I’m a 4th year undergraduate student currently studying at UCLA and majoring in computer science. Planning on graduating in the summer of 2019. Looking for full-time opportunities with an emphasis on SWE and machine learning
I’m passionate about applying my knowledge of computer science and machine learning to areas in healthcare where we can really engineer better solutions for helping doctors and taking care of patients. In my mind, machine learning and computer science really have the power to make the gradual shift to preventative instead of reactionary healthcare. If you’re working in the healthcare or medical fields, don’t hesitate to reach out if you think there’s an opportunity for collaboration. Would love to discuss.
- Applied Machine Learning Intern at Clarifai (June 2018 - August 2018)
- Created internal tools to check the accuracy of image labeling from human workforce services.
- Built evaluation scripts to easily assess and visualize the performance of Clarifai’s base image recognition models.
- Created demo webpages to showcase Clarifai’s detection models during internal meetings.
- Software Engineering Intern at Qualcomm (June 2017 - August 2017)
- Worked on the core Android platform team to test over-the-air (OTA) upgrades on Qualcomm powered Android devices.
- Performed fail-safe testing to ensure proper functionality during OTA updates and bootup.
- Consolidated OTA projects into a unified location to achieve smooth upgrades with limited disruption to other modules.
- Tools Used: Android Fastboot/ADB, OpenEmbedded, Bitbake
- Computer Engineer Intern at U.S Naval Research Lab (June 2016 - September 2016)
- Developed object localization algorithms through convolutional neural networks for deployment on IBM’s TrueNorth neuromorphic chip.
- Wrote Matlab functions and shell scripts to format and preprocess datasets.
- Implemented a selective search and sliding window based approach to localization.
- Trained a convolutional neural network to place bounding boxes over a specific object of interest with a classification accuracy of 92.86%.
- Presented results to a group of engineers and upper level management at the conclusion of the internship.
- Research Intern in Boston RISE program (June 2014 - August 2014)
- Participated in the Boston RISE summer internship program during the summer between my junior and senior years of high school.
- Completed an Electrical Engineering project under the guidance of Professor Ajay Joshi.
- Ran benchmarks on a Parallella board containing a 16 core Epiphany processor, analyzed results, and participated in a research poster session at the end of the program.
- Author at O’Reilly Media
- President(2018-2019), Vice President(2017-2018) of UCLA ACM Artificial Intelligence
- Coach with UCLA Special Olympics
- Peer Mentor with UCLA Engineering Mentorship Program
- UCLA Lead Resident Assistant(2018-2019), UCLA Resident Assistant(2017-2018)
- KDnuggets author page
- Interview with KDnuggets
- DZone author page
- O’Reilly Generative Adversarial Network Tutorial
- O’Reilly LSTM Video Tutorial
As president of UCLA’s ACM AI group, I’ve presented/co-presented on the following topics (with slides attached).
- ACM AI Intro Meeting
- Workshop #1: Linear Regression with Tensorflow
- Workshop #2: Logistic Regression with Tensorflow
- Workshop #3: Pandas and Kaggle
- Workshop #4: Neural Networks with Tensorflow
- Workshop #5: Multi Layer Neural Networks with Tensorflow
- Workshop #6: Convolutional Neural Networks with Tensorflow
- Workshop #7: Recurrent Neural Networks with Tensorflow
As part of ACM AI, we hold research paper reading group meetings.
Books I’d Highly Recommend
- When Breath Becomes Air - Paul Kalanithi
- Option B - Sheryl Sandberg
- Quiet: The Power of Introverts in a World That Can’t Stop Talking - Susan Cain
- Emotional Agility - Susan David
- Chasing the Scream - Johann Hari
- The Elegant Universe - Brian Greene
- 10% Happier - Dan Harris