news
 November 2017.
My two MSc students just graduated, both with
grade 19 in 20! Congratulations for your excellent work this year! I
was also invited to give a talk on the Optimization group of the Math
department of FCTUNL. It was very interesting and we talked about
lots of cool new problems. I just signed my contract as an Invited
Assistant Professor at DEEC/IST.
 October 2017.
I was invited to present at SIAM IS18. My talk will
be about Distributed learning in large scale networks: from GPSdenied
localization to MAP inference in a graphical model.
 July 2017.
I found some great crowd at IFORS! Stefania Bellavia
from Italy, with some very interesting work on SDPs, Natasa Krejic,
Natasa Krklec Jerinkic and Dusan Jakovetic doing gamechanger distributed
optimization from Serbia, Ana Luisa Custodio from FCT, Portugal, with
an impressive work on derivative free optimization. What a great
conference!
 June 2017.
We have an accepted paper at OCEANS’17 at
anchorage. It is all about distributed maximum likelihood localization
of mobile agents. Amazingly, we beat an extended Kalman filter, with a
centralized architecture! A big thanks to my coauthors: Pusheng Ji,
João Pedro Gomes and António Pascoal!
 May 2017.
I successfully submitted Project DIPLOMAT to the FCT
call 02/SAICT/2017 as PI! A huge thank you to my coPI João Pedro
Gomes, and the team which shared this journey with us: João Xavier,
Anders Lyhne Christensen, Sancho Oliveira, and António Pascoal. Here's
a bit on the abstract: “Smart city sensing, sea exploration, robotics
and assisted living  four forces promoting the wellbeing and
development of our society  struggle with a problem triggered by
technologies that empowered us with devices capable of computing,
communication and environmental sensing. How can we process the data
collected by this unprecedented number of agents? For this era of
distributed Big Data we need distributed processing, where centralized
solutions are recreated in an emergent and scalable way by network
agents collecting raw data  not by having them flood the network, but
by having them exchange wellcrafted messages with a distributed
algorithm.”
 February 2017.
Our abstract on distributed and robust network
localization was accepted at IFORS’17, for the
distributed optimization track. The conference will be held in Quebec
City.
 January 2017.
I submitted a very exciting paper on robust distributed localization for networks of mobile
agents, jointly with Joao Pedro Gomes, Beatriz Ferreira and Joao Paulo
Costeira. Our algorithm is called LocDyn, works like a filter,
depending only on a few past estimates of the positions, and at each
time step computes distributedly the MAP estimate of the current
positions. Also, I presented the last session of the crash course on
scientific writing. The slides for both sessions are gathered
here.
 November 2016.
I've presented the
first of two sessions of a short crash course on scientific writing,
based on the book
The Writer's Diet by Helen Sword and also on my professional past
experience as a copywritter. Thanks to Sabina Zejnilovic for calling
my attention to a typo on the presentation.
 October 2016.
Thanks to the people in
CEMAT for inviting me to present
on their Probability and Statistics Seminar. My special thanks to the
organizer, Ana Henriques, and Professor
Manuel Cabral Morais. I presented some of my work on
distributed
network localization. We also went through some cool
proof sketches. The audience
was interested and interesting — thanks for all the comments and
questions!
Joao Pedro Gomes and I submitted a paper on
robust and distributed network
localization — those dealing with realworld systems know how
outliers plague data! We developed a soft outlier rejection estimator
and convexified it. We presented two methods for dealing with outlier
measurements, one working under an synchronous time model, and
another for asynchronous distributed computation. Both are really
fast: the sync algorithm is a first order method using Nesterov
optimal gradient iterations, and the async one is a (provably
convergent) coordinate descent method. Surprisingly, the async
algorithm is competitive in the number of communications with the
synchronous one, despite the requirements on the network operation
are much milder.
things I like
