Welcome!

I am an applied mathematician at Stanford University who researches how uncertainty propagates through models in science and engineering. That means I study how imperfect knowledge of a model input affects what that model outputs, and I rigorously quantify which model outputs are possible or more likely to occur. I am fascinated by this work, and it uses a variety of tools from statistics, linear algebra, probability, and scientific computing. 

Currently, I am serving as the President of the SIAM Student Chapter at Stanford. My academic CV and Google Scholar profile give additional information. 
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If you have any questions, the most efficient way to contact me is through email (lymanla AT stanford DOT edu​). I look forward to hearing from you!​

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Teaching

• In Fall 2021, I am the Primary Instructor for a course I designed entitled Advances in Computing with Uncertainties (CME 270). The official listing is here and the class webpage is here. 
• In Spring 2022, I am co-teaching Uncertainty Quantification (ME 470) with Professor Gianluca Iaccarino. 
• I am a recipient of the Stanford Centennial Teaching Award for the School of Engineering. I also received the ICME Departmental Teaching Award.
• ​The entirety of my teaching reviews can be found here. 

Research

• Four publications can be found on my Google Scholar or ORCID profile
• As of October 2021, there is a paper I have submitted to the Journal of Computational Science.
• Besides these five publications and my dissertation, I have an additional manuscript in progress.

Humor

• Randomly generate your own mathematics research paper here.
• Proof by intimidation. Argue why that proof is trivial here. Keep refreshing the page for more ways to baffle your colleagues.