This is a brief reflection on the part-time, virtual internship I carried out as part of my first year at the Horizon CDT, with Orbit RRI. ORBIT, the Observatory for Responsible Research and Innovation in ICT is a spin-out company of Oxford and De Montfort Universities resulting from an EPSRC project, and aims to promote a culture of responsible research and innovation in information and communications technology and other areas of technology, research and innovation.
Image (c) Pablo Amargo, New York Times 2019
As a mature student, a virtual internship with a virtual organisation provided an interesting opportunity to reflect on the question, ‘what is an internship?’, by contrast to internships I had carried out earlier in my career, including in the Royal Navy (as an officer cadet) and in the investment bank JPMorganChase. As a Human Resources practitioner, it was also an opportunity to experience life as a ‘virtual new starter’, in common with an increasing number of employees who have been prevented by lockdown from meeting colleagues in person in the office.
The Cambridge Dictionary suggests, for ‘internship’
a period of time during which someone works for a company or organization in order to get experience of a particular type of work
Merriam-Webster gives us the following, for ‘intern’
an advanced student or graduate usually in a professional field (such as medicine or teaching) gaining supervised practical experience (as in a hospital or classroom)
The OED gives us, variously
A student or trainee (originally, a trainee teacher) working, sometimes without pay, in order to gain practical experience in a particular field of employment, or to satisfy requirements for a qualification.
Of or situated on the inside
Of or belonging to the inner nature of something; intrinsic, essential
Which of these best describes the experience, and just how intrinsic and valuable an internship ends up being, will often depend on the terms we can establish with the organisation (with the help of the CDT)!
As is often the case with internships, a project gave mine focus – in this case, a study into the potential effect of ‘RRI intensity level’ (a combination of Technology Readiness Level and relevance to the UN Sustainable Development Goals), based on original Orbit research and its increasingly widely used self-assessment tool. This was an interesting area for study that aligned helpfully with my PhD – should organisations consider different responsible innovation practices for different situations, depending on (for example) the developmental stage of a technology?
To carry out this project, I worked up a plan and objectives with the Orbit management team, carried out a scoping review, and organised research through an online workshop and pre-event questionnaire, with the support of the Orbit team. I sought and was fortunate to receive involvement from three blue-chip organisations who provided engaging speakers for the event to provide a sparking point for discussion.
The event in November 2020 saw 34 delegates from a variety of backgrounds engaging in discussion of the issues relating to responsible innovation assessment at earlier, or later stages of technological development and provided valuable material for my report. In planning and publicising the event through various networks and social media channels, we took care to make the event appealing, and with just the right duration to balance presentations, discussion, and comfort in the context of mid-pandemic ‘webinar fatigue’.
Following the event, I analysed the questionnaire data and workshop transcript to evaluate the overall research question relating to the potential significance of RRI intensity level for responsible innovation activity. My findings highlighted the relevance of the knowledge inputs to responsible innovation assessment alongside tailoring to the object of assessment, and the need to enable ongoing rather than one-off assessments. A presentation back to the management team confirmed that these would usefully inform a wider review of the organisation’s self-assessment methodology.
The following helped make the internship a valuable experience for me:
—making efforts to identify high-profile speakers for an event and early, broad spectrum publicity yielded a strong turnout for an online event
—integrating the participant information sheet and consent questions for research purposes into the online signup workflow for a workshop required care and ethical approval, but minimised barriers for participants while ensuring ethical rigour
—attending and reviewing material for management and Board meetings provided a valuable insight into the organisation’s priorities
For other Centre for Doctoral Training students, I would encourage careful consideration at an early stage, before and while confirming details of internships, of the personal objectives you want to achieve through the experience. If your aim is first-hand experience of what it’s like to work in a particular organisation, you will need as much contact as you can get with your supervisor and relevant teams working there. If interning with a virtual organisation, in a remote work setting, the value you gain from it may depend on how proactive you are in organising regular meetings, attendance at team or higher-level meetings, and potential in-person contacts. It is also valuable to negotiate an achievable project scope that benefits the organisation, utilises your skills, and potentially contributes to your wider PhD study. In this case, things came together and having interned previously, a ‘remote’, ‘virtual’ internship was an interesting and useful experience that contributed to my learning for the PhD.
I am grateful to Serena, Paul, Bernd and Martin on the Orbit team for their support, and to Microsoft, Arm Holdings and BSI for their proactive engagement with the responsible innovation assessment event.
