Research

Broadly speaking, my research interest lies in computational mathematics. I like to turn abstract math into working efficient code and apply it to solve real problems in various engineering domains, such as computer vision, positioning, and robotics. My language-of-choice is Julia, but I am also comfortable with Python, Matlab, Haskell, C and C++. Topics I have worked with include: computational algebraic geometry, geometric computer vision, algorithms for positioning, interval arithmetic, automated reasoning and fuzzy logic.

I strongly believe research software is a fundamental part of research, and I believe open-science and open-education are fundamental values. Combining the two, I believe writing good open-source research software is just as important as writing the paper describing the results. I try to promote these values as much as I can, maybe one day it will make the difference.

You can find my full list of publication in my academic cv.

Here some highlights of my latest research outputs

  1. Papers
  2. Talks
  3. Thesis

Papers

Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes

L.Ferranti, K.Åström, M.Oskarsson, J.Boutellier, J.Kannala, 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022,

Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if...
arxiv

Homotopy Continuation for Sensor Networks Self-Calibration

L.Ferranti, K.Åström, M.Oskarsson, J.Boutellier, J.Kannala, 2021 IEEE European Signal Processing Conference (EUSIPCO), 2021,

Given a sensor network, TDOA self-calibration aims at simultaneously estimating the positions of receivers and transmitters, and transmitters time offsets. This can be formulated as a system of polynomial equations. Due to the elevated number of unknowns and the nonlinearity...
arxiv

Sensor Networks TDOA Self-Calibration: 2D Complexity Analysis and Solutions

L.Ferranti, K.Åström, M.Oskarsson, J.Boutellier, J.Kannala, 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021,

Given a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration. In this paper we consider 2D networks with synchronized receivers but unsynchronized transmitters and the corresponding calibration techniques, known...
arxiv

Can You Trust Your Pose? Confidence Estimation in Image-Based Localization

L.Ferranti, X.Li, J.Boutellier, J.Kannala, 2020 International Conference on Pattern Recognition (ICPR), 2020,

Camera pose estimation in large-scale environments is still an open question and, despite recent promising results, it may still fail in some situations. The research so far has focused on improving subcomponents of estimation pipelines, to achieve more accurate poses....
arxiv

Towards Algebraic Modeling of GPU Memory Access for Bank Conflict Mitigation

L.Ferranti, J.Boutellier, 2019 IEEE International Workshop on Signal Processing Systems (SiPS), 2019,

Graphics Processing Units (GPU) have been widely used in various fields of scientific computing, such as in signal processing. GPUs have a hierarchical memory structure with memory layers that are shared between GPU processing elements. Partly due to the complex...