[seminarios-mlpb] Thursday June 27th, 13:00, PA2: Claudia Soares on "Learning of leader-follower graph from time-correlated big data streams with missing entries"

[Sebastião Miranda]

Hello all,

Next week Claudia Soares, Professor at DEEC/IST and researcher at Signal and Image Processing Group (SIPG) - Institute for Systems and Robotics (ISR), will present her work on "Learning of leader-follower graph from time-correlated big data streams with missing entries" on Thursday June 27th at 13:00h (room PA2- Pav. Matemática, IST).

Due to a large number of leftovers, we kindly ask you to please register only if you intend to attend the event:

https://www.eventbrite.pt/e/learning-of-leader-follower-graph-from-time-correlated-big-data-streams-with-missing-entries-tickets-63384616093     

Best regards,
Sebastião Miranda, 
sebastia...@priberam.pt

Priberam Labs
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PRIBERAM SEMINARS   --  Room PA2
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Priberam Machine Learning Lunch Seminar
Speaker:  Claudia Soares (SIPG - ISR)
Venue: IST Alameda, Room PA2 (Pavilhão de Matemática)
Date: Thursday, June 27th, 2019
Time: 13:00 (Lunch will be provided)

Title:

Learning of leader-follower graph from time-correlated big data streams with missing entries
 

Abstract:

Nowadays we are collecting high-dimensional and large data streams, where many dimensions can be expressing basically the same information on the underlying process of interest. This redundancy is apparent, for example, if we observe mass media news outputs through time. Here, even the discovery of the leader-follower structure of the news streams is valuable information.

I will be presenting very recent work approaching the leader-follower problem with missing entries, using scalable and accurate algorithms for big data streams.

 

Bio:

Claudia Soares works in Big Data and distributed processing, working at ISR Lisboa. She strongly believes in developing research with academia and industry, exchanging ideas and methods for effective, simple, and scalable algorithms — and for solving real problems. Her research dwelves on developing a generic framework for learning with large-scale, heterogeneous, and space-time dependent data. For this work, Dr. Soares developed both parallel and stochastic algorithms, where nodes compute asynchronously, mostly with outdated data.

Approaching real-world problems resulted in successful projects and publications in top venues. She has been collaborating with companies to address problems that are both real and aligned with her scientific interests. In this context, she worked with national and international industries like NOS, Nomad-Tech (CP), TAP, Thales, 3Lateral, uRoboptics, and developed academic collaborations with International partners like the TU/e, U. Milano, and U. of Novi Sad. Dr. Soares has a key role in funded projects of the national agency (FCT) in Data Science and AI for predicting ECU admissions and EU funded projects in AI, namely AI4EU -- European AI On Demand Platform and Ecosystem, and a European Doctoral program, BIGMATH,  for BIG data challenges for MATHematics.

More info: 
http://labs.priberam.com/Academia-Partnerships/Seminars.aspx

Eventbrite: 
https://www.eventbrite.pt/e/learning-of-leader-follower-graph-from-time-correlated-big-data-streams-with-missing-entries-tickets-63384616093