Welcome to the School of Computer Science and Information Technologies Seminar Series

"We can only see a short distance ahead,
but we can see plenty there that needs to be done."
~ Alan Turing, Computing machinery and intelligence

News Update

Following the announcement from the Taoiseach, and UCCs closure, the CSIT seminar series is postponed until further notice.

About CSIT Seminar Series

Upcoming Seminars

Past Seminars

Register Your Interest


The CSIT seminar series aims at creating opportunities to connect with colleagues and to focus on shared interests in both the research and practice. We hope to foster collaboration, the creation of new ideas and to achieve better visibility for members of the CSIT research community in UCC.

Our all-inclusive approach allows for a broad range of topics and backgrounds and we hope to bring to light the great many ways the CS research community is impacting society through research and teaching.

The seminar series is a great opportunity for any CS staff and CS postgraduate students to engage with colleagues and share their latest findings, practice a conference talk, review their domain or give a tutorial, among other things. Attendance is welcome from the School staff members and students.

If you are interested in participating in the seminar series, please fill out our registration form

If you ave any feedback (good or bad), we would love to hear from you. You can use our feedback form.

This series is BYOB (Bring Your Own Beverage), we will try to bring biscuits.

If you have questions, feel free to contact us. You can find our contact details by clicking here.

Upcoming Seminars

Date, Time, Place, Talk Type Speaker, Position, Affiliation Title, Abstract, Keywords
12/March/2020 13:00 - 14:00, WGB 405, Presentation of a technical piece of work
Rodrigo Fernandes de Mello, Associate Professor, University of Sao Paulo
Title: On Computing the Shattering Coefficient to Analyze the Bias of Supervised Learning Algorithms with Applications to Deep Learning
Abstract: The Statistical Learning Theory (SLT) provides the foundation to ensure that a supervised algorithm generalizes the mapping f : X → Y given f is selected from its search space bias F. SLT depends on the Shattering coefficient function N(F, n) to upper bound the empirical risk minimization principle, from which one can estimate the necessary training sample size to ensure the probabilistic learning convergence and, most importantly, the characterization of the capacity of F, including its under and overfitting abilities while addressing specific target problems. However, the precise computation of the Shattering coefficient is still an open problem, which we address in this paper by firstly estimating the maximal number of hyperplanes required to shatter any data sample based on the recent contributions by Har-Peled and Jones, and then we estimate the Shattering coefficient for both binary and multi-class problems. As main contributions, (i) our approach allows to study the complexity of the search space bias F, (ii) estimate training sample sizes, and (iii) parametrize the number of hyperplanes necessary to address some supervised task, what is specially appealing to deep neural networks, as evidenced by our experiments.
Keywords: Statistical Learning, Modeling complexity
12/March/2020 14:00 - 15:00, WGB 405, Presentation of a technical piece of work
Subhrakanti Dey, Professor, Hamilton Institute Maynooth University
Title: Energy-Neutral IoT for sensing and control
