I'm a Staff Research Scientist at Meta Reality Labs, where I lead ranking, targeting, and machine learning for Wearables Growth. In my current role, I've set the multi-year ranking and targeting strategy for our wearables products, driven technical alignment across product groups up to the VP level, and led 0-to-1 launches of new growth surfaces from concept to production.

I hold a Ph.D. in Computational Social Science from Stanford (NDSEG Fellow), an A.M. in Statistics from Harvard, and a B.S. in Mathematics from Ohio University. My research on network science, machine learning, and experimentation has appeared in Nature Human Behaviour, AAAI, ICWSM, and TheWebConf. Previously, I was a Member of Technical Staff at Sandia National Laboratories and a research fellow at Stanford Law School.

Throughout, I've cared a great deal about developing others. I've mentored senior engineers and a dozen-plus PhD interns now building research careers of their own.

1. A Two-Part Machine Learning Approach to Characterizing Network Interference in A/B Testing Yuan Yuan and Kristen M. Altenburger (2025). Manufacturing & Service Operations Management.
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2. Node Attribute Prediction on Multilayer Networks with Weighted and Directed Edges Yiguang Zhang, Kristen M. Altenburger, Poppy Zhang, Tsutomu Okano, and Shawndra Hill (2024). International AAAI Conference on Web and Social Media (ICWSM).
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3. Consequences of Conflicts in Online Conversations Kristen M. Altenburger, Robert Kraut, Shirley Hayati, Jane Yu, Kaiyan Peng, and Yi-Chia Wang (2024). International AAAI Conference on Web and Social Media (ICWSM).
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4. Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for the Internal Revenue Service Audit Selection Peter Henderson, Ben Chugg, Brandon Anderson, Kristen M. Altenburger, Alex Turk, John Guyton, Jacob Goldin, and Daniel E. Ho (2023). AAAI Conference on Artificial Intelligence.
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5. Understanding Conflicts in Online Conversations Sharon Levy, Yi-Chia Wang, Robert Kraut, Jane Yu, and Kristen M. Altenburger (2022). TheWebConf.
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6. What Does Perception Bias on Social Networks Tell Us about Friend Count Satisfaction? Shen Yan, Kristen M. Altenburger, Yi-Chia Wang, and Justin Cheng (2022). TheWebConf.
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7. Causal Network Motifs: Identifying Heterogeneous Spillover Effects in A/B Tests Yuan Yuan, Kristen M. Altenburger, and Farshad Kooti (2021). TheWebConf.
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8. Which Node Attribute Prediction Task Are We Solving? Within-Network, Across-Network, or Across-Layer Tasks Kristen M. Altenburger and Johan Ugander (2021). International AAAI Conference on Web and Social Media (ICWSM). Outstanding Problem-Solution Paper Award
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9. Is Yelp Actually Cleaning Up the Restaurant Industry? A Re-Analysis on the Relative Usefulness of Consumer Reviews Kristen M. Altenburger and Daniel E. Ho (2019). TheWebConf. Best Poster, Honorable Mention
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10. Decoupled Smoothing on Graphs Alex Chin, Yatong Chen, Kristen M. Altenburger, and Johan Ugander (2019). TheWebConf.
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11. When Algorithms Import Private Bias into Public Enforcement: The Promise and Limitations of Statistical De-Biasing Solutions Kristen M. Altenburger and Daniel E. Ho (2018). Journal of Institutional and Theoretical Economics.
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12. Monophily in social networks introduces similarity among friends-of-friends Kristen M. Altenburger and Johan Ugander (2018). Nature Human Behaviour, 2(4), 284.
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13. Are there Gender Differences in Professional Self-Promotion? An Empirical Case Study of LinkedIn Profiles among Recent MBA Graduates Kristen M. Altenburger, Rajlakshmi De, Kaylyn Frazier, Nikolai Avteniev, and Jim Hamilton (2017). International AAAI Conference on Web and Social Media (ICWSM). Winner, 2015 LinkedIn Economic Graph Challenge
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14. PuzzleCluster: A Novel Unsupervised Clustering Algorithm for Binning DNA Fragments in Metagenomics Kyler Siegel, Kristen Altenburger, Yu-Sing Hon, Jessey Lin, and Chenglong Yu (2015). Current Bioinformatics, 10(2), 231–252.
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• Dec 2024Social Media Lab, Stanford University — Invited seminar, Social Networks for Product Innovation.
• Apr 2024Business Analytics, University of Iowa — Invited seminar, Social Networks for Product Innovation. link
• Oct 2023Fairness, Privacy & Causality in Graphs Workshop, UC Santa Cruz — Invited speaker, Conversations and User-to-User Networks for Product Innovation. link
• Oct 2023INFORMS, Human-Centered ML Session (Phoenix, AZ) — Invited speaker, Conversations and User-to-User Networks for Product Innovation. link
• Oct 2022IEEE IEMCON — Invited keynote speaker. link

• Till Saenger · Summer 2025
• Amel Awadelkarim · Fall/Winter 2023
• Yiguang Zhang · Summer 2022
• Shirley Hayati · Summer 2022
• Usman Tariq · Summer 2022
• Shlok Mehrotra · Summer 2022
• Sharon Levy · Summer 2021
• Manoel Horta Ribeiro · Summer 2021
• Grace Li · Summer 2021
• Shen Yan · Summer 2021
• Poppy Zhang · Winter 2021
• Yuan Yuan · Summer 2020

• Facebook AI Blog — "Facebook AI's co-teaching program to increase pathways into AI for diverse candidates" · Oct 2020
• Food Safety Magazine — "Artificial Intelligence and Food Safety: Hype vs. Reality" · Dec 2019
• Food Safety News — "Can Silicon Valley save food safety? Maybe, but not with online reviews alone" · Jan 2019
• Scientific American — "Friends of Friends Can Reveal Hidden Information about a Person" · Jun 2018
• Rewire — "How Friends of Your Friends Give Away Your Private Info Online" · May 2018
• LinkedIn Engineering Blog — "Economic Graph Research Program: Insights and Updates" · Jul 2018
• LinkedIn Engineering Blog — "Measuring Gender Diversity with Data from LinkedIn" · Jun 2015