PeopleofSuperintelligence

Researcher

Dan Geiger

Dan Geiger is a computer scientist whose work connects probabilistic AI with genetic analysis through Bayesian networks. He earned a PhD at UCLA in 1990 under Judea Pearl and coauthored studies of network independence, Bayesian-network learning, and genetic linkage. He co-chaired UAI '97 and coauthored a 2006 paper about Superlink Online, a pedigree-linkage tool; a 2020 study he coauthored examines a genomic region linked to heritable pulmonary arterial hypertension. As of October 2026, he is Professor Emeritus of Computer Science at the Technion, where he earlier served as department dean.

Now at
Technion
Works
190
Citations
17,948
h-index
51
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1990

    A PhD at UCLA

    He completes a PhD at UCLA in 1990 under Judea Pearl. His research centers on probabilistic models for intelligent systems, including Bayesian networks and bioinformatics.

  2. 1990

    Independence in Bayesian networks

    With Thomas Verma and Judea Pearl, he coauthors “Identifying independence in Bayesian networks” in 1990.

  3. 1995

    Learning Bayesian networks

    With David Heckerman and David M. Chickering, he coauthors a paper in 1995 on learning Bayesian networks from user knowledge and statistical data.

  4. 1997

    UAI '97 program chair

    In 1997, he co-chairs the UAI program with Prakash P. Shenoy.

  5. 2002

    Exact linkage for pedigrees

    With M. Fishelson, he coauthors “Exact genetic linkage computations for general pedigrees” in 2002.

  6. 2006

    SUPERLINK-ONLINE for pedigrees

    In 2006, he coauthors a paper on Superlink Online, a linkage-analysis tool that finds suspected disease-gene locations from pedigree information.

  7. 2020

    A 2q24.3 genetics study

    He coauthors a study that identifies a genomic region in 2q24.3 as a candidate modulator of reduced penetrance in heritable pulmonary arterial hypertension in 2020.

  8. As of October 2026

    Professor emeritus at Technion

    He is Professor Emeritus of Computer Science at the Technion. His earlier department roles include dean.

Career

  1. Since 1992TechnionDean of the department
  2. 1994–2001Microsoft

Education

  1. 1990University of California, Los AngelesPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes Technion. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Technion. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. 41% of people who worked abroad later worked in their country of birth among people with a recorded birth country and dated work historyIncludes Technion. Of 991 people with a recorded birth country who worked outside it, 410 (41%) later held a work position at home, led by the United States at 69%.
  4. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Microsoft. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Distinguished Alumni | CS cs.ucla.edu. Checked 22 October 2026.
  2. Identifying independence in bayesian networks - MaRDI portal portal.mardi4nfdi.de. Checked 22 October 2026.
  3. dang_journal_papers_sorted dang.cs.technion.ac.il. Checked 22 October 2026.
  4. [1302.6815] Learning Bayesian Networks: The Combination of Knowledge and Statistical Data arxiv.org. Checked 22 October 2026.
  5. UAI-97 Tentative Program auai.org. Checked 22 October 2026.
  6. Exact genetic linkage computations for general pedigrees (2002) – Bioinformatics | Metascience Observatory Explorer explore.metascienceobservatory.org. Checked 22 October 2026.
  7. Dan Geiger | Head of the Computational Biology Laboratory dang.cs.technion.ac.il. Checked 22 October 2026.
  8. Dan Geiger - Technion - Israel Institute of Technology cris.technion.ac.il. Checked 22 October 2026.