Abstract: As billions of devices are expected to be powered in the next generation of Internet of Things (IoT), ambient energy harvesting and wireless power transfer are two fast maturing technologies, that will become highly relevant. In numerous applications involving autonomous systems, smart homes, Industry 4.0 and advanced healthcare, we expect to see more and more wireless sensor networks powered by energy harvesting. Such networks may be deployed for specific tasks such as remote detection and estimation (smart agriculture) or wireless control (smart automation, autonomous systems). While most of the existing research on the use of sensor networks in such applications have focused on battery-powered sensors and how to increase their lifetimes, the potential problems are very different under the energy harvesting scenario. While energy harvesting promises the sensors to be perpetually powered, the availability of harvested energy is often random and unpredictable. Designing detection, estimation and control algorithms under the constraints of unreliable energy availability at the sensors gives rise to challenging co-design problems of estimation and control algorithms and optimal power management strategies. In this talk, we will look at some examples of remote estimation and wireless control where optimal energy/power allocation for sensing, processing and information transmission will be investigated with a goal of directly optimizing the estimation or control performance. Dynamic optimization problems will be formulated over a finite or infinite horizon and stochastic control based optimal solutions will be provided, along with reduced-complexity heuristics based algorithms and their numerical performance. An example of a recent case study in a paper mill in Sweden will be also provided for wireless process control.
Keywords: IoT, energy harvesting, wireless control
18/March/2020 12:00 - 13:00, WGB-G16, Presentation of a technical piece of work Md Noor-A-Rahim, Marie Curie Fellow, Connect Title: DNA-based Data Storage
Abstract: With ultra-high density and preservation longevity, Deoxyribonucleic acid (DNA)-based data storage is becoming an emerging storage technology. Firstly, this talk will present the motivation behind the concept of DNA data storage. The principle of digital data reading and writing in DNA will be discussed. We will show our proposed DNA data storage scheme, which was validated through wet-lab experiment. Lastly, the research challenges and future works will be highlighted.
Keywords: DNA, data-storage, coding
25/March/2020 12:00 - 13:00, WGB-G08, TBC Eduardo Vyhmeister, Post-doc, Insight@UCC To be confirmed
01/Apr/2020 12:00 - 13:00, WGB-G08, CS7003 Speaker - details to follow To be confirmed
08/Apr/2020 12:00 - 13:00, WGB-107, Maurizio Mancini, Lecturer, To be confirmed
15/Apr/2020 12:00 - 13:00, WGB-107, Presentation of a technical piece of work
Cathal Hoare, Part time lecturer, UCC
Title: Receiving and Decoding NOAA Weather Satellite Imagery Using Software Defined Radio
Abstract: SDR provides endless opportunities to do 'fun' things and provides a medium through which STEM and programming in particular can be promoted and taught. This tutorial will provide a 30 minute introduction to using SDR and other tools to receive satellite communications. The talk will then talk about how these signals can be transformed into photographs.
Keywords: NOAA, Software Defined Radio, Sound to Image processing
22/Apr/2020 12:00 - 13:00, WGB-107, Available
29/Apr/2020 12:00 - 13:00, WGB-107, Available
06/May/2020 12:00 - 13:00, WGB-107, CS7003 Speaker - details to follow To be confirmed
13/May/2020 12:00 - 13:00, WGB-107, Available
20/May/2020 12:00 - 13:00, WGB-107, Available
27/May/2020 12:00 - 13:00, WGB-107, Available
03/Jun/2020 12:00 - 13:00, WGB-107, Piotr Sobonski, PhD Student & Senior Researcher, UTRC & Cybersecurity@Utz@UCC To be confirmed
10/Jun/2020 12:00 - 13:00, WGB-107, Available
17/Jun/2020 12:00 - 13:00, WGB-107, Available
23/Jun/2020 12:00 - 13:00, WGB-107, Available
30/Jun/2020 12:00 - 13:00, WGB-107, Available

