First Year Employability Lectures 2017-2018

This year the Employability Lectures Series runs every Monday morning from 11:00 to 12:00 in room H116.

 

Date and timeSpeakerDetails
09/10/2017Prof. Balbir Barn (Middlesex University)Computer Science at Middlesex: Reasons to be cheerful.

In this talk, I will discuss computer science as an important subject and a career, identifying some important industrial trends and how you can maximise your educational experience at Middlesex. I will try and counter some of the issues around employability and what you can do. Finally, I will outline some of the research being conducted by your tutors, how it fits in with the taught programmes and how you can also participate in the co-design of your own learning.
16/10/2017Stevan Zivanovic (BTTB Ltd)What it takes to be a Software Tester

Stevan will describe how he became involved in software testing and why he has found it such an exciting area for over 25 years. We will also explore what software testing is and why it is such a large part of the IT industry.
23/10/2017Dr. Bob Fields (Middlesex University)Generating Insights using Mobile Technology

In this talk I will describe the Insight project, a collaboration between CS, Product Design, and Psychology, that has resulted in research tools for collecting and analysing research data. Insight began as a project to collect rich, near-real-time data from participants in a study focused on mental health, using mobile phone apps and wearable technology. Study participants can be sampled many times over the course of a study, and the data uploaded to a server for later analysis. The tools are being used in a number of studies that go beyond the original focus of mental health. In the talk, I will highlight how projects like Insight can present Computer Scientists some of the most interesting opportunities that arise when working with such a range of different specialists – including designers, psychologists, architects, and healthcare professionals. Finding out about how other experts work and think, and how users make sense of the systems we develop, can be among the most fascinating challenges open to us.
30/10/2017Prof. Franco Raimondi (Middlesex University)Avoiding errors in complex and critical systems.

An increasing large number of tasks are delegated to computer systems in which software and hardware interact: think of autopilots in modern planes, autonomous cars, medical devices, etc. However, these systems are typically built by humans and are therefore subject to human errors, not only in terms of "software bugs", but also in terms of design mistakes. In this talk I will present some approaches that help in the construction of more robust systems, ranging from testing to model checking, presenting some of my work in the area.
06/11/2017Enrico Scalavino (Google)Designing and Building Products At Google.

The aim of this talk is to give an idea of what Google's approach to product design and engineering looks like, who the people involved are, what their roles are and how they interact with each other.
13/11/2017Michele Sama (Gluru)From UX/UI to UX/AI: educating businesses to trade control for predictive automation

The opposable thumb has been driving the evolution of human civilisation from its dawn. From cutlery to smartphones being able to "handle" tools gives us a sense of being in control and being productive. Software is no different: UIs have been designed for decades to give users manual control. With the commercialisation of machine learning being in control is no longer necessary and delegating a predictive model is often more efficient. In this talk I will guide you through the journey that businesses have to undertake to trade manual control in favour of predictive automation.
20/11/2017Prof. Xiaohong Gao (Middlesex University)Deep machine learning, the state of the art

In this talk, the introduction of deep learning techniques will be given, in particular with regard to their application and prosperity, in the fields of computer vision and natural language processing.
27/11/2017Tomas Petricek (Alan Turing Institute)Building Better Data Science Tools (while avoiding a real world job!)

Data science is hard. You need to learn how to write web scrapers, analyse and clean messy data, design statistical models, build interactive web-based visualizations and many more. Can better programming tools reduce the vast number of different technologies that one needs to learn? In this talk, I will present some of my work on making data science easier for professional developers (https://fslab.org), but also for journalists (https://thegamma.net). Along the way, I will talk about my personal story of how I got to work on these projects while mostly remaining an independent open-source contributor – as a PhD student in Cambridge, intern in a New York hedge fund, contractor for Microsoft Research and recipient of a grant from Google.
04/12/2017Prof. Rajagopal Nagarajan (Middlesex University)Everything You Always Wanted to Know About Quantum Cryptography*
(*But Were Afraid to Ask)


The novel field of quantum computing and quantum information has gathered significant impetus in the last few years, and it has the potential to radically impact the future of information technology. While the successful construction of a large-scale quantum computer may be some years away, secure communication involving quantum cryptography has already been demonstrated in several scenarios and practical equipment for quantum cryptography is commercially available. In this talk, I shall introduce a few basic concepts of quantum information processing, give an overview of quantum cryptography and discuss state-of-the-art.
11/12/2017Rosie Hyde (Pirum Systems Ltd)How to Survive the Job Market

Finding a job after University is a maze, in this presentation I will talk about how I made my way through it and give tips on making the whole process easier. I will also discuss what it’s like to work as a graduate and what I do in my graduate job.
08/01/2018No LectureNo Lecture
15/01/2018Dr. Simon Attfield
(Middlesex University)
Exploring Possible Futures: Human Computer Interaction and Interaction Design

In this talk I will give a short history my career, which has been a winding road indeed, and my research in the area of Human Computer Interaction, Interaction Design, Visualisation and Sensemaking. Through this I will discuss the multidisciplinary nature of Human Computer Interaction and how these areas have developed. These areas have lively career paths in both academia and industry for the interested student. I will try to give a sense of what each of these looks like and how an interested student might move in this direction from an IT related degree at Middlesex University. And if I can, I will unleash a few pearls of wisdom!
22/01/2018Prof. Richard Bornat (Middlesex University)Learn to program (for Really Good Jobs)

