Samsung Research America’s AI Center is focused on several areas encompassing machine learning, computer vision, and natural language. This talk will describe recent work from the Creative AI lab which focuses on developing the core technology to support applications in creative domains such as music generation. This includes new self-supervised methods for 1) understanding music in a manner that correlates with human perception and 2) enabling an embodied agent to generate action sequences allowing it to achieve a task grounded in music.

Understanding human movement is essential for the better design of human-machine interface. Researchers have made great efforts to develop cheap and easy-to-use wearable sensors and algorithms to achieve this goal. In this talk, I will present my previous works in this field, including movement intention detection and perception and cognition recognition using bio-signals collected by wearable sensors. First, I will talk about detection of arm and leg movement intention using ForceMyography, ElectroMyography, and Inertial Measurement Units.  The applications of this line of studies are for human-machine interaction, prosthetic limb (robotic arm) control, and rehabilitation and assistive device. Second, I will discuss how to measure visual perception and cognition of surgeons using eye-tracking technology. Results gained can help us to assess mental workloads, team cognition of surgical team, and help to detect the moment of performance difficulty under AR/VR environment.

For decades, our collective view of how software is built was strongly influenced by unscientific, non-empirical "best practices" and experience reports. In recent years, empirical research has invalidated many common beliefs about software development, and generated many new theories, concepts, tools and techniques. In this talk, Dr. Ralph will summarize over a decade of empirical research at the intersection of software engineering and project management, including seminal research on decision-making, waste-reduction, software engineering success, product backlogs, cognitive biases in requirements engineering, and surviving disruption.

Public art festivals provide a unique opportunity for Human-Computer

Interaction (HCI) research. They attract a diverse population interested

in engaging in novel experiences, foster a lively crowd dynamic, provide

a variety of interesting public settings, and can be a remarkably

efficient means of collecting participant data. Yet pitfalls abound: for

example, the desire to provide a good experience can trump scientific

objectives, onsite testing can be difficult, and small mishaps can have

disastrous consequences for data collection. This talk reviews six

studies conducted at art festivals, highlighting successes and failures

in each, and then offers a set of hard-won recommendations, useful for

researchers who might consider a similar approach: have concrete

research objectives as well as higher level interests, use agile

approaches to system building, balance audience engagement and feature

simplicity, articulate backup plans when things go wrong but remain

nimble, consider research as spectacle.

Over the past two decades advances in the field of ocean technology have led to the exponential increase in volumes of oceanographic data. Acoustic remote sensing, autonomous surface and underwater platforms, in-situ sensor platforms, and vessel-deployed instruments are now capable of collecting extremely large, diverse and interconnected oceanographic data sets for a wide range of applications. The technology has reached the state where ocean data are being generated at a rate faster than can be assessed and interpreted using traditional methods. The need for development of analytical tools to process these data sets, coupled with the skilled individuals to undertake these analyses is now paramount.

We present case study examples of applied research activities in the field of integrated ocean mapping at the Nova Scotia Community College (NSCC) where analytical procedures are under development to handle, process and deliver results from large oceanographic data sets in support of ocean sector stakeholders. NSCC works closely with regional and Canadian-based companies, federal and provincial government departments, and other academic institutions to provide innovative applied research solutions in the area of ocean technology and ocean analytics. An overview of various habitat mapping approaches will be provided to illustrate advances in this field of research.

Join Engineers Nova Scotia for this new PD Session which will feature several ethics and safety related case studies. This interactive session will allow participants the opportunity to discuss and explore some common ethical issues encountered today.

The human brain is one of the most complicated biological systems in the world. The brain activities measured by various signals such as electroencephalogram (EEG), electrocorticogram (ECoG), and functional magnetic resonance imaging (fMRI) provide avenues that can help understand the underlying mechanisms of the brain as well as diagnosis brain disorders and the related diseases. However, without the proper techniques to analyze the brain signals, they are of limited value. In this talk, I will discuss the challenges in brain signal analysis and emphasize the role of machine learning techniques in feature extraction and classification of EEG/ECoG signals. From an algorithmic perspective, I will present multitask learning techniques that aim to discover the common structure that is shared across the brain signals from different subjects to improve the learning performances. In addition, I will also discuss some theoretical aspects of multitask learning, and address two fundamental questions: First, compared with single-task learning, why multitask learning can succeed? Second, under what conditions multitask learning can succeed?

Ethics is everywhere. We need to get our research plans approved by ethics boards, we now do ethical AI (based on ethics codes), the European Union makes data-science projects have an independent ethics advisor, and management now engages in ethical leadership. 