Past Seminars

Date, Time, Place, Talk Type Speaker, Position, Affiliation Title, Abstract, Keywords
04/March/2020 12:00 - 13:00, WGB-G08, Presentation of a technical piece of work
Bernd-Ludwig Wenning, Research Fellow, CONNECT@CIT
Title: Client-side AI for uplink data rate estimation in mobile networks
Abstract: Remote monitoring, diagnosis and maintenance, e.g. of autonomous or semi-autonomous vehicles, requires reliable uplinks with sufficient data rates to send sensor data to their monitoring and maintenance services. When the vehicle has multiple uplink options (e.g. different technologies such as 3G, 4G and 5G or subscriptions to different operators), the most suitable or reliable uplink should be chosen. However, client-side assessment of uplink quality is a challenge in mobile networks, as the related parameters are usually only available on the operator's side, while the client only has access to downlink parameters. Our research employs AI methods on the client to estimate expected uplink quality based on the downlink parameters. This helps to choose the most suitable uplink interface and increases the reliablity of the remote monitoring and maintenance solution.
Keywords: AI, Mobile Communication, Link Quality
26/Feb/2020 12:00 - 13:00, WGB-G08, Conference paper rehearsal
Hossein Ajorloo, Marie Curie Research Fellow, Connect@UCC
Title: Using Double Links for Stabilizing mmWave Wireless Channels
Abstract: With the advent of technology, demand for ultra-high bitrate wireless technology is arising. For example, in virtual reality (VR) games, communication between the game console and the headset requires +6 Gbps data-rate. In autonomous vehicles, sharing sensors data requires +10 Gbps data-rate. Millimetre wave (mmWave) is the range of frequencies between 30-300 GHz which can provide such data-rates due to available wide bandwidths. In such frequencies, the signal power is attenuated severely. Steerable directional antennas and beemsteering protocols are used to compensate for this power degradation. But, a small movement causes a sudden drop in data-rate down to 0 bits/s making mmWave channels unstable. To make the channel more stable for aforementioned ultra-high bitrate demanding applications which are affected by frequent blockages and fast movements, we designed and developed a double-link mmWave system on a real testbed available at Vodafone Lab in Technische Universität Dresden (TUD) and tested its efficiency by conducting some experiments. The results will be presented in this talk.
Keywords: mmWave, Channel Stability, Scheduling
19/Feb/2020 12:00 - 13:00, WGB-G08, Tutorial / Skill Share
Cathal Hoare, Lecturer, Computer Science @UCC
Title: Example of Development of a Simple iOS Application
Abstract: This tutorial will introduce the attendees to development tools, processes and methodologies for developing iOS applications. The tutorial will be motivated by a practical example that demonstrates the basics of app development and deployment.
Keywords: iOS Development Example
14/Feb/2020 13:00 - 14:00, BHSC-302, Presentation of a technical piece of work
Sasitharan Balasubramaniam, Director of Research, TSSG
Title: Applications of Molecular Communication and the Internet of Bio-Nano Things
Abstract: The emerging field of molecular communication aims to create a communication systems infrastructure that is constructed using biological components and systems that are found in nature. The development of such communication systems is possible through the combination of nanotechnology as well as synthetic biology, enabling biological cells to be reprogrammed in a similar manner as a computing device. The possibility of constructing biocompatible communication systems using natural biological cells are at the basis of a plethora of applications including, intra-body sensing and actuation as well as targeted drug delivery. The seminar will start with a general introduction to the field of molecular communications, and how the field has shaped over the last decade. The talk will then focus on emerging applications of molecular communications that includes development of digital synthetic gates that can communicate and interconnect into circuits, DNA storage, as well as applications that can potentially prevent infections. The seminar will also briefly touch on the potential cyber-security threats that can emerge from future DNA storage systems. Lastly, the seminar will discuss a new paradigm known as the Internet of Bio-Nano Things, where miniature molecular communication and computing systems can be interconnected to the Internet.
Keywords: Molecular Communications, Internet of Bio-Nano Things, Bio-Cyber Security
05/Feb/2020 12:00 - 13:00, BHSC-302, Review of a domain
Rosane Minghim, Lecturer, UCC
Title: Visual Analytics Applications and Challenges ahead
Abstract: Visual Analytics (VA) is a partner of data analysis necessary in many real applications by helping to find patterns, draw hypotheses and detect relationships in complex data sets. VA integrates visualisation strategies with data science and machine learning approaches in situations where the user must have control over analysis processes. This talk intends to exemplify the employment of visualisation tools in a variety of data analysis applications as well as to discuss the challenges of the field moving forward and in the context of big data.
Keywords: visualization, visual analytics, big data
29/Jan/2020 13:00 - 14:00, BHSC-303, Presentation of a technical piece of work
Ahmed Zahran, Lecturer, MISL@UCC
Title: Empowering Mobile Applications with Accurate Throughput Prediction using Machine Learning
