Exploring and expanding into the worlds and futures beyond our small pale blue dot.
- Sustained industrialization and colonization of our solar system, likely starting with returning to the Moon and staying there.
- Not blinking out of existence until we have at least found other intelligent life out there and become part of something bigger.
Pursuing real-world applications of artificial intelligence and robotics.
- Widespread use of AI, robotics, and automation, especially applied to expanding into space in a significant way, and radically freeing up human time and efforts here on Earth.
- Achieving artificial general intelligence as a technological civilization, and hopefully witnessing first-hand how this changes human life indefinitely.
Defeating mortality, whether through extending our biological lifespans or engineering a way for living on through advanced
- Give myself, my loved ones, any future children, and all mankind in general the ability to experience even more of what life has to offer, without fear of aging and death.
- Live long enough to see humanity building a utopia on Earth and thriving across the inner solar system, or at least enable future generations to live these dreams for me.
Bringing humanity together as one family by seeing the bigger picture of our existence and how meaningless our conflicts
are in light of this.
- Breaking down imagined barriers to instead work together towards a brighter future.
- Machine vision engineer @
- Founder @
- Senior software engineer @
- Engineer @
Human Dx (2016-2018)
- Software engineering intern (web applications) at
Rocket Fuel (2014)
- Research assistant at
Stanford Vision Lab under Dr. Fei-Fei Li (2012-2013)
- Member of UCLA Stroke Force organization (2011-2012)
REU sponsored summer intern at the University of Michigan, Ann Arbor under
Dr. Allison Steiner (2010)
- Stanford University: M.S., Computer Science (2016)
- Specializations: Artificial Intelligence, Real-World Computing
- UCLA: B.S., Neuroscience (2012)
Social, worldwide, daily vlogging platform focused on simplicity and
authenticity. Provides a quick and easy way for people around the world to
vlog their daily lives, with the mission of bringing the world closer
together as one family.
Built using Golang, Scala, PostgreSQL, Redis, React Native,
- 2D simulation of robot constructing human-livable habitats on Mars. Modeled as Markov Decision Process (MDP), with
multiple task phases implicitly formulated into transition/reward functions, allowing naturally solving the sequential
phases without manual phase conditions or explicit instructions.
- Manually modeled state and action spaces, transition and reward functions, and various “worlds”/difficulties. Applied
varying degrees of model uncertainty (movement, object interaction, etc.). Used discrete value iteration to solve
- Successful in simplistic settings, always achieving optimal policies and performances in minimal time.
- Implemented using Julia, POMDPs.jl, and PyPlot.jl. Individual project. Dec 2015.
- Social network recommendation system for encouraging shared-interest, distance-based connections. Used Twitter network/dataset/API
and Google Maps Geocoding API; acquired network structure and geographical locations for ~57,000 users, with 1 million
connections between them. Generated simulated user interests vectors.
- New user connection ranking and recommendation using network structure features, user geolocations and distances, and
simulated interests. Successfully recommended both users with similar interests and geolocations (“distance-penalizing”
mode) and with similar interests and distant geolocations (“distance-rewarding” mode).
- Implemented using Python, Snap.py, and Gephi. Individual project. Dec 2015.
- 2D real-time puzzle game for Android OS using only Open GL ES 2.0.
- Available on Google Play Store, built entirely from scratch with no external game libraries in under 10 days
- Low-level handling of all shape drawing, shape texturing, game logic, player interaction, cross-thread communication,
Android UI, etc.
- Implemented using Android/Java and Open GL ES. Individual project. Aug 2015.
- Mobile computer-vision/augmented-reality Android application. Performed real-time hand and finger tracking on a mobile
device camera using only on-device computation. Interface enabled interaction with several on-screen functions via
real-world hand and finger placement.
- Used HSV-flesh probabilities with per-user/per-session calibration, CAMSHIFT and convex hull estimation for hand/finger
localization, and Android for the augmented reality on-screen interface.
- Implemented using Android NDK, C++, OpenCV, and Java/Android. Individual project. May - Jun 2015.
Galaxy Morphology Classifier
- Machine learning and computer vision system for galaxy morphology characterization.
- Used ~140K images from the Sloan Digital Sky Survey to provide outputs along ~40 continuous-valued morphology categories.
Preprocessing involved cropping, Gaussian filter smoothing, downsampling, and rotated image copies for rotational
- Used (Dense) SIFT, radii-based spatial descriptors, HSV, and bag-of-visual-words for features. Used K-nearest neighbors
regression, ridge regression, support vector regression, and convolutional neural networks for learning. RMSE for
- Implemented using Python, OpenCV, scikit-learn, and Caffe. Individual project. Feb - Mar 2015.
- Machine learning system to detect exoplanets using NASA Kepler Space Telescope data and planetary transit detection
method applied to Kepler brightness time series data.
- Noise reduction via sliding-window percentage-change transformation. Engineered manual features extracted from time
series data, considering properties such as global statistics, peak width/magnitude/frequency, inter-peak width, etc.
Applied k-means clustering and PCA methods for dimensionality reduction.
- Used k-nearest neighbors, logistic regression, softmax regression, SVMs, and k-fold cross validation for classification.
Achieved ~85% test classification performance.
- Implemented using Python, NumPy, matplotlib, and LIBSVM. Individual project. Sep - Dec 2014.
LORE: Light Object-Relational Environment (LORE). Provides a simple and lightweight pseudo-ORM/pseudo-struct-mapping
environment for relational database interaction using Golang.
Geocoder: Simple REST API server for geocoding addresses, implemented in Python.