DEI Talks | ”AutoML and Meta-learning for Neural Network Robustness Verification” by Prof. Jan N. van Rijn, Leiden Institute of Advanced Computer Science

Jan N. van Rijn holds a tenured position as assistant professor at Leiden University (ada.liacs.nl), where he works in the computer science department (LIACS) and Automated Design of Algorithms cluster (ADA).

His research interests include artificial intelligence, automated machine learning (AutoML) and meta-learning.

He obtained his PhD in Computer Science in 2016 at Leiden Institute of Advanced Computer Science (LIACS), Leiden University (the Netherlands).

During his PhD, he developed OpenML.org, an open science platform for machine learning, enabling sharing of machine learning results.

He made several funded research visits to the University of Waikato (New Zealand) and the University of Porto (Portugal).

After obtaining his PhD, he worked as a postdoctoral researcher in the Machine Learning lab at the University of Freiburg (Germany), headed by Prof. Dr. Frank Hutter, after which he moved to work as a postdoctoral researcher at Columbia University in the City of New York (USA). His research aim is to democratize access to machine learning and artificial intelligence across societal institutions, by developing knowledge and tools that support domain experts.

He is one of the authors of the book `Metalearning: Applications to Automated Machine Learning and Data Mining’ (published by Springer).”

AutoML and Meta-learning for Neural Network Robustness Verification” will be presented january the 25th, at 14:45, room B006 – free entrance, all are welcome.

Abstract: Artificial intelligence is being increasingly integrated in modern society, with applications ranging from self-driving cars to medicine development. However, artificial intelligence models (in particular neural networks) have been notoriously known for being susceptible for various forms of attacks, including adversarial attacks. In a bid to make these models more trustworthy, the field of neural network robustness verification aims to determine to which degree a given network is susceptible to such an attack. This is a very time consuming task, that can greatly benefit from the various advances that the Automated Machine Learning and meta-learning community have made.

In this talk, it will be explained the basis of automated machine learning and meta-learning, and the speaker will talk about their research on applying this to robustness verification. He will also explain how the community can further engage in this endevour towards trustworthy artificial intelligence.

Talk a Bit is back for its 11th edition

Talk a Bit is back on January 28th (Saturday), at the FEUP Auditorium, for its 11th edition.

The conference is organized annually by the final year students of the Master in Informatics and Computing Engineering of FEUP and is well known for the quality of its programme and the high number of participants.

This year’s theme will revolve around data, “Data. How it’s created, how it’s stored, how it’s streamed, how it’s processed” and will feature a number of experts who will bring a lot of material to be explored and discussed.

The event programme aims to promote learning, the discussion of ideas and social moments and among the list of speakers we can see João Silveira from Microsoft, Sónia Liquito from Spotify, João Gonçalves and José Costa from Critical Techworks, João Carvalho from Tandhem Esports, Liliana Ferreira from Fraunhofer Portugal AICOS, Pedro Dias and Marco Sousa from Zero Zero, Tiago Matos from Jumpseller, (…), who will for sure contribute to another successful edition.

Pre-event (24 to 26 January), an hackaton will be hosted with great prizes for the winners.

All the information and the registration link can be seen here.

DEI Talks | “Clustering Healthcare Data” by Prof. Pasi Fränti

Pasi Fränti received his MSc and PhD degrees from the University of Turku, in 1991 and 1994 in Science. Since 2000, he has been a professor of Computer Science at the University of Eastern Finland. He has published in 99 journals and 175 peer review conference papers. Pasi Fränti is the head of the Machine Learning research group. His current research interests include clustering algorithms, location-based services, machine learning, web and text mining, and optimization of health care services. He has supervised 30 PhD graduates and is currently supervising nine more.

 “Clustering Healthcare Data” will be presented November 7, at 11:00, in room I125 – participation is  free, all are welcome.