Abstract: The highly dynamic wireless communication environment poses a challenge for many applications, e.g., adaptive multimedia streaming services. Providing accurate throughput prediction can significantly improve the performance of these applications. This talk presents how Machine Learning can be leveraged for accurate throughput prediction in cellular networks using PHY and application layer metrics. We present key architectural components and implementation options, illustrating their advantages and limitations of various implementation options. We also highlight key design choices and investigate their impact on prediction accuracy using real data. Using video streaming as a use case, we illustrate how accurate throughput prediction improves the end user's quality of experience. Finally, we report on lessons learned and provide conclusions which we believe will be useful to practitioners seeking to leverage machine learning in mobile applications.
Keywords: Mobile Networks, Throughput Prediction, machine Learning, Video Streaming
22/Jan/2020 12:00 - 13:00, WGB-G16, Presentation of a technical piece of work
Erica Volta, Research Fellow, University of Genova
Title: Multisensory learning in adaptive interactive systems
Abstract: The main purpose of my work is to investigate multisensory perceptual learning and sensory integration in the design and development of adaptive user interfaces for educational purposes. To this aim, starting from renewed understanding from neuroscience and cognitive science on multisensory perceptual learning and sensory integration, I developed a theoretical computational model for designing multimodal learning technologies that take into account these results. Main theoretical foundations of my research are multisensory perceptual learning theories, research on sensory processing and integration, embodied cognition theories, computational models of non-verbal and emotion communication in full-body movement, and human-computer interaction models. Finally, the case studies I will present are based on two EU ICT-H2020 Projects, "weDRAW" and "TELMI", on which I worked during my PhD.
Keywords: multisensory technology, learning technology, multi sensory perceptual learning
Click here to view presentation
15/Jan/2020 12:00 - 13:00, WGB-G16, Conference paper rehearsal Steven Prestwich, Lecturer, UCC Title: Bayesian Constraint Acquisition
Abstract: Modeling a combinatorial problem is a hard and error-prone task requiring expertise. Constraint acquisition methods can automate this process by learning constraints from examples of solutions, and usually non-solutions. I describe a new statistical approach based on sequential analysis (sequential Bayesian hypothesis testing) that is orders of magnitude faster than existing methods. It is also robust in the sense that it can learn constraints correctly even when the data contain many errors.
Keywords: AI, constraint acquisition, Bayesian
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08/Jan/2020 12:00-13:00, WGB-G16, Presentation of a technical piece of work
Cathal Hoare, Senior Postdoc, ESIPP@UCD
Title: The Dynamic District Information Model
Abstract: Renovation of existing housing stock is essential to tackle the twin challenges of climate change and housing stock shortages that are now common in many large cities. This presentation will present the development of the Dynamic District Information Model as part of the ESIPP project. The model uses linked data protocols to provide a scalable data manager that allows many heterogeneous data sources that are used to model grid energy demand at scales ranging from district to national. The model also seeks to preserve data control for organisations. This talk will describe the ESIPP project, before focussing on the requirements, development and results of the DDIM server.
Keywords: Decision support, Construction, Linked Data, Data integration, Energy Renovation
Date, Time, Place, Talk Type Speaker, Position, Affiliation Title, Abstract, Keywords
12/Dec/2019 13:00-14:00, WGB - 402, Presentation of an initiative on smart cities
Vanessa Pulgarin, Research Support Officer, Cork Smart Gateway @UCC
Title: Cork Smart Gateway - Innovating, creating, connecting
Abstract: The Cork Smart Gateway initiative is composed by members from Cork City Council, Cork County Council, UCC, CIT and Tyndall. It aims to enhance the reputation of Cork as an attractive place to live, work, visit and invest. A place where public infrastructure and public service provision utilise best in class technology solutions and one which allows all stakeholders to participate in decision making and enjoy an enhanced environment. This initiative will compliment and support the already large number of organisations in Cork who are working on smart solutions to improve the physical realm, from energy conservation to open data.
Keywords: Smart cities, test beds, IoT
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06/Dec/2019 13:00-14:00, WGB - 402, Review of a domain & Work in progress
Anne-Marie George, Postdoc, TU Berlin, Efficient Algorithms Group
Title: Liquid Democracy with Ranked Delegations
