Adam Li

About Me

Research Work

For a list of my publications, see my Google Scholar. If there are any publications not publicly accessible, please shoot me a message and I'm happy to share with you.

I am a sixth year PhD student in biomedical engineering, specializing in computational neuroscience and machine learning at Johns Hopkins University. I work with Dr. Sridevi V. Sarma in the Neuromedical Control Systems group. I am also jointly pursuing a MS in Applied Mathematics and Statistics with a focus in statistical learning theory, optimization and matrix analysis. My thesis work focuses on developing algorithms in the context of seizure localization in drug-resistant epilepsy patients. Specifically, I analyze multivariate time-series intracranial EEG data using dynamical systems, control theory, machine learning and statistics. I combine biological understanding of the brain with mathematical models of dynamical systems. I also utilize machine learning and statistical models to answer relevant hypothesis-driven questions. I combine these approaches with neuroimaging data analyses of T1 MRI and CT data to analyze the anatomical spatiotemporal dynamics present in epileptic neuronal networks. My research interests are broadly in the intersection areas of neuroscience, machine learning and statistics, control theory and dynamical systems. I am also extremely passionate about open-source everything.

My interest in engineering and medicine started at UCSD, where I graduated in 2015 with a double major in Bioengineering and Mathematics. It was there under the guidance of many great faculty, such as Dr. Todd Coleman, that I became interested in applied mathematics, data analytics and machine learning in healthcare. It led me to pursue a PhD, with the ultimate goal of bringing together technology expertise with biomedical domain knowledge to solve challenging medical problems. I am an NSF-GRFP fellow, Whitaker International Fellow , Chateaubriand Fellow and ARCS Chapter Scholar .

Non-Research Work

Outside of my research work, I'm grateful to be involved with a non-profit called AAMPLIFY, which is an education and charitable non-profit that empowers underserved Asian Pacific American youth to become social justice leaders. Every year, we host a Social Justice Leadership Program for low-income high school students that aim to pursue careers in law, government, non-profit or social enterprise. Our program includes an intensive summer training and ongoing development with rotations in leadership, social justice and college/career planning. By helping these students recognize their leadership potential and ability to change the world, we give a voice to the needs of our community. I'm happy to be involved in developing the leadership curriculum even though I'm so far away. I'm hoping that giving time and effort can translate to reaching this mission in some way in the not-so-far future.

In addition, I'm involved in a Whitaker International Program Conclusion Grant. A few Whitaker alumni and I won a Whitaker concluding grant of $100k to build a digital ever-lasting storyboard of biomedical engineering lives. This will be centered around Whitaker scholar and fellow experiences throughout the years of the grant. This will involve creating a Instagram, Twitter, Facebook and website that tells stories of the impact of the Whitaker grant, and how biomedical engineers are all over the world changing lives. For more information, see our group, called EverydayBME.

Personal Background

I'm originally from Los Angeles, CA and consider myself a true CA native even though I wasn't born there. I have a range of hobbies, including, but not limited to: running, gymming (weight lifting), reading, hacking, traveling and photography.

Technical/Soft Skills

As an engineer, I consider myself an expert in Matlab and Python, being able to work with Numpy, Pandas, Scipy, Keras/Tensorflow, Pytorch and more. I am familiar with Bash, Javascript, HTML, CSS, C/C++, MongoDB and SQL. I have experience with Django, Pelican web frameworks. I like building stuff with Arduino, and Raspberry Pi; I've made a self-driving toy car using an ultrasound sensor and setup a hacked-version of Alexa using Raspberry Pi. As a data analyst, I have experience with PBS/SLURM scheduling systems and GNU parallel.

My domain experience includes neuroscience, linear systems, data wrangling, machine learning and algorithm development.

Everything on this site reflects my personal views only. It'll generally range from research/science thoughts, to photo blogs (in progress in the backend), to travel blogs (for my own benefit of keeping track of where I went :p).


Read my blog.

Here's a timeline, or tags of my blog posts.



  • ali39 at jhu dot edu


Check my social media links to get in touch!