I carried out my internship with Connected Places Catapult (CPC) between February to April 2021 on a full-time basis. I worked as a Cybersecurity Specialist in the Cyber Security Team within the Applied Data and Technology Directorate. I did this during the third year of my PhD – thanks to the efforts of my (super) supervisor who aligned the stars for me after my industry partnership lapsed.
My overall set up:
CPC provided me with ideal conditions that allowed me to get comfortable and take things at my own pace. This meant that I was able to work autonomously, trusted to perform my job to the best of my abilities and proactively look for and choose to work on projects that interested me. To discover projects of interest, I started off by speaking to a lot of people about their work and their vision for the projects to understand if there would be added value by adding in a cybersecurity element. This discovery effort was helped tremendously by my line manager (and some Urban Technology team members) who directed projects my way which made for good introductions and built my confidence.
I had regular catch-ups with the Director and weekly check-ins with my line manager to discuss how I was doing, projects that I found stimulating and my overall progress. Although my line manager worked at CPC three days a week, we quickly built a strong rapport with each other where we could just talk about things on my mind, seek her guidance on various aspects and have a relaxing conversation. She was also very responsive on messaging platforms and emotionally intelligent which meant that I knew she’d be there if I needed her, providing me with a lot of reassurance and making me feel safe in a new, remote environment.
As I was the only member in the Cyber Security team, I collaborated with the Software Engineering team but was primarily hosted by the Urban Technology team during my placement. There were the expected 9.30am morning catch-ups on alternating days that provided me with a valuable opportunity to learn about some of the other projects the team were working on. Team meetings on Mondays were one of my favourite things as it incorporated brainstorming using an online collaborative board and was one of the best applications of Action Research Methodology in a real-world setting that I’ve seen. Being a part of this team and the wider Directorate was really enjoyable and I’m hoping to see everyone in real life once offices re-open and maybe we can find ways to continue this collaboration.
My projects:
I worked on a range of projects with various teams. I mapped cybersecurity stakeholders which was a landscape scanning exercise to record entities within cybersecurity and the various resources they provide to the wider public. I also reviewed existing and potential projects pertaining to Critical National Infrastructure to identify aspects linked to cybersecurity that would be potential sources of collaboration. I fed in to CPC’s response to the governmental consultation on the cybersecurity of 5G Private Networks.
CPC was also engaged with ‘Homes for Healthy Aging’ that involves assistive technologies to help the aging population stay in their homes for longer. I advised on the cybersecurity elements of this project to help incorporate cybersecurity proactively in the early stages of their testbeds.
I produced a detailed report on Cybersecurity of Future Air Mobility and Digital Twins through a consultation with two leading SMEs in the digital twin space. This was a very exciting project with a 2 week turnaround (including the consultation with the SMEs). This report is due to be published on their website in the coming months.
And finally, my passion project which was suggested by the Urban Technology team was designing cybersecurity resources for local authorities and SMEs. This excited me as these segments are cybersecurity poor with limited resources and often struggle to get acquainted with the fundamentals of cybersecurity in a meaningful or practical way. I designed a game which explored privacy within data and two resources exploring the themes of Spear Phishing and Strong Passwords. The aim of this series is for the audiences to explore how cybersecurity is linked to the technologies they invent, implement and utilise for their clients. This would be a great resource page for start-ups and local authorities if it’s developed further.
Overall, I was surprised by how much of an impact remote working has if you’re starting a new position but I think I was very lucky to get an amazing line manager, a wonderful team (who made every effort to pronounce my name correctly and conquered it) and a really wonderful working environment that allowed me to feel connected despite never having visited their offices (which look really cool)!
The Audio Mostly 2019 conference provided me with a relevant and convenient platform through which I could present an outline of my PhD research activity to date. Convenient, and also economical, as this year it was hosted by the University of Nottingham’s Department of Music, but also highly relevant, as many papers from this particular conference’s previous proceedings have presented themselves as being important points of reference though my PhD work to date. Having followed particular research projects of specific relevance to my PhD, Audio Mostly not only presents itself as an appropriate platform for the publication of my work, but also as springboard for other publishing possibilities. This is made evident by many projects being initially presented at Audio Mostly, and then having additional work included within them and then being published and presented as journal articles or at other conferences as the projects progress and evolve.
The published paper presented a synopsis of what I considered as the most pertinent points of my research so far. Rather than presenting specific research data from the results of studies, the paper presented the results of my practical lab-based activities in the development of a working technical prototype, and outlined my methodology and approach, and two proposed study environments, the latter being the subject of currently ongoing and future plans for the development of the project.
