Jared Lee Katzman Email & Phone Number

New York, NY, US

Ann Arbor, MI, US

PhD Student in InformationTopic areas: algorithmic accountability & transparency; political theories of technical design; algorithmic agonisms and political mobilization

Washington, District Of Columbia, US

• Researched multiple projects, including statistical methods for polling and election forecasting, interactive data journalism to improve comprehension of politically-relevant data, and survey design for measuring.
• Investigate a taxonomy for fairness and inclusiveness in image tagging and captioning AI services. Member of Fairness, Accountability, Transparency, and Ethics (FATE) reading group.
• Teaching Assistant for Microsoft Research Data Science Summer School, Summer 2021, an intensive, four-week hands-on introduction to data science for college students in the New York City area.

Seattle, WA, US

• Founding engineer on team developing Machine Learning Bias and Explainability products and research across ML platform.
• Researched technological and scientific vision and strategy for 5 new product proposals reviewed by senior AI leadership.
• Specialized in building new AI-powered services for various business use-cases. Rotated between scientific research, product development, and engineering implementation:
• Automated data explainability reports in Python Notebooks for Auto ML service within 1 month of joining the team.
• Designed new ML micro-services on AWS with data pipelines for deep learning models for information retrieval.
• Researched Entity Linking models on top of BERT which improved precision by 10% compared to baseline methods.

Seattle, WA, US

• Developed Entity Linking models on top of BERT which improved precision by 10% compared to baseline methods.
• Researched, developed, and released IP Insights, a deep learning algorithm that learns the history of users' IP addresses to identify anomalous behavior such as fraudulent logins and account takeovers.
• Discovered and removed bottlenecks in algorithm's performance by tuning MXNet's distributed training, leading to a 50% reduction in training time for 75% of the comparable cost of scaling.
• Presented a talk on scalable, distributed machine learning on MXNet at Amazon's internal developer conference to 110 attendees. Designed and facilitated workshops on machine learning and security.

Westport, Connecticut, US

• Built a real-time analytics platform with AWS services to transform security controls and operations from a perimeter, defensive model to a data-centric, automated-reasoning framework.
• Redesigned a batch processing architecture (Spark, Scala) as a real-time, serverless, streaming framework (AWS Kinesis, Lambda, ElastiCache, DynamoDB, Lambda, Java) which decreased a security control’s effect time from.

• Studied the politicization of churches and the influence of church leaders as part of the political elite.
• Wrote a web scraper in Python to help construct a novel dataset to study political affiliation of religious leaders.

Seattle, WA, US

• Programmed a multi-tier sandbox environment that enabled end-users to simulate transactions for new payment methods.
• Developed a full-stack solution including: Java server backend, data model and storage with Dynamo DB, and a dynamically generated UI with JavaScript.

Sunnyvale, CA, US

• Wrote program requirements and design specifications.
• Reinvented the team’s log analyzer tool and automated daily log reports with content rich emails.
• Implemented 'known-error' database with autonomously bug-status updates.

• Organized and ran a conference on the future of global energy.
• Brought together a diverse set of scientists and environmental leaders to discuss topics ranging from disruptive energy technologies to the changing energy sectors.

Doctor Of Philosophy - Phd, Information

Bachelor Of Science (Bs), Computer Science

Academy Of Information Technology