Algorithmic Developer2016 - 2018Hudson River Trading
Technologies: PyTorch, TensorFlow, CUDA, Python, C++
- Developed novel high-frequency trading strategies that currently traded more than 5% of US equities; they were primarily liquidity taking and deep learning-based and I was responsible for all stages, from alpha modeling to production implementation.
- Improved firm-wide profit and loss (P&L) by $XX million/year, in simulation and live trading.
- Created the HRT AI Labs Fellowship along with the founding partners.
Ph.D. Candidate (Machine Learning and Computer Vision)2012 - 2016University of California, Berkeley
Technologies: Amazon Web Services (AWS), AWS, Ceres, Google, PCL, PyTorch, TensorFlow, CUDA, Python, C++
- Developed a 3D scanner from scratch using commodity hardware: low-end DSLR cameras, Carmine PrimeSense depth sensors, a turntable, and an arm to hold the devices.
- Wrote bundle adjustment-based camera calibration software using Google Ceres (used in Google StreetView's calibration) and published the BigBIRD dataset at ICRA 2014. This dataset has been cited 200+ times.
- Developed novel 3D reconstruction algorithms to produce 3D meshes of objects scanned in the BigBIRD dataset (ICRA 2015). Experiments reveal that scanning accuracy exceeds scanners that cost $100,000+; our scanner costed $3,000+.
- Developed a novel Levenberg-Marquardt-based 3D mesh coloring algorithm to produce photorealistic 3D scans of the BigBIRD dataset (IROS 2015). User studies indicate that users could rarely distinguish between real images and our model renderings.
- Developed 3D scanned models that were used by Amazon as part of the Amazon Picking Challenge (2014).
- Developed the first end-to-end CUDA implementation of t-SNE (a highly popular visualization algorithm in deep learning). Sped up t-SNE runtimes by 60x (ICML 2015:). Generalized t-SNE to allow users to focus on micro and macro data statistics.
Quantitative Researcher Intern2015 - 2015Citadel LLC
Technologies: TensorFlow, Caffe, Python, C++
- Developed the first deep learning-based alpha models at Citadel Global Quantitative Strategies which currently generate $XX million/year in live P&L. Was responsible for all stages of development, from research to production implementation.
- Implemented heavily optimized C++ libraries and deployed the alpha model directly into the production trading environment.
- Implemented an end-to-end research pipeline, allowing a researcher to easily reproduce the alpha models that I had produced during the internship.
Research Intern2012 - 2012Cornell University
Technologies: BMAD, Unix, C++
- Developed novel algorithms to efficiently track photon beam propagation through particle accelerators, particularly the Cornell Electron Storage Ring (CESR) and the Energy Recovery Linac (ERL).
- Implemented the algorithms in C++ and integrated the system with BMAD, a particle accelerator library developed at Cornell University.
- Created algorithms that Cornell researchers at CESR and ERL now use to compute mirror placements along the particle accelerator to control photon beam propagation prior to physical implementation.
Software Engineer (Google Ads Quality)2011 - 2012Google, Inc.
Technologies: Python, C++
- Deployed click-through-rate prediction models that generated $XX million/year from Mobile Search Ads traffic.
- Developed and deployed a novel, large-scale feature selection algorithm responsible for improving click-through-rate prediction performance for Google Mobile Search Ads.
- Conducted Python code reviews for the full team for Python readability.
Software Engineering Intern (Google Help)2011 - 2011Google, Inc.
Technologies: Java, Objective-C
- Developed a framework for all Google iOS products to handle user-submitted feedback and report iOS app crashes.
- Created the front-end interface and application using Objective-C and the back end using Java.
- Internationalized all front-end components in 30+ languages.
- Began evangelizing the framework towards the end of the internship; now, most Google iOS applications (e.g., search, shopping) employ this framework, allowing millions of users around the world to report feedback for Google iOS products.
Undergraduate Researcher2008 - 2011Georgia Institute of Technology
Technologies: Python, Java, C++
- Developed a multi-agent extension to value iteration, a model-based reinforcement learning algorithm. Published results at AAAI 2011 with Prof. Charles Isbell and Dr. Liam MacDermed.
- Built a laser-cooled ion trap capable of trapping Ba-138 ions. Produced false-color image of *individual barium ions*. Responsible for mirror and laser calibration and constructing the physical trap. Supervised by Prof. Michael Chapman.
- Developed a natural language generation framework allowing users to quickly author large amounts of varied text, useful for chatbot applications. Published at AIIDE 2011 with Prof. Charles Isbell and Prof. David Roberts. Press release on Engadget.
Software Engineering Intern (Google Search Quality)2010 - 2010Google, Inc.
Technologies: Unix, C++
- Implemented inline satellite/terrain map display in Google Search. For example, try searching for [terrain map of mount everest] on Google.com.
- Internationalized the satellite/terrain map display functionality across 30+ languages, working with product management and translation teams. For example, try searching for [satelitska karta mount everest-a] on Google.hr; this is Google Croatia.
- Ran several AB tests to demonstrate that (1) users had positive experiences with this feature and (2) Google ad revenue was not impacted adversely. Verified that the increase in Google search metadata logging was minimal.