 Abstract: Clustering can a powerful tool in analyzing healthcare data. We show how clustering based on k-means and its variants can be used to extract new insight from various data with the aim to better optimize the health care system. We first show that simple variants of k-means and random swap algorithms can provide highly accurate clustering results. We demonstrate how k-means can be applied to categorical data, sets, and graphs. We model health care records of individual patients as a set of diagnoses. These can be used to cluster patients, and also create co-occurence graph of diagnoses depending on how often the same pair of diseases are diagnosed in the record of the same patient. Taking into account the order of the diagnoses, we can construct a predictor for the likely forthcoming diseases. We also provide a clustering algorithm to optimize the location of health care systems based on patient locations. As a case study, we consider coronary heart disease patients and analyze in what way the optimization of the locations can affect the expected time to reach the hospital within the given time. All the results can provide additional statistical information to healthcare planners and also medical doctors at the operational level to guide their efforts to provide better healthcare services.

Featured Informatics Week [31-2]

The Informatics Week (SINF), organized by Núcleo de Informática da Associação de Estudantes da Faculdade de Engenharia da Universidade do Porto (NIAEFEUP), was created with the purpose of allowing students, regardless of their program, to develop skills in several areas of Informatics, promoting their interaction with the business world through social events.

The 2022 edition will take place between October 31st and November 2nd with numerous activities, including lectures and workshops, that will allow participants to get in touch with several technologies and concepts that are not part of the academic program, therefore focusing on technical skills, as well as a pitch, interview sessions and visits to companies, fostering their contact with top national and international companies.

This year the themes of Cybersecurity and Gaming and Interactivity will be in focus and all activities can be seen on the event’s website.

DEI Talks | “Tools and methods for the understanding of road users behaviours” by Prof. Stéphane Espié and “Driving-Pattern Identification and Event Detection Based on an Unsupervised Learning Framework: Case of a Motorcycle-Riding Simulator” by Prof. Abderrahmane Boubezoul

Within the framework of the European University Alliance for Global Health (EUGLOH), we are glad to host the visit of Stéphane Espié and Abderrahmane Boubezoul, visiting DEI during this week (17-21).

Our guests will deliver two seminars on Friday, October 21, at 9:00, in Room B 009. You are all invited!

 “Tools and methods for the understanding of road users behaviours”

By the Author:

“To be efficient and accepted, road safety counter-measures need to be defined thanks to scientific studies. The question is not only to imagine an optimal solution in the absolute, but to understand the real practices and, based on this knowledge, to design the measures (sensitivity campaigns, changes in Highway Code, changes in initial training curriculum or licence tests, infrastructure (re)design, vehicles homologations, etc.).

In our talk we will describe the tools and methods we promote and refined for decades to improve road safety, and their use in research projects. Our approach is systemic and is based on three pillars: instrumentation of vehicles for in-depth naturalistic studies, traffic modelling and simulation using a multi-agents system, and design of driving simulators to study driving behaviours. We will illustrate our approach using research projects we have conducted over these last years.

Stéphane ESPIÉ is a research director at the Gustave Eiffel University. He holds an Accreditation to Direct Research in Computer Science (HdR, Pierre et Marie Curie University, 2004). His main research areas are behavioural traffic simulation (MAS based), and the design of tools to study road user behaviours (driving/riding simulators and instrumented vehicles). He currently conducts his research in SATIE laboratory (Paris Saclay university) where he leads the MOSS (Methods and Tools for Signals and Systems) research group.

“Driving-Pattern Identification and Event Detection Based on an Un-supervised Learning Framework: Case of a Motorcycle-Riding Simulator”

By the Author:

“Analysis of human driving behavior aims to inspect drivers’ behavior in the real-world and in a virtual environment. The study of driving behaviors can be conducted in naturalistic situations or controlled experiments. Analyzing driving behaviors based on the data collected in naturalistic driving experiments or controlled experiments in the real-world or in a virtual environment is beneficial to fill in many of the knowledge gaps about driving behaviors and risk factors. I will present a multi-step framework for analyzing driving behavior on macroscopic and microscopic scales. The core step of this framework is based on unsupervised machine learning algorithms applied to driving-pattern identification and the detection of critical driving events using anomaly-detection algorithms. The detected events are interpreted and described by computing their feature importance using graphs centrality measures. This provides new insight into driving behavior by identifying the motives behind the driver’s actions.

