PeopleofSuperintelligence

Researcher

Christine Piatko

Also known as Christine D. Piatko

Christine Piatko is a research scientist whose work spans clustering, language technologies, and AI for scientific discovery. She earned a B.A. in computer science and mathematics from New York University in 1986, an M.S. in computer science from Cornell in 1989, and a Cornell computer science Ph.D. in 1993. Her 2002 paper presented an efficient filtering implementation of Lloyd's k-means algorithm. In 2007, she coauthored text-categorization research and helped establish Johns Hopkins's Human Language Technology Center of Excellence; in 2010, she coauthored a center overview. In 2026, she coauthored SFBench, a benchmark for evaluating scientific-claim feasibility; as of October 2026, she is a principal research scientist and project manager at Johns Hopkins APL, with a research faculty appointment in computer science.

Works
94
Citations
8,891
h-index
25
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 1986–1993

    Degrees at NYU and Cornell

    She earns a B.A. in computer science and mathematics from New York University in 1986, an M.S. in computer science from Cornell in 1989, and a Cornell computer science Ph.D. in 1993.

  2. 2002

    An efficient k-means algorithm

    In 2002, she coauthors the paper "An efficient k-means clustering algorithm: Analysis and implementation," which presents a simple filtering implementation of Lloyd's algorithm.

  3. 2007

    Text categorization and HLTCOE

    In 2007, she coauthors "Using “Annotator Rationales” to Improve Machine Learning for Text Categorization" with Omar Zaidan and Jason Eisner. Johns Hopkins's Human Language Technology Center of Excellence is founded in 2007, and she is instrumental in establishing it.

  4. 2010

    Establishing a language center

    In 2010, she coauthors an overview of the Human Language Technology Center of Excellence with Gary Strong and Jason Eisner.

  5. 2026

    SFBench for scientific claims

    In 2026, she coauthors SFBench, a benchmark for evaluating whether systems can assess the feasibility of scientific claims. It includes 197 materials-science claims with ground-truth feasibility scores.

  6. As of October 2026

    Research scientist at APL

    As of October 2026, she is a principal research scientist and project manager at Johns Hopkins APL, where her recent work focuses on AI for scientific discovery in chemistry and materials science; she holds a research faculty appointment in the Johns Hopkins Department of Computer Science.

Career

  1. Since 1997Johns Hopkins UniversityPrincipal Research Scientist and Project Manager

Education

  1. 1993Cornell UniversityPhD
  2. 1989Cornell UniversityM.S.
  3. 1986New York UniversityB.A.

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

Most-cited works

  1. An efficient k-means clustering algorithm: analysis and implementation2002 · IEEE Transactions on Pattern Analysis and Machine Intelligence · 5,652 citations
  2. A visibility matching tone reproduction operator for high dynamic range scenes1997 · IEEE Transactions on Visualization and Computer Graphics · 764 citations
  3. A local search approximation algorithm for k-means clustering2002 · 476 citations
  4. Using “annotator rationales” to improve machine learning for text categorization2007 · 250 citationsWith Jason Eisner
  5. Comparing Real and Synthetic Images: Some Ideas About Metrics1995 · Eurographics · 128 citations

From OpenAlex, as of 19 October 2026.

  1. Google has the highest combined h-index among AI organizationsIncludes Johns Hopkins University. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  2. Stanford University trained or employed 20 of the 89 AI major-prize winners, more than any other universityIncludes Johns Hopkins University. Stanford University trained or employed 20 of the 89 AI major-prize winners, more than any other university. We compare doctorate and employment links for major-prize and best-paper winners.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Johns Hopkins University. Our estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.
  4. The company share of AI researchers’ top papers rose from 2% to 32%Includes Johns Hopkins University. 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.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Christine Piatko's home page cs.jhu.edu. Checked 19 October 2026.
  2. Efficient Algorithms for K-Means Clustering cs.umd.edu. Checked 19 October 2026.
  3. Using “Annotator Rationales” to Improve Machine Learning for Text Categorization aclanthology.org. Checked 19 October 2026.
  4. Christine D. Piatko | Johns Hopkins University Applied Physics Laboratory jhuapl.edu. Checked 19 October 2026.
  5. About | Human Language Technology Center of Excellence hltcoe.wordpress.com. Checked 19 October 2026.
  6. SFBench: The SciFy Scientific Feasibility Benchmark arxiv.org. Checked 19 October 2026.