Abstract: I will first give an introduction to Computational Social Choice and Voting Theory to set the context for discussing Liquid Democracy. Liquid Democracy is a voting framework in which voters can decide to either vote on an issue directly or to delegate their vote to other voters. As such it can be seen as a hybrid between Direct Democracy and Representative Democracy. While Liquid Democracy aims at overcoming certain problems of these two more traditional types of democracy, it brings it's own types of problems with it. As theoretical computer scientists we are interested in formalising desiderata (e.g., that voters cannot manipulate the system) and design mechanisms that enforce these. An analysis of these algorithms for Liquid Democracy typically comes with a graph theoretical flavour. I will present work in progress on the specific case, where voters are allowed to specify several delegation possibilities in form of a ranking.
Keywords: Computational Social Choice, Voting Theory, Liquid Democracy, Vote Delegation, Ordinal Preferences
Click here to view presentation
27/Nov/2019 14:00-15:00, Electronic Engineering building room L3/EDA Lab, Industry Rajeev Jain, Emeritus Professor and Senior Director, Qualcomm Title: Qualcomm AI Research
Abstract: The talk will review main directions in corporate Qualcomm R&D in AI with examples of successful products and genuine technical innovations.
21/Nov/2019 13:00-14:00, WGB - 402, Technical piece of work Dimitrios Zormpas, Marie Curie EDGE Fellow, Tyndall National Institute Title: From ALOHA-based to SYNC-based LoRa communications
Abstract: Due to the ALOHA-style transmission policy of LoRa networks, delivering a large number of packets by a large number of nodes becomes impossible. To avoid bursts of collisions and expedite data collection, we propose scheduling of transmissions in time slots. We provide evidence through extensive experiments that time-slotted synchronous LoRa communications are feasible under different node arrangements.
Keywords: wireless communications, LPWAN, LoRa, Scheduling
07/Nov/2019 13:00-14:00, WGB - 402, Technical piece of work Marc van Dongen, Lecturer, UCC Title: Implementing a CSP Solver
Abstract: This talk presents work about a general-purpose, sound and complete solver for deciding and enumerating the solutions of binary Constraint Satisfaction Problem (CSP) Instances which are provided in extension.
Keywords: Binary CSPs, Solver
31/Oct/2019 13:00-14:00, WGB - 402, Event presentation & recruitment
Bastien Pietropaoli & Milan De Cauwer, Post-docs, Insight@UCC Confirm@UCC
Title: IrlCPC / AIPO - Post-mortem & How we created the problem set
Abstract: In this talk, we will present the results of IrlCPC (Irish Collegiate Programming Contest) and AIPO (All-Ireland Programming Olympiads) that were held at UCC on March 19 2019. We will present how the candidates/teams performed. We will explain how we created a fun but interesting problem set and how our various test cases reflected in the scoreboards. If you would be interested in participating in the writing of the problem set for 2020, we would strongly encourage you to come to this talk.
Keywords: Programming Competition IrlCPC - AIPO
Click here to view presentation
25/Oct/2019 13:00 - 14:00, L2 Electrical and Electronic Engineering Building UCC Dr. Michele Magno, Associate professor, ETH Zurich Title: Smart Sensing in the IoT Era: Machine Learning on Ultra Low Power Microcontrollers
Abstract: Machine Learning (ML) and artificial intelligence are pervading the digital society. Today, even low power embedded systems are incorporating ML, becoming increasingly "smart." This talk gives an overview of ML methods and algorithms to process and extract useful near-sensor information in end-nodes of the "internet-of-things", using low-power microcontrollers ARMCortex-M; Bluetooth low energy SoC, and other low power microcontrollers. The main objective is to show how Machine Learning algorithms can be adapted to the performance constraints and limited resources of low-power microcontrollers both the popular ARM-Cortex-M family and novel Parallel Ultra Low Power (PULP) family based on RISC-V cores. Finally, the talk will introduce an open-source library based on a Fast Artificial neural network, that allows implementing quickly Artificial Neural Network on ARM Cortex-M Family and PULP. The talk will also show with use-case examples, the benefits of energy-efficient ML to achieve self-sustaining smart sensing.
Keywords: AI, Machine Learning, Internet of Things, energy efficiency
17/Oct/2019 13:00-14:00, WGB - 402, Overview of Research Projects
Dirk Pesch, Professor, ADVANCE CRT@UCC
Title: Does the Internet of Things exist only in silos? Challenges for interoperability
Abstract: The Internet of Things, that is connecting the physical world to the Internet to enable smart objects and an unprecedented access to data about our world, has been around for over 20 years, since Kevin Ashton of MIT coined the phrase in 1999. However, much of its promise, both technical and from a commercial perspective, is still to be fulfilled. Recently estimates of the number of IoT devices has been downgraded from 50 billion by 2020 (prediction in 2013) to around 6 - 7 billion by 2022. Why is it that we are not seeing the promise of the Internet of Things envisioned a few years ago? This talk will look one of the issues underlying the much slower than expected growth, the issue of interoperability. Firstly, we will summarise what the internet of things is, then present a brief overview of the different technology components, which will highlight the issues. We then suggest a number of mechanisms that may help to overcome the siloed situation of the current Internet of Things. These include interoperability platforms, software defined infrastructure, interoperable data semantics and the potential of artificial intelligence.
Keywords: IoT, Future of IoT, Interoperability, Software defined infrastructure, Artificial Intelligence
