Bento Natura

Bento Natura

PhD Student in Mathematics

London School of Economics and Political Science

About me

I am a fourth-year PhD student in the Department of Mathematics at the London School of Economics under supervision of László Végh. I am funded by his ERC grant ScaleOpt.

In October 2022 I am joining Georgia Tech as an ARC/ISyE Postdoctoral Fellow.

Both my Bachelor’s and Master’s degrees were received from the University of Bonn under supervision of Stephan Held and Jens Vygen. My research interests are in Operational Research, Combinatorial Optimization, Convex Optimization and Game Theory.

Interests
  • Convex Optimization
  • Combinatorial Optimization
  • Data Structures and Algorithms
  • Game Theory
Education

  • PhD in Mathematics, 2018 -

    London School of Economics and Political Science

  • MSc in Mathematics, 2017

    University of Bonn

News
04/2022 I am joining ICERM at Brown University for Spring 2023 as a Term Postdoctoral Fellow for the program Discrete Optimization
03/2022 In October 2022 I am joining Georgia Tech as an ARC/ISyE Postdoctoral Fellow.
02/2022 A non-technical short Q&A on my research.
05/2021 Laci is giving a series of lectures in the IPCO Summer School on our results on the circuit imbalance measure for linear programming.
03/2021 I am attending the Hausdorff Trimester on Discrete Optimization in Bonn in Michaelmas Term 2021.
11/2020 I was jointly awarded the DODU Prize for the best talk of a young researcher at SMAI MODE.

Publications

Xavier Allamigeon, Daniel Dadush, Georg Loho, Bento Natura, László A. Végh (2022). Interior point methods are not worse than Simplex. In FOCS 2022.

PDF Cite arXiv

Bento Natura, Meike Neuwohner, Stefan Weltge (2022). The Pareto cover problem. In ESA 2022.

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Shunhua Jiang, Bento Natura, Omri Weinstein (2022). A Faster Interior-Point Method for Sum-of-Squares Optimization. In ICALP 2022.

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Daniel Dadush, Zhuan Khye Koh, Bento Natura, László Végh (2021). On Circuit Diameter Bounds via Circuit Imbalances. In IPCO 2022.

PDF arXiv

Farbod Ekbatani, Bento Natura, László Végh (2021). Circuit imbalance measures and linear programming. In Surveys in Combinatorics 2022.

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Daniel Dadush, Zhuan Khye Koh, Bento Natura, László Végh (2021). An Accelerated Newton-Dinkelbach Method and its Application to Two Variables Per Inequality Systems. In ESA 2021.

PDF Cite Slides arXiv

Daniel Dadush, Bento Natura, László Végh (2020). Revisiting Tardos's Framework for Linear Programming: Faster Exact Solutions using Approximate Solvers. In FOCS 2020.

PDF Cite Poster Video arXiv

Daniel Dadush, Sophie Huiberts, Bento Natura, László Végh (2020). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. In STOC 2020.

PDF Cite Video arXiv

Siad Daboul, Stephan Held, Bento Natura, Daniel Rotter (2019). Global Interconnect Optimization. In ICCAD 2019.

Cite Source Document

Teaching

Reinforcement Learning

Postgraduate Course, London School of Economics, Department of Statistics, 2022.

Foundations of Machine Learning

PhD Course, London School of Economics, Department of Statistics, 2021 and 2022.

Algorithms and Programming

Undergraduate Course, London School of Economics, Department of Mathematics, 2020.

Programming in C++

Undergraduate course, London School of Economics, Department of Mathematics, 2019.

Operational Research Methods

Undergraduate course, London School of Economics, Department of Mathematics, 2019.

Further Mathematical Methods

Undergraduate course, London School of Economics, Department of Mathematics, 2018.

Combinatorics, Graphs and Matroids

Undergraduate course, University of Bonn, Research Institute for Discrete Mathematics, 2016.

Calculus I

Undergraduate course, University of Bonn, Institue for Applied Mathematics, 2013.

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