Math search for the masses.

New: We are looking for a new PhD student to start in Fall 2020 - please see the "Jobs" page.

We are creating a system to make finding mathematical information easier. We want students of all ages and the general public to be able to quickly lookup unfamiliar symbols, and see how formulas are defined, used, and analyzed in online resources like WikipediaMath StackExchange, and technical document collections such as CiteSeerX.

These technologies will also be useful for math experts, and for exploring how math is used within and across disciplines. For example, a mathematician studying graph theory could use our system to find related applications in physics, ecology, and social networks.  

Research Goals

To be successful, we need to create innovative search engines, interfaces, and algorithms for extracting and recognizing math. Here are the research topics we are currently working on: 

  • How people search for math online
  • Search interfaces with easy formula authoring, easy inclusion of math in queries, and that present search results so they are easily read, organized, and reused 
  • Indexing and search techniques for individual formulas
  • Indexing and search techniques for document collections that contain both text and math, with support for queries that combine keywords and formulas
  • Fast and accurate recognition of math in handwriting and images
  • Fast and accurate extraction of math from web pages and technical documents (including PDF files, which do not represent the locations or content of formulas)

Related Activities

  • ARQMath. The Answer Retrieval for Questions on Math task will be held as part of CLEF 2020. The ARQMath web page and Twitter page have been set up. Stay tuned for updates!
  • CROHME + TFD 2019 Competition.  An international competition organized around data and evaluation tools concerned with advancing the state-of-the-art in handwritten formula recognition, and detecting formulas in document images. Mashad Mahdavi and Richard Zanibbi are co-organized the competition along with Harold Mouchère (Univ. Nantes, France) and Utpal Garain (ISI, India).  The ICDAR paper on the competition is now available.

The MathSeer Team

MathSeer is being developed through a collaboration of students and faculty at the Document and Pattern Recognition Lab at the Rochester Institute of Technology, and the Intelligent Information Systems Research Laboratory at PennState, along with faculty from the RIT Math department and the Computational Linguistics and Information Processing Lab at the University of Maryland, College Park.

Our multi-disciplinary team includes recognized experts in Information Retrieval, Pattern Recognition, Mathematics, and Math Education. Additional information may be found on the Members page.  


Support for the MathSeer Project

The MathSeer project is made possible through research grants from the Alfred P. Sloan Foundation and the National Science Foundation (USA). All materials on this website reflect the work and opinions of the project team, and not the Alfred P. Sloan Foundation or the NSF. 

MathSeer is supported by the Alfred P. Sloan Foundation and the National Science Foundation