    Why is this, and what does ethics actually mean in the context of data science? In this talk, I will give a hands-on introduction to important schools of thought and questions from this fascinating subfield of philosophy. The “hands-on” means that we will, interactively, go through a number of real-life case studies from data science, study what values and rights are at stake and how they were and can be disregarded, respected, protected, and questioned.   

    In the second part of the talk, I will focus on a specific application of ethical questioning: the analysis of vehicle/human trajectory data, and a specific value: privacy. I will discuss two recent examples of the analysis of such data – the New York City taxi rides dataset, and the use of data from the maritime Automatic Information System (AIS) for mapping refugee movements on the Mediterranean Sea. The examples will illustrate a feature that engineers often find very difficult to deal with: the tension between allowing for different (and often mutually incompatible) ethical stances on the one hand, and requiring adherence to certain ethical norms that are considered non-negotiable on the other hand. But these examples will also illustrate why we should care, why it is intellectually stimulating to think about ethics, and why doing so requires us to also question ethics or “ethical” codes, boards and advisors, and certainly leaders.

In this talk, I will present two contrasting approaches to building generative models for audio with deep learning techniques:

1) In the TimbreTron system (developed in collaboration with students and faculty at U of Toronto and Vector), we learn to manipulate the timbre of a sound sample from one instrument to match that of another while preserving musical content such as pitch and rhythm. I will describe how we do this by combining a CycleGAN architecture, appropriate spectral representations and a conditional WaveNet synthesizer.

2) In PerformanceRNN (developed in collaboration with researchers at Google, and with subsequent developments in collaboration with undergraduate students at Dalhousie FCS), we work directly with MIDI data rather than raw audio, which allows us to treat music generation as language-modeling problem. We use a conditional LSTM to generate solo piano music based on a dataset of human performances.

I will also provide overviews as needed throughout the talk of concepts related both to audio generation (e.g. "What is MIDI? What are spectral representations?") as well as to deep learning techniques (e.g. "What is CycleGAN?”).

Data science is creating novel means to study the complexity of our societies and to measure, understand and predict social phenomena. My seminar gives an overview of recent research at the Knowledge Discovery (KDD) Lab in Pisa within the SoBigData.eu research infrastructure, targeted at explaining the effects of data and algorithmic bias in different domains, using both data-driven and model-driven arguments. 

First, I introduce a model showing how algorithmic bias instilled in an opinion diffusion process artificially yields increased polarisation, fragmentation and instability in a population. Second, I focus on the urgent open challenge of how to construct meaningful explanations of opaque AI/ML black-box decision systems, introducing the local-to-global framework for the explanation of ML classifiers.

The two cases show how the combination of data-driven and model-driven interdisciplinary research has a huge potential to shed new light on complex phenomena like discrimination and polarisation, as well as to explain how decision making black-boxes, both human and artificial, actually work. 

I conclude with an account of the open data science paradigm pursued in SoBigData.eu Research Infrastructure and its importance for interdisciplinary data driven science that impacts societal challenges.

We will be discussing how drones or UAVs have become an important tool for engineering purposes. Their versatility has made it possible to be implemented in almost every field. Applications go from construction, inspections, asset management, surveying, energy audits, and more. Everyday there are new uses in this ever expanding field. Join us as we discuss how they can be used and applied to a variety of engineering environments. 

Are you short on time to start from scratch to use deep learning to solve complex problems involving topics like neural networks and reinforcement learning? If yes, then this is the workshop to help you.

This workshop is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow.

The aim of this talk is to present research results of the Complex Event Recognition lab (http://cer.iit.demokritos.gr/) of NCSR Demokritos (Athens, Greece), focusing on maritime applications. Maritime monitoring systems support safe shipping, through real-time detection of dangerous, suspicious and illegal vessel activities. We have been developing a complex event recognition system for maritime monitoring in the Event Calculus, allowing both for verification and real-time performance. The basic system is being developed through collaboration with domain experts, constructing effective patterns of maritime activity. In order to refine these patterns, we have developed online, relational learning techniques and applied them on AIS data streams. More recently, we have also been developing complex event forecasting techniques, allowing for predictive maritime analytics. In the talk, we will show results of our techniques on real AIS streams, covering large geographical areas.

The Faculty of Arts and Social Sciences, in cooperation with the Faculty of Medicine and the Faculty of Computer Science, is pleased to invite you to a special panel event to introduce the three Donald Hill Family Postdoctoral Fellows.Their panel will discuss their research intentions and generate stimulating dialogue about the impact of emerging technology on society. 

Please join us for this panel event. All are welcome! 

Reception to follow.