Abderrahmane Boubezoul received his Ph.D. in Computer Science and Mathematics from University Paul Cézanne (Aix-Marseille III), France in 2008 and his Master’s degree in Virtual Reality and Complex Systems from Evry Val d’Essone University, France. Since 2008, he is a researcher at Gustave Eiffel University. His current work is about statistical signal processing and machine learning applied to road transport systems. He currently conducts his research in SATIE laboratory (Paris Saclay university) MOSS (Methods and Tools for Signals and Systems) research group.

Creativity Talks 08 – “A Theoretical Computer Science Perspective on Consciousness: Insights from the Conscious Turing Machine” – Lenore and Manuel Blum

The eighth session of the Creativity Talks will have as keynote speakers the distinguished Professors at Carnegie Mellon School of Computer Science Lenore Blum and Manuel Blum.

Lenore and Manuel Blum, recipients of the PAESMEM and Turing awards, respectively, will present at FEUP “A Theoretical Computer Science Perspective on Consciousness: Insights from the Conscious Turing Machine” on Sep 29 2022, at 6 pm., in Room B032, and also streamed online via Youtube.

“We are Theoretical Computer Scientists. Theoretical Computer Science is a subarea of Mathematics that has tools, we claim, ideally suited to understanding consciousness. We have applied these tools to produce a model of consciousness that we call the Conscious Turing Machine (CTM). Our model gives insight into what goes on in our head to cause us to feel conscious. It also suggests how machines may be constructed to be conscious.

A Turing Machine (TM) is a very simple device defined mathematically by Alan Turing. There is no way that anyone would or should consider a TM to be conscious. However, with the advent of fMRI in 1990, advances in Neuroscience, and the Global Neuronal Workspace Models of Baars, Changeaux, and Dehaene, we have defined a variant of TM, the CTM, that we argue gives insight into consciousness.

Lenore will present and explain our model of consciousness, the CTM. Manuel will discuss how and why the CTM experiences feelings of consciousness”, shares Prof. Blum.

To attend the lecture at the Faculty of Engineering of the University of Porto, please register HERE! Participation at the event is free of charge, but registration is compulsory. Online participation does not require any registration.

Talk link: https://youtu.be/V7BunRG_9-A

Lenore Blum has been passionate about mathematics since she was 10. She attributes that to having dropped out of school when she was 9 to wander the world, then hit the ground running when she returned and became fascinated with the Euclidean Algorithm. Her interests turned to non-standard models of mathematics, and of computation. As a graduate student at MIT, she showed how to use saturated model theory to get new results in differential algebra. Later, with Mike Shub and Steve Smale, she developed a foundational theory for computing and complexity over continuous domains such as the real or complex numbers. The theory generalizes the Turing-based theory (for discrete domains) and has been fundamental for computational mathematics. Lenore is internationally known for her work in increasing the participation of girls and women in STEM and is proud that CMU has gender parity in its undergraduate CS program. Lenore is currently president of the Association for Mathematical Consciousness Science. Lenore Blum: lblum@cs.cmu.edu

Manuel Blum has been motivated to understand the mind/body problem since he was in second grade when his teacher told his mom she should not expect him to get past high school. As an undergrad at MIT, he spent a year studying Freud and then apprenticed himself to the great anti-Freud neurophysiologist Warren S. McCulloch, who became his intellectual mentor. When he told Warren (McCulloch) and Walter (Pitts) that he wanted to study consciousness, he was told in no uncertain terms that he was verboten to do so – and why. As a graduate student, he asked and got Marvin Minsky to be his thesis advisor. Manuel is one of the founders of complexity theory, a Turing Award winner, and has mentored many in the field who have chartered new directions ranging from computational learning, cryptography, zero knowledge, interactive proofs, proof checkers, and human computation. Manuel Blum: mblum@cs.cmu.edu

DEI Talks | “Efficient Engineering of Systems of Systems” by Prof. Jerker Delsing

Professor Delsings research profile can be entitled “Internet of Thing Services and Systems”, with applications to automation in large and complex industry and society systems. Addressing design, engineering, and deployment of System of Systems (SoS) capable of collaborative automation, Prof. Delsing and his EISLAB group has participated in important EU projects like SocradesIMC-AESOP, Arrowhead and Productive4.0 project.

