing deep learning approaches.
To meet these objectives, I am conducting both experimental studies (laboratory and field experiments using several aerosol-related instruments) and computational analyses (such as statistics and machine learning using Igor Pro, R, Python, and MATLAB). Specifically, I have worked on the following research tasks: 1). Conducting field experiments and operating instrumentation at U.S. Forest Service Fire Sciences Laboratory; 2). Analyzing the BC samples in the laboratory at OSU campus; 3). Using a set of statistical tools to understand the data; and 4). Developing artificial neural networks and other statistical models to constrain measurement uncertainties.
Overall, I enjoy addressing challenging research questions via creative and critical thinking. I believe my graduate education and research experiences would contribute to my future success in the professional career as a scientist in the field of atmospheric science.