03/Oct/2019 13:00-14:00, WGB - 402, Tutorial / Research Strategies
Klaas-Jan Stol, Lecturer, Lero@UCC
Title: The ABC of Software Engineering Research
Abstract: A variety of research methods and techniques are available to SE researchers, and while several overviews exist, there is consistency neither in the research methods covered nor in the terminology used. Furthermore, research is sometimes critically reviewed for characteristics inherent to the methods. We adopt a taxonomy from the social sciences, termed here the ABC framework for SE research, which offers a holistic view of eight archetypal research strategies. ABC refers to the research goal that strives for generalizability over Actors (A) and precise measurement of their Behavior (B), in a realistic Context (C). The ABC framework uses two dimensions widely considered to be key in research design: the level of obtrusiveness of the research and the generalizability of research findings. We discuss metaphors for each strategy and their inherent limitations and potential strengths. We illustrate these research strategies in two key SE domains, global software engineering and requirements engineering, and apply the framework on a sample of 75 articles. Finally, we discuss six ways in which the framework can advance SE research.
Keywords: Research Strategies Empirical Research
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19/Sept/2019 13:00-14:00, WGB - 402, Workshop rehearsal
Guillaume Escamocher, Post-doc, Insight@UCC
Title: Solving Logic Grid Puzzles with an Algorithm that Imitates Human Behavior
Abstract: I will present in this seminar our entry to the Workshop on Progress Towards the Holy Grail Challenge. The Challenge consists in providing an automated process that can solve the puzzles from the logicgridpuzzles.com website, as well as explain how it got to the solution. The approach used by our algorithm mimics the way a human would try to solve the same problem. Every progress made during the solving process is accompanied by a detailed explanation of our program’s reasoning. Since this reasoning is based on the same heuristics that a human would employ, the user can easily follow the given explanation.
Keywords: Artificial Intelligence Holy Grail of Programming Explanation Logic Grid Puzzle
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12/Sept/2019 13:00-14:00, WGB - 402, Technical piece of work Laura Maye, Lecturer, School of CS & IT Title: Grassroots Radio: Radio for the 21st Century
Abstract: How should radio work for remote and rural communities in light of urbanisation and globalisation, which are diminishing local voices? Grassroots Radio aims to enable community members, through the use of radio as a grassroots peer production platform, to have a voice on local issues, topics, and concerns of value to them. The project is employing an open platform called RootIO: founded in 2013, RootIO can be used by community members to broadcast over FM using any basic phone. Currently, RootIO is deployed in six rural and remote communities across Ireland, including Bere Island and the Islands on the southwest of Ireland, two communities in the Island of Madeira in Portugal, and two communities in the Danube Delta in Romania. In this talk, I will present work completed in the project to date, with the goal of highlighting the RootIO intends to enable communities low-barrier means of communicating at a hyper local level. This will also be accompanied by a demonstration of the platform.
Keywords: Peer-to-peer production Communication Community Rural
06/Sept/2019 12:00-13:00, WGB - 2.26, Overview of research projects Lara Quijano Sánchez, Associate Lecturer, Autónoma University of Madrid Title: The Associate: From Social Group Recommenders to Active Citizen Participation
Abstract: This talk is an account Lara's research career, presenting past, present and future research projects. It contains an overview of several research projects related to i) Recommender systems and the hypothesis that social factors and organizations such as personality and tie strength have a positive impact in group recommendation processes; ii) Social network analysis and decision support systems for client capture applied to social media and financial networks; iii) Applications of data science in policing including VeriPol, an Investigation support tool in the Spanish National Police that allows to identify false reports, and HaterNet, an intelligent system in the Spanish National Office Against Hate Crimes that monitors and visualizes hate speech in Social Media. iv) VioGen: a study of a copycat effect in intimate partner homicides and definition of a risk model, a lesson from Spanish femicides. v) Active citizen participation: explanatory recommendation systems for the improvement and motivation of citizen participation.
Keywords: AI Social Recommender Systems Tie Strength Social Network Analysis Sentiment Analysis Natural Language Processing Predictive Policing E-participation Explainable AI
28/Aug/2019 12:00-13:00, WGB - G09, Conference rehearsal
Brian McCarthy, Ph.D Student, Connect@UCC
Title: OpenCV2X Mode 4: A Simulation Extension for Cellular Vehicular Communication Networks
Abstract: In this work the authors present the first publicly available, open-source simulation model of the Third Generation Partnership Project (3GPP) Release 14 Cellular Vehicle to Everything (C-V2X) standard. The model specifically addresses Mode 4, in which vehicles communicate directly in peer to peer mode using a distributed resource allocation algorithm. Importantly, the model is fully compliant with existing service and application layers already defined by the automotive and standards communities, providing a fully standardised cross-layer communication model spanning application layer based on the ITS-G5 standard to physical layer from the new C-V2X Mode 4 standard. This enables enhancements of the lower layers to support future vehicular use cases.
