PeopleofSuperintelligence

Researcher

Dany Rouhana

With a computer science and mathematics background, Dany Rouhana is a Microsoft Research data scientist whose work connects machine learning, language-model training, and LLM-guided algorithm design. He coauthored Placer and Placer++, machine-learning systems for place labels, and ported a C# prototype of Flash Fill to C++. His 2024 and 2025 papers explored synthetic data for language-model training and LLM-guided design of robust heuristics. As of October 2026, he is a Principal ML Data Scientist at Microsoft Research.

Works
5
Citations
127
h-index
3

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2013

    Semantic place labeling

    In 2013, he coauthors Placer, a machine-learning algorithm that classifies visited locations as home, work, or school; his education is in computer science and mathematics.

  2. 2015

    Place labels beyond visits

    In 2015, he coauthors Placer++, which adds labeled visits from other people and visit sequences to the place-labeling model; these changes raise accuracy by 8.85 percentage points over Placer.

  3. By 2021

    Porting Flash Fill to C++

    By 2021, he has ported the C# Flash Fill prototype to C++ as a Microsoft Research engineer. Shipping the Excel feature takes a two-year collaboration.

  4. February 2023

    Responsible AI mitigation tools

    In February 2023, he contributes to Microsoft Research's open-source Responsible AI Mitigations library and Tracker, tools that help data scientists apply and compare model mitigations.

  5. July 2024

    Teaching models with AgentInstruct

    In July 2024, he coauthors AgentInstruct, an agentic framework for generating synthetic data to teach language models. The authors post-train Mistral-7b on a 25-million-pair dataset and produce Orca-3, which improves on Mistral-7b-Instruct across several benchmarks.

  6. October 2025

    Designing robust heuristics

    In October 2025, he coauthors Robust Heuristic Algorithm Design with LLMs, which uses failure examples and explanations to guide LLM-designed heuristics. The authors report about 28 times better worst-case performance than FunSearch while maintaining runtime.

  7. As of October 2026

    Principal ML data scientist

    As of October 2026, he is a Principal ML Data Scientist at Microsoft Research.

Most-cited works

  1. Placer2013 · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · 101 citations
  2. Placer++: Semantic place labels beyond the visit2015 · IEEE International Conference on Pervasive Computing and Communications · 22 citations
  3. AgentInstruct: Toward Generative Teaching with Agentic Flows2024 · 4 citationsWith Ahmed Awadallah, Andres Codas, Corby Rosset and Wei-ge Chen
  4. Robust Heuristic Algorithm Design with LLMs2025 · 0 citations

From OpenAlex, as of 19 October 2026.

  1. The company share of AI researchers’ top papers rose from 2% to 32%Includes Microsoft. We estimate where leading AI researchers worked when their most-cited papers appeared. The company share rose from 2% in 1975–1979 to 32% in 2020–2024.
  2. Google has the highest combined h-index among AI organizationsIncludes Microsoft. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  3. Google alumni founded or led 87 other organizations, the most among the labs we compareIncludes Microsoft. We trace 212 organizations founded or led by AI lab alumni, and 223 career moves between the labs.
  4. Google had the most people shaping AI every year from 2014 to 2025Includes Microsoft. Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.

Sources and credits

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  1. Placer: Semantic Place Labels from Diary Data microsoft.com. Checked 19 October 2026.
  2. Dany Rouhana - Microsoft Research microsoft.com. Checked 19 October 2026.
  3. Placer++: Semantic Place Labels Beyond the Visit microsoft.com. Checked 19 October 2026.
  4. The Story of the Flash Fill Feature in Excel blog.sigplan.org. Checked 19 October 2026.
  5. Responsible AI Mitigations and Tracker: New open-source tools for guiding mitigations in Responsible AI microsoft.com. Checked 19 October 2026.
  6. AgentInstruct: Toward Generative Teaching with Agentic Flows microsoft.com. Checked 19 October 2026.
  7. AgentInstruct: Toward Generative Teaching with Agentic Flows arxiv.org. Checked 19 October 2026.
  8. Robust Heuristic Algorithm Design with LLMs microsoft.com. Checked 19 October 2026.