“Efficient Engineering of Systems of Systems” will be presented July the 26th, at 10:00, room I-105.

Areas of Research / Professional Expertise

“Delsing has a long standing in ultrasound sensor technology in particularly applied to flow measurement. His present research profile can be entitled “Internet of Thing Services and Systems”, with applications to automation in large and complex industry and society systems. The approach is based on Internet of Things (IoT) and the design engineering, and deployment of System of Systems (SoS) capable of collaborative automation. The integration and manufacturing of necessary electronics is a of key interest. Prof. Delsing and his EISLAB group has been a partner of several large EU projects in the field, e.g. Socrades and IMC-AESOP and ESIS. Currently he is the coordinator of the very large ARTEMIS project Arrowhead,  with 78 partners and a budget of 69M€.

Delsing has been supervisor for 37 students receiving the PhD degree, with some 45+ students in total for the EISLAB group. His list of publications can be found at: https://scholar.google.se/citations?user=_XLRuYAAAAAJ&hl=sv

Delsing is highly involved in the innovations systems related to automation and embedded systems. At the European level he is steering board member of ARTEMIS, board member of ProcessIT.EU. At national (Sweden) level he is board member of ProcessIT Innovations and ESIS. From 1998 – 2015 he was the chairman of ITF (Instrument Tekniska Föreningen/Instrument Society of Sweden) with about 1.000 automation engineers as members.”

Bio

“Prof. Jerker Delsing received the M.Sc. in Engineering Physics at Lund Institute of Technology, Sweden 1982. In 1988 he received the PhD. degree in Electrical Measurement at the Lund University. During 1985 – 1988 he worked part time at Alfa-Laval – SattControl (now ABB) with development of sensors and measurement technology. In 1994 he got the docent degree (associate prof) in Heat and Power Engineering. Early 1995 he was appointed full professor in Industrial Electronics at Luleå University of Technology where he currently is working as the scientific head of EISLAB, http://www.ltu.se/eislab. For the period 2004-2006 he also served as Dean of the engineering faculty at Luleå University of Technology.”

Source: https://www.routledge.com/

DEI OPEN DAY | Return in loco on July 12

On July 12th, DEI Open Day 2022 will finally return to in loco format.

This event takes place annually and aims to be a showcase of the teaching and research activity of the Department of Informatics Engineering of FEUP, with the goal of strengthening the collaboration of DEI with companies and its connection to the community.

Exploring this year’s theme, “Undergraduate + Masters to train the computer engineers of the future“, themes such as the role of undergraduate degrees and masters in the comprehensive training of Computer Engineers will be addressed in a joint reflection between teachers and guests from industry.

There will also be an opportunity to learn about ongoing projects in the DEI laboratories and, after lunch, a visit to the stands of these laboratories and the π Projects Fair (projects of final-year students of L.EIC undergraduate course).

+ info: programme

DEI Talks |”From building installations, through archaeology to precision agriculture” – Projects of the Jaén Graphics and Geomatics Group (GGGJ)

“From building installations, through archaeology to precision agriculture ” will be presented July the 13th, room B019 , at 15:00.

Abstract:

 The GGGJ research group celebrates its 25th anniversary working in two areas, Computer Graphics and Geomatics. The projects that have been awarded lately are also in these lines of research.

The so-called project: “Computer Graphics tool for 3D and 4D data management. Applying VR & AR techniques to Urban Infrastructures and Archaeology” (2018-2021) completed in December 2021, is oriented to 4D models hidden or disappeared for the view.

