Senior Data Scientist
- Senior researcher on Duo’s Algorithms Research team, leading research initiatives for model improvement.
- Leading geospatial anomaly detection research, from initial literature review through current deployment and development.
- Coordinating and collaborating with product and leadership on customer discussions to guide future product directions.
Data Scientist (2019-2021)
- Researcher and developer on Duo Trust Monitor, an anomaly detection platform.
- Continuously iterated on threat detection models to improve detection precision, including geospatial modeling research and automated model drift detection.
- Developed features within Scala pipeline, PySpark.
- Co-presented at DEFCON 29 AI Villiage
Software Engineer (2018-2019)
- Developer on Duo’s Network Gateway, a reverse proxy server enabling zero trust secure remote access.
- Developed features in Python, as well as a client in Go.
- Mentored interns, led technical interview training, led workshops on Go and Python Twisted development.
University of Michigan
Teaching Assistant, Computer Security (2017-2018)
- Led discussions on web security, application security, cryptography
- Redesigned entire discussion and lab curriculum to include more interactive experiences and increase student engagement
Research Assistant, Radiation Health Lab (2015-2017)
- Developed system for continuous data collection from radiation weather station
- Presented system design at 2016 Health Physics conference
Graduate - M.C.S., Data Science Track - University of Illinois at Urbana Champaign
- Relevant coursework: Applied Machine Learning, Advanced Bayesian Modeling, Practical Statistical Learning, Data Cleaning, Data Visualization, Distributed Systems
Undergraduate - B.S., Computer Science - University of Michigan
- Relevant coursework: Operating Systems, Web Systems, Computer Security
Talks and Publications
- Keep Your Enemies Closer: Understanding Reverse-Proxy 2FA Hijacking via Large-Scale Internal Red Teaming , Cisco Data Science Summit
- Enhancing 2FA with IP-based Geolocation Without Blocking All Your Users, CAMLIS (Conference on Applied Machine Learning for Information Security)
- Near, Far, Wherever You Are: Geospatial Modeling for Anomaly Detection, Cisco Data Science Summit
- Where We’re Going, We Don’t Need Labels: Anomaly Detection for 2FA, link , DEFCON 29 AI Village
- An Actionable Approach to Diversity and Retention link , Black Hat USA
- A Radiation Weather Station: Development of a Continuous Monitoring System for the Collection, Analysis, and Display of Environmental Radiation Data, link , Health Physics Journal