Hello! I'm a machine learning researcher in NYC currently working as a software engineer at Google AI. Before graduating in 2018, I was a Ph.D. student at the Cornell Tech SE(3) Vision Group under Dr. Serge Belongie. I previously worked as a research assistant in the Vision and Security Technology lab and as a software engineer at Securics, Inc., both under Terrance E. Boult.
My hobbies include peer counseling, bouldering (still a beginner, VB-V1), lifting (beginner), hiking, and finding delicious quiet places in the city to drink tea and read books.
My full publication list is available on my CV or my **Google Scholar Profile Page.**
<aside> ✏️ Note that some work before 2018 is listed under a previous name.
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We created a system that can understand the aesthetic quality of user-created photos on online marketplaces like Letgo or eBay. This was a collaboration between Cornell Tech, eBay, and the Oath connected experiences lab.
We taught a computer about artwork! Our efforts led to the creation of "BAM," currently the largest semisupervised dataset of digital artwork on the Internet freely available for researchers.
What happens when you perform brain surgery on a ResNet? Surprisingly, performance still stays the same when deleting several layers, even without fine-tuning. We investigate why in this paper.
On flagship datasets like LFW and Caltech-256, the current top performing algorithms at time of writing do not satisfy the triangle inequality, symettricity, or even identity. Why are top-performing algorithms non-metric?
We built "SNaCK", a system that combines expert constraints with deep-learning similarity kernels to understand intuitive ideas like the taste of food or the visual similarity of different classes of animals.
This project studied how best to ask human experts about food taste similarity. We showed that we could pay our Amazon Mechanical Turk workers more by collecting their input using more efficient UIs for higher-quality results.
Our team built a system to help scientists track the population of endangered ground squirrels and desert tortoises living near the Edwards Air Force Base in the Mojave Desert. This is a challenging detection and recognition task - the animals of interest are only a few pixels tall and are easily confused with non-endangered species.
Most biometrics systems compromise users' privacy by storing their data in large biometrics databases that can be searched by law enforcement and rogue actors. Our Vaulted Verification work allows users to authenticate their accounts, but requires their cooperation to verify their identity, so it cannot be used in large-scale search databases.
Throughout my academic career, I am grateful to be supported by Dr. Serge Belongie, the NSF Graduate Research Fellowship, Oath, Google, Adobe, the faculty and staff at Cornell Tech, and and my friends, family, partners, and community. I am an Oath PhD fellow. I also participated at the NSF REU program at UCCS in Summer 2011.
You can find my contact details on my CV or my LinkedIn page.