I've lived through five decades of computing innovation, from the time
when programs were written in assembly code and every manufacturer had their own programming language(s), then through the development of
machine-independent programming languages, through various times when programming was said to be out of date, through the time when it became a branch of engineering, into the time when the best jobs go to those that can program and think about how programming can be made more efficient. All that time there has been lots of work for programmers. If
you can learn to program, you'll do all right. If you find it hard to begin with, don't worry: so does almost everyone else. There are hundreds or thousands of ways to go forward.
29/01/2018Andrea Magnorsky (Goodlord)Programming over time. How writting code has changed and what I wish I'd known

Over the last 15 years writting code professionally has changed a lot in the surface, but has it? What are the skills that stick around and what are the things that quickly become obsolete
05/02/2018Dr. David Windridge (Middlesex University)Machine Learning and its Many Applications

As Associate Professor in Data Science I have research interests in topics like automated classification, autonomous vehicles, cognitive systems and computer vision, as well as interdisciplinary interests ranging across areas as diverse as psychological modelling and proteomic classification. I have consequently worked with a diverse range of industries in my research career including manufacturing, automotive, healthcare, media and defence. At the centre of all of these is the subject of machine learning; the science of getting machines to learn like humans. It will be the argument of my talk that, in employment terms, there is essentially nowhere now that machine learning cannot be applied, particularly given that, in many areas, machine learning can outperform humans at specific tasks. The job of Data Scientist will therefore be something that will be in enormous demand in the coming years, with companies increasingly requiring machine learning for imaginative and generalised use of the data they collect to e.g. provide bespoke services tailored to the individual client. It will therefore be the aim of my talk to give an overview of, and introduction to, machine learning and explore some of its applications in order to give a flavour of its diversity and relevance to contemporary corporate/societal needs.
12/02/2018Russell Weetch (SmXi)Blockchain and the opprtunities it presents

We will be looking at Blockchain technology, what it is, how it works, what the employment opportunities are and what you need to make the most of them.
19/02/2018Prof. William Wong (Middlesex University)Real People, Real Problems -- The role of Human-Computer Interaction in the invention of new technologies.. or why you should study HCI if you want to be a technology entrepreneur

In this lecture, we introduce the idea of “technology entrepreneurs” - people who can see an opportunity and figure out how technology can be used to turn it into business profit. If we wish to become technology entrepreneurs, we look at what we might want to know about how opportunities are created by real people in the real world, working on or around real problems. Real problems often have many inter-related causes that require knowledge from different areas of expertise. Human-computer interaction is one of those subjects that brings together different sets of expertise to find technology solutions that work for people. We will look at examples from 10 years ago that investigated how we might develop the future air traffic controller workstation, and now, how we are addressing multi-disciplinary problem of criminal intelligence analysis using a HCI-based multi-disciplinary approach to develop a technology to address the multi-faceted problem of making sense of data. We will look at how the methods of HCI combine different areas of study to facilitate your ability to see innovative ways of fixing the problem.
26/02/2018Prof. Franco Raimondi (Middlesex University)A very gentle introduction to blockchains.
05/03/2018James Sadler & Scott Willson (Jammoo)Paid development opportunities for Students

The lecture will be about Jammoo, a digital studio specialising in e-learning and programming. We will be giving students opportunities that will help enhance their future in the digital world. Offering paid portfolio & part time work which will not only give them a great stance for future employment but a chance to work with some amazing brands, such as The BBC, Waitrose, Barclays and First News.
12/03/2018Armando Pesenti Gritti (EngageHub)From Student to Software Engineer: 5 lessons learned so far

When you are starting your career in any field, you probably have high hopes but don’t really know what to expect. In this talk, I will discuss what I’ve learned so far from my experience of transition into work life by presenting 5 serious (but common among students) misconceptions I had to overcome about being a Software Engineer.
19/03/2018Nicholas Fitton (Post-Quantum)[CANCELLED]

Leveraging Ethereum - When to not use the blockchain

Is the blockchain actually useful? In this lecture we will be discussing when and where to use the blockchain, how to write an Ethereum Smart Contract and how to squeeze as much out of the blockchain as you can.
26/03/2018Easter Break
09/04/2018Yuan Yuan Zhang (UCL)Hyper-Heuristics and Optimisation for Early Lifecycle Software Engineering

Search Based Software Engineering (SBSE) uses search based optimisation to seek optimal or near optimal solutions to complex problems in software engineering. It is well adapted to problems that involve multiple, competing and conflicting objectives and can handle partial, noisy and even inaccurate data. This generality and flexibility have made SBSE very popular as a technique for finding effective and efficient solutions to challenging software engineering problems. SBSE can also be used to yield insight into the structure and character of the software engineering problem, by exploring "what if" questions and providing sensitivity analyses. Such decision support is crucial at the early stages of development where any decisions taken will have the longest lasting and most profound consequences. This talk will describe recent progress working on SBSE techniques, particular hyper-heuristics and optimisation for these critical early life cycle activities, focusing on Requirements Selection and Software Project Management.