We’re a mighty team of five
We're on a mission to make LSAT prep more affordable and efficient with AI-machine learning. That's why we emphasize our data science capabilities instead of our co-founders' LSAT scores.
Justin Huang
Justin Huang
​CTO & Co-founder
M.S. from Stanford University
Before AdeptLR, Justin worked at some of the big tech companies and startups in Silicon Valley.
Marie Ng
Marie Ng
Chief data scientist & Co-founder
Ph.D. & M.S. from USC
Before AdeptLR, Marie worked as data scientist at IBM and was an Assistant Professor at the University of Washington.
Christopher Yang
Christopher Yang
VP of Engineering
B.S. from UCLA
Before AdeptLR, Chris worked at some of the big tech companies and startups in Silicon Valley.
Tim Ng
Tim Ng
Co-founder
J.D. from Berkeley Law
Tim practices international tax law. If you have any questions about the tax practice (the best kept secret in law school) or biglaw in general, please feel free to drop Tim a note in contact us.
Peter Jung
Peter Jung
Co-founder
J.D. from Berkeley Law
Peter is a technology transactions attorney and, prior to attending law school, taught middle school and high school math. Peter is passionate about effective and affordable education.
Our story
We built AdeptLR with one goal in mind: To make LSAT prep affordable & efficient.

During law school, Peter and Tim decided to take an MBA class called ‘Entrepreneurship’. Even though the idea we came up with in class failed (the idea was to revolutionize garage parking by allowing customers to reserve garage parking in advance - RIP "E-park"), we were possessed by the entrepreneurial spirit.

So while we were studying for the bar, we began to recall our LSAT-studying days and thought of how our experience could be better. Knowing what we know now about data science and digital UX, we knew we could create a platform that provides students with an efficient way to leverage their own data in LSAT prep while making the experience of studying for the LSAT more pleasant.

We decided to focus on drilling because there are already ample sources that will teach the contents of the LSAT, and the cost ranges from $20 (books) to over $2,000 (prep courses and tutoring). But when it comes to drilling, most people (including us) answered LSAT questions on paper and had to manually track and organize our correct and incorrect answers in separate categories (e.g., must be true). Second, there was no cost-efficient way of drilling (prep courses may provide drilling features but requires purchasing the entire course). Lastly, there was no way of practicing the questions according to difficulty in relation to our individual testing profile. For example, an easy question to a 90th percentile test taker is likely a hard question to a 50th percentile test taker.

Thus, we created AdeptLR to fill those gaps (and yes we passed the bar!).

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