LinkedIn

■ 𝗔𝗜 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Led a 1.5-year, cross-org initiative, driving AI strategy across >150 projects and 77+ ICs. Delivered an estimated >130 engineering-quarters of productivity savings per year across Trust, with platform improvements extending even further across all AI teams at LinkedIn, increasing overall impact. Evangelized the strategy, secured leadership buy-in, and scaled by growing new leaders to deliver step-function improvements in online/streaming AI infrastructure.
■ 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗰𝗼𝗻𝘁𝗲𝗻𝘁: Led the vision and development of LinkedIn's Generative AI (GAI) image detection system from inception to production, addressing new abuse challenges (fake accounts with GAI profile photos). Recruited and collaborated with renowned Berkeley Prof. Hany Farid, delivering cutting-edge research and publications. Recognized as a thought leader in the field, e.g., invited to speak on a DARPA panel at SXSW24.
■ 𝗠𝗲𝗺𝗯𝗲𝗿 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲𝘀: Pioneered LinkedIn Trust’s sequence-based detection technology, building it from 0 to 1 and addressing one of Trust’s hardest challenges—scaling detection across multiple surfaces without feature engineering. Defined the multi-year strategy and led the execution, resulting in significant DBI wins across three verticals. This technology was used to deliver impactful models in account takeover (ATO), fake accounts, and scraping. Granted two USPTO patents in 2024 for innovative sequence modeling techniques.
■ 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽 𝗮𝗻𝗱 𝘁𝗮𝗹𝗲𝗻𝘁 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Mentors and develops leaders across multiple orgs, contributing to the promotion of many mentees to Staff+ roles. Leads technical forums on strategy and innovation. Actively supports recruiting efforts, including giving talks at key events and interviewing high-priority, senior candidates. Interviewed 200+ candidates for AI/ML engineer and manager roles.

Senior Staff Software Engineer, Machine Learning

■ 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽: Led a team of 40+ engineers and managers as the Anti-Abuse AI technical lead for over two years, developing AI strategies that effectively combat platform abuse.
■ 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗰𝗼𝗻𝘁𝗲𝗻𝘁: Created LinkedIn's first deepfake video detection system using deep learning, enhancing platform integrity and user trust.
■ 𝗠𝗲𝗺𝗯𝗲𝗿 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲𝘀:  Pioneered the use of deep learning and NLP techniques to detect abusive sequences of user activity, addressing critical scaling challenges across multiple attack surfaces.
■ 𝗔𝗜 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Led a comprehensive two-year, 20-engineer cross-functional effort totaling 113 developer-quarters, resulting in the successful migration of dozens of models to a new ML tech stack, significantly reducing technical debt and improving team morale.
■ 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽: Mentored 4+ engineers across multiple organizations who were successfully promoted into senior and staff roles, contributing to LinkedIn's talent development.
■ 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Enhanced LinkedIn's reputation through talks at conferences like KDD, Spark+AI Summit, and Scale AI, and through open-source contributions to Microsoft's SynapseML library.

Staff Software Engineer, Machine Learning

■ 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽: Tech lead of the Anti-Scraping and Automation AI team, focused on detecting and preventing automated bot behavior to safeguard LinkedIn’s platform integrity.
■ 𝗠𝗟 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 (𝗶𝘀𝗼𝗹𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿𝗲𝘀𝘁): Developed LinkedIn’s first general-purpose outlier detection library by implementing isolation forest in Spark/Scala. Open-sourced the library, now utilized in over six production use cases within LinkedIn.
■ 𝗖𝗿𝗼𝘀𝘀-𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Partnered with multiple LinkedIn organizations and external partners to implement comprehensive automation defenses across various site surfaces, ensuring robust protection against automated abuse.
■ 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽 𝗮𝗻𝗱 𝘁𝗮𝗹𝗲𝗻𝘁 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Mentored new engineers and contributed to talent acquisition efforts, fostering a culture of growth and technical excellence within the team.
■ 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗮𝗻𝗱 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘀𝗵𝗮𝗿𝗶𝗻𝗴: Delivered presentations on isolation forests and anti-scraping strategies at internal meetings and external conferences, promoting best practices and continuous learning within the organization.

Senior Software Engineer, Machine Learning

■ 𝗙𝗮𝗸𝗲 𝗮𝗰𝗰𝗼𝘂𝗻𝘁 𝗺𝗼𝗱𝗲𝗹𝘀: I built abusive entity reputation and fake account detection machine learning models while working in the Anti-Abuse AI Team.

Software Engineer - Data Mining/Data Analysis/Machine Learning

Insight Data Science

■ 𝗔𝗜/𝗠𝗟 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴: Created an account takeover (ATO) detection system while consulting for Castle (YC W16).
■ 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴: Developed a statistical model for unsupervised anomalous event detection resulting in a >2× improvement in the recall of compromised accounts over the existing model with the same false positive rate.

Data Science Fellow

Brown University

■ 𝗪𝗼𝗿𝗹𝗱-𝗹𝗲𝗮𝗱𝗶𝗻𝗴 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵: Led the experimental design, operations, and data analysis effort for a novel, world-leading calibration of the world's most sensitive dark matter detector.
■ 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽: Managed the data processing working group while scaling up the data pipeline for production use. Managed a team of scientists and engineers as a calibration working group leader. Directed multiple teams during 307 days of on-site presence during the integration and operation of the LUX experiment 4,850 ft underground at Sanford Laboratory in Lead, SD.
■ 𝗠𝗟 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Led development of the Python-based data processing framework supporting Python, Matlab, and C++/ROOT algorithm modules.
■ 𝗗𝗮𝘁𝗮 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: Architected and administered the primary data repository and distribution system serving 500 TB to 100+ worldwide collaborators.
■ 𝗛𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗰𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴: Created, deployed, and operated a Python-based data processing framework on an 8,000 core high-performance computing cluster processing up to 1 TB/day of incoming data.
■ 𝗧𝗶𝗺𝗲-𝘀𝗲𝗿𝗶𝗲𝘀 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Implemented algorithms to characterize features (10 ns to 300 μs) in time series data.
■ 𝗖𝗹𝗼𝘂𝗱 𝗰𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴: Pioneered the use of SciDB using AWS for interactive analysis on TB-scale datasets.

Particle Astrophysics Group

Experienced Senior Staff Software Engineer specializing in the large-scale application of AI and machine learning at LinkedIn. Drives innovative AI strategies that enhance platform trust and security, and boost developer productivity. Expert in developing cutting-edge AI/ML approaches to tackle ambiguous and complex business problems. Proven leader and mentor, fostering the growth of high-performing teams and cultivating new technical leaders to achieve strategic objectives.

Recognized thought leader with multiple patents and significant open-source contributions. Authored publications and presented at conferences while collaborating with academic experts to advance the field at the intersection of trust and AI.

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