Keywords: Networks LTE-V C-V2X 3GPP 4G Sensing Based Semi-Persistent Scheduling (SB-SPS)
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21/Aug/2019 12:00-13:00, WGB - G09, Technical piece of work
Eduardo Vyhmeister, Post-doc, Insight@UCC
Title: A combined photovoltaic and novel renewable energy system
Abstract: The productivity of the mining industry in Chile, currently the main driver of Chilean economy, is closely tied to foreign demand for ores. Ore-processing is known for involving energy-intensive processes, such as comminution, concentrating and cathodic processes. As mining activities take place in the arid north of Chile, they are affected by water scarcity. Water shortage has forced the industry to pump desalinated seawater up to mining sites over 2000 m above sea level, further increasing electricity consumption. Given these energy needs, and the fact that electrical energy supply in the north of Chile is based on fossil fuels, it is important to consider the use of renewable energies as environment-friendly and economic alternatives. The aim of this work is to evaluate, by an optimized techno-economic analysis, the use of photovoltaic and a novel wind-based technology to supply at least 10% of the current and the predicted electrical energy requirements of the mining industry in the Antofagasta region. A combination of an optimization problem and technical evaluation was performed using Matlab to obtain the optimal number of solar and wind-based technology units in a case study. Total energy generation from a novel wind-based technology unit is 67,616 MWh/y, corresponding to 14.45$10 6 Nm 3 (1298 t) of hydrogen and 7.41$10 6 Nm 3 (10,323 t) of oxygen after electrolytical transformation. Considering a 65% efficiency of the combined cycle fed with hydrogen and oxygen, 28,133 MWh/y of electrical energy would be obtained. For the cases studied the cost of energy from the combined system was estimated to be between 0.255 US$/kWh and 0.273 US$/kWh, slightly higher than the average energy regional cost. According to the analysis, the renewable energy system could be a sustainable alternative to supply economic green energy to the mining industry in Chile.
Keywords: AI Optimization Energy Hydrogen Electrolysis
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14/Aug/2019 12:00-13:00, WGB - G09, Workshop rehearsal
Andrea Visentin, Ph.D Student, Insight@UCC
Title: Optimal (R,s,S) policy for inventory lot sizing problem with stochastic non-stationary demand
Abstract: We propose an efficient branch-and-bound approach for computing the optimal (R, s, S) policy parameters under non-stationary stochastic demand. In this policy, the inventory position is raised to an order-up-to-level at a review instant when the inventory position is at or below reorder-levels. To the best of our knowledge, no method for computing the optimal policy parameters has been reported in the literature.
Keywords: AI Optimization Inventory Control Stochastic Demand Dynamic Programming
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31/July/2019 12:00-13:00, WGB - G01, Post-viva presentation
Begüm Genç, Post-doc, Confirm@UCC
Title: An approach to robustness in matching problems under ordinal preferences
Abstract: Matching problems under ordinal preferences is a popular field. Some of the well-known matching problems can be listed as Stable Marriage (SM), Stable Roommates (SR), and Kidney exchange problems. There are many variations of these problems being studied under different optimality criteria. In this work, considering the dynamism of the real-world, we propose using a novel 'robustness' notion for these problems. Our proposed notion that captures both robustness and stability constraints is called (a,b)-supermatches. We study (a,b)-supermatches for the SM and the SR. We present some theoretical findings related to the mathematical complexity as well as some empirical results. This talk mainly focuses on motivating the problem, discussing some real world examples, and presenting the outlines of the study.
Keywords: AI Optimization Theoretical Complexity Partially Ordered Sets Meta-heuristic Methods Matching Problems Robustness
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17/July/2019 12:00-13:00, WGB - G01, Post-viva presentation Mesut Kaya, Ph.D Student, Insight@UCC Title: Subprofile Aware Diversification of Recommendations
Abstract: Intent aware diversification methods formulate diversity in terms of coverage and relevance of aspects. The aspects are most commonly defined in terms of item features. We present a new form of intent aware diversification, which we call SPAD (Subprofile Aware Diversification). In SPAD and its variants, the aspects are not item features; they are subprofiles of the user’s profile. Therefore, they are useful even in domains where item features are not available or are of low quality. On several datasets, SPAD and its variants increase both relevance and diversity for even more configurations than other approaches to diversification.
Keywords: AI Recommender Systems Diversity Subprofiles

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The School of Computer Science and Information Technology Seminar Series is organised by a small team of Computer Science Researchers.