Research at LaMaStEx is at the interdisciplinary interface of computing, mathematics and statistics. We use computer arithmetic and combinatorial data-structures through custom-built mathematical and statistical models to rigorously solve numerical optimization and simulation problems that arise in statistical decision-making from real-world data.

Details of research:

Current research projects in scalable data science

Research Vision and Grants

Most Important Contributions to Research & Current Directions

Mathematical Statistical Combinatorial Stochastic Processes & Data Science

  • Ancestries of a Recombining Diploid Population, Raazesh Sainudiin, Bhalchandra Thatte, and Amandine Véber, Journal of Mathematical Biology, Volume 72, Issue 1, pp 363-408, 2016 (preprint PDF 436KB). The final publication is available at Springer via 10.1007/s00285-015-0886-z
  • Experiments with the Site Frequency Spectrum, Raazesh Sainudiin, Kevin Thornton, Jennifer Harlow, James Booth, Michael Stillman, Ruriko Yoshida, Robert Griffiths, Gilean McVean and Peter Donnelly, Inaugural Issue in Algebraic Biology, Bulletin of Mathematical Biology, Volume 73, Number 4, 829-872, 2011 (AMS review)
    • Towards general lumped controlled Markov processes (basis for privacy-preserving decision procedures with social-media and geospatial trajectory data with others at UU as explained below)
    • Towards distributed computing algorithms for Population Genomic Inference with Veber (Paris) and EEB-based Pop-gen group (early stages; journal-clubs, 360-in-525-05 population genomics and big data course, etc.)
  • The Transmission Process: A Combinatorial Stochastic Process for the Evolution of Transmission Trees over Networks, Raazesh Sainudiin and David Welch, Journal of Theoretical Biology, Volume 410, Pages 137–170, 10.1016/j.jtbi.2016.07.038, 2016. See research project: Meme Evolution Programme
    • Towards SIR/SIS models, Population Ideological Forests in Twitter, and their Dynamic models (much harder problems; joint work with Veber and Gaiffas in Paris)

Computer Arithmetic & Data Science

  • Mapped Regular Pavings, Jennifer Harlow, Raazesh Sainudiin and Warwick Tucker, Reliable Computing, vol. 16, pp. 252-282, 2012 (PDF 972KB)
  • Minimum distance estimation with universal performance guarantees over statistical regular pavings, Raazesh Sainudiin and Gloria Teng, 17 pages, 2018 (PDF 708KB)
    • Towards Scalable (big data friendly) variants that can be used in real-world industry-scale problems (Anamoly Detection, Predictive Maintenance, etc.) (working with Tilo Wiklund, Maths@UU and Warwick Tucker on arithmetical aspects; got three submissions of applications relevant to Combient AB, Stockholm)
    • Towards Privacy-Preserving Tree Arithmetics for geospatial trajectories

Grants and Research Collaborators - Next 5-6 years

Research Grants Concluded in 2017

  • 245Kkr/2.95Mkr: EU Marie Curie Actions People (Co-applicant with countepart funding from Royal Society of NZ) on Project CORCON: Correctness by Construction (30% rsrch)
    • main output:
      • MRS 2.0: A C++ Class Library for Statistical Set Processing and Computer-Aided Proofs in Statistics (Version 2.0) [Software], Available from https://github.com/lamastex/mrs2, 2017

Research Grants Won in 2017-2018 for 2018-2025

Research-led Teaching Grants Won in 2017-2018

Research Grants Applied for in 2018-2024 (waiting on decision)

  • 14.9Mkr: VR Research Environment Grant (Migration and Integration); Integration in a mobile society, modelling and analysing how everyday mobility is shaping the potential for integration
  • 29Mkr: VR Research Environment Grant (Interdisciplinary Research); Privacy-preserving Decisions from Social Media Communications and Geo-spatial Movements of a Sovereign European Population
    • Main Applicant with some of the key participating researchers (40% rsrch + 4 PhDs):
      • Anna Sara-Lind, Professor of Public Law at the Faculty of Law, Uppsala University
      • John Östh, Associate Professor, Department of Cultural and Economic Geography, Uppsala University
      • Stéphane Gaïffas, Professeur, Laboratoire de Probabilités et Modèles Aléatoires, Université Paris Diderot, Paris, France
      • Amandine Veber, CNRS Researcher, Centre de Mathématiques Appliquées, École Polytechnique, Palaiseau, France
  • 4.8Mkr: Twitter Health Metrics Research; Scalable Markov Kernels from Twitterverse to the GDELT Project
    • Main Applicant (20% rsrch + 1 PhD)
  • 2.9Mkr: Research grant jointly with Blavtnik Interdisciplinary Cyber Research Center, a Telecom Company and Tel Aviv University, Israel Mobile Phone Data for Society and Privacy for the Individual: From the Conflict to a Synergy in Transport Flows Analysis
    • Co-PIs with Professors Itzhak Benenson and Itzhak Omer, Porter School of Environment and Geoscience, Faculty of Exact Sciences, Tel Aviv University (10% rsrch + 1 PhD co-supervision)