Founder2018 - PRESENTScalar Research
Technologies: TensorFlow, PyTorch, Python
- Founded a consulting firm to help companies tackle complex business challenges with cutting-edge AI and data science.
- Served in leadership and advisory roles for tech startups, investment firms, and large corporations across multiple industry verticals.
- Helped Scale AI ($1+ billion tech firm) optimize quality assurance in its distributed data annotation workforce with predictive analytics.
- Built computer vision systems to track cars and optimize servicing efficiency for client’s pilot with Fortune 500 auto company.
- Improved Fandom’s page tagging model (ad targeting, content recommendation) with cutting-edge NLP (from 0.35 to 0.557 R at P95).
- Created a text-mining (NLP) tool to help HelixNano (biotech firm) predict cancer therapeutics from a massive research dataset.
- Led the development of semantic search and recommendation engine products for a startup that resulted in contracts with Fortune 500.
- Helped a leading global professional services firm and a large Asian industrial conglomerate launch a computer vision joint venture.
- Developed tooling for a data science team creating supply-chain analytics software for a major CPG conglomerate in LATAM.
- Worked on other projects including license plate recognition (OCR) from edge devices, sports tracking and scoring from real-time video, unstructured data extraction from millions of PDF documents, and financial time series forecasting for securities trading.
- Presented 20+ technical talks and workshops at major international conferences (e.g., AWS re:Invent, the annual event by Amazon).
- Taught artificial intelligence to non-technical audiences at leading institutions (e.g., a workshop for artists and public at Tate Modern).
Reviewer2020 - 2020International Conference on Machine Learning (ICML)
Technologies: Machine Learning
- Selected as a peer reviewer for paper submissions for ICML 2020 (International Conference on Machine Learning), one of the leading academic conferences on machine learning.
- Reviewed papers related to natural language processing (NLP), model compression, and deep learning for tabular data analysis.
Research Assistant2017 - 2017Stanford Computer Vision Lab
Technologies: Python, TensorFlow, PyTorch
- Researched for AI-enabled smart hospitals that leverage computer vision methods to reduce the monitoring workload of clinicians.
- Developed deep learning models (based on RNNs and CNNs), end-to-end data pipeline, and annotation tools.
- Published a first-author paper that was selected for a spotlight presentation (top ten papers) at NIPS ML4H 2017.
- Published a paper in Nature Partner Journals (Nature) Digital Medicine.
Research Intern2016 - 2017QxBranch
Technologies: Python, PyTorch, TensorFlow
- Researched quantum deep learning methods using the D-Wave 2X quantum computer.
- Developed a novel architecture and quantum-assisted learning algorithm for convolutional deep belief networks.
- Accepted for a poster presentation at the Adiabatic Quantum Computing Conference 2017 (Tokyo, Japan).
Software Engineer Intern2015 - 2015
- Implemented monitoring features for Google Cloud.
- Presented to enterprise customers and was featured on the Google Cloud Platform Blog.
- Conducted market research, prepared mockups, and created proof of concept for upcoming Google Cloud Monitoring features.
Software Engineer Intern2014 - 2014
- Developed collaboration and data integrity features to streamline the workflow of large customers using Facebook Ads Manager.
- Created a plugin for an internal tool to increase developer productivity.