New projects now active are focused on Precision Agriculture, mostly oriented to the olive grove. The last one granted by the Spanish Ministry (180,000 euros) is entitled:” 3D/4D tools for the generation of digital twins of rural environments. Applications” starts in September and has a duration of 3 years.

Bios:

Francisco Feito, graduated in Mathematics (specializing in Pure Mathematics) in 1977, at the Complutense University of Madrid. After 12 years in pre-university teaching, he joined the University of Granada (Jaen Campus). In 1993 (already constituted the University of Jaen) he was elected Director of the Department of Computer Science (which included, and still includes, the areas of Computer Languages and Systems, Computer Science and Artificial Intelligence and Computer Architecture and Technology). In 1997 he was appointed General Director of Curriculum and Quality of the University of Jaén and in 1999 Vice-Rector of Research and International Relations (until 2002). Subsequently he was again Director of the department from 2004 to 2008. He has been a member of the faculty and of several University committees.

Areas of interest: Geometric Modeling; Solid Modeling; Algorithms in Computer Graphics; Geomatics; Computational Geometry; Spatial Information Systems; Geographic Information Systems; Precision Agriculture in the Olive Grove; Virtual Reality/Augmented Reality; Simulation; Smart City; Digital Twin- Digital Twin.

Lidia. M. Ortega received the BSc degree in Computer Science from the University of Granada (Spain), and the PhD degree from the University of Seville. She has been an associate professor at the Department of Computer Science at University of Jaén teaching at the High Polytechnics Institute since the 90s. Her research work focuses on computational Geometry applied to Computer Graphic, 3D-GIS, Spatial databases, Geomatics and Agriculture precision.

2022 MDSE – Sunset Session: Ethics and Responsability in AI

With the preparation of the 3rd edition of the M.Sc. on Data Science and Engineering (https://dei.fe.up.pt/mdse/) well under way, it is time to look back at what was accomplished so far and also to project the future. This will be done as part of the 2022 MDSE Sunset Session, on the 2nd July (Saturday), in room B032, in a relaxed environment but focused on a very important topic: Ethics and Responsability in AI.

The program will feature two keynote talks, by Ana Costa e Silva (Mercer) and Pedro Saleiro (Feedzai), as well as a panel discussion including Inês de Matos Pinto (S&D Group @ European Parliament)Inês Sousa (Fraunhofer Portugal) and Peter van der Putten (Pegasystems & U. Leiden), moderated by Eugénio Oliveira (FEUP). During the event MDSE students will also present some of their projects.

The event is targeted both to companies, looking for talent in Data Science, as well as prospect students, looking for an advanced education on Data Science.

Participation is free but requires registration here.

 Program

14:30 – Opening – João Mendes Moreira – Director of the M.Sc. on Data Science and Engineering (MDSE)

14:40 – Ana Costa e Silva – Global Chief of Data Science @ Mercer, TBA – introduced by António Pedro Aguiar

15:10 – Pedro Saleiro – Director of AI Research @ Feedzai, challenges in the development of responsible AI research/solutions in Industry – introduced by José Luís Borges

15:40 – MDSE Student Showcase – introduced by Ana Aguiar

  • Cláudia Pinheiro: AI-based cancer characterization using semi-supervised learning algorithms
  • Diogo Queirós: Reconciling prediction in the regression setting: an application to Portuguese breweries’ market share prediction
  • Nuno Gaspar: Prediction of Shell Finite-Element Stresses using Convolutional Neural Networks (CNN)
  • Rafael Guedes: Data, machine vision and reinforcement learning for explainable and safe autonomous driving of platooning vehicles
  • Wagner Ceulin: Predicting customer purchasing behavior of a self-care online store
  • João Pedro Pêgo: Predicting candidate engagement in a job matchmaking site

16:30 – Coffee Break

17:10 – Panel discussion – moderated by Eugénio de Oliveira – Emeritus Professor @ FEUP

18:20 – Closing João Mendes Moreira – Director of the MDSE

18.30 – Sunset Drinks & Networking

19.30 – End of the event

We are very grateful to our partner for their support