All of my supervision team had input on the paper, from proofreading to practical advice and providing some written introductory content. Another academic, involved in one of the proposed studies, also provided some written content specifically relating to the introduction of this specific part of the project. I wrote an initial draft and then sent it to the relevant parties with a specific request on how I thought they may be able to contribute and help with its authorship.
One comment from a particular reviewer proved very useful and centered around the use and definition of a specific acronym. This prompted me to investigate the issue further and, as such, has enabled me to focus my research to a much greater extent and to communicate more effectively the subject of my research to others. It has also provided a much clearer definition of the place of my research within its specific sphere of study.
As well as presenting the paper, I also had the opportunity to demonstrate my technical prototype at the conference. Having been scheduled to present my paper before my demo gave me the perfect opportunity to engage with people whilst demonstrating, answering questions, and continuing discussions as a result of my presentation, and also answering some of these questions practically via the technical demonstration. Generally, the feedback was complimentary and demonstrated an interest in my work, especially in relation to its study through practical application.
Authors whose papers were successfully accepted to the conference have since been invited to contribute to a special edition journal on audio interactivity and to build on the papers initially presented. This seems like a logical next step, as I have since completed some of the proposed studies, and therefore can include the findings and conclusions from these studies in the paper, with a view to formulating a journal article, and providing me with an opportunity to publish the subsequent stage of my PhD research.
On reflection, there are two particular challenges that sprint to mind as a result of this publication and presentation process. The first was the practical task of synthesising a 7000-word paper into a 20-minute presentation. What content to include? What content to leave for discussion? How much detail do I need to include on specific points to get the points across? These were all questions I was asking myself. Another challenge was the problem of presenting ‘live’ research. By the time I actually presented, my research had moved on. I’d changed some of the technology within the prototype and another study opportunity had presented itself which I hadn’t included in my future work section. This led to a bit of back peddling during the presentation, but I did have the opportunity to discuss these points with individuals during my demonstration.
As someone whose journey so far has been straight through education, from school to BSc to MSc and PhD, exposure to life outside of the education bubble has been fairly limited. So, for the internship, I was keen to work in industry!
With the arrival of the pandemic in my third year, there was a fair amount of concern that the opportunity for an internship was sparse. Around the time when I was starting to mildly panic, there was an advertisement for a virtual internship as a UX/UI Designer. The company was a start-up called Footfalls and Heartbeatsand they had developed a technology that meant that knitted yarns could act as physiological sensors. The internship was focussed on one product which was a knee sleeve designed to provide physiological feedback to physiotherapists and athletes during training. The product was still under development, but the prototype looked just like a soft knee brace which weightlifters wear and the data it could measure included the range of motion of the knee and a squat repetition counter; the product had potential to measure velocity but that was an aim for further in the future.
The description seemed tailored to my idea of an ideal internship! It was related to my PhD as my research involves investigating effective ways of conveying brain data to users, and the internship project investigated ways of conveying the physiological data from the knee sleeve to users. The description of the project also suited my interests in sport (and weirdly knees and sewing). I applied and was lucky enough to be accepted. The application process had a few stages. The first stage was the submission of a CV and personal statement. After that, I got asked to do a practical task which involved a UX task of evaluating where I would input a certain aspect of the knee sleeve connection within the app, and a UI task of making high fidelity wireframes on Figma (a design software) based on low fidelity wireframes that were provided. The task had a 5-day deadline and I had no UI experience. To be honest, I had never heard of Figma (or high fidelity wireframes or basically anything to do with UI), so I basically spent all 5 days watching YouTube videos and doing a lot of learning! An interview with a director and data scientist/interface designer followed the practical task and they liked my design (somehow I forgot to tell them that I had only just learned what Figma was)!
There were two of us doing the internship; I was supposed to be designing the desktop app and the other person was to design the mobile and tablet app. We were supervised by the data scientist who interviewed me and he was a talented designer which meant he often took on design roles in the company. He wanted to create an office-like atmosphere even though we were working remotely so the three of us remained on a voice call all day (muted) and piped up when we wanted to discuss anything.
With the product still very much under development and its direction ever-changing, our project changed during every weekly team meeting for the first 4 or 5 weeks. I think this was because the company wasn’t really sure where the product was going and thus they would ask us to do something, like display a certain type of data, only for us to find out the next week that the product couldn’t measure that type of data. The product was supposed to be a business to consumer product and thus we started designing a detailed app fit for end users, but the company’s crowdfunding was unsuccessful so they changed direction to create a business to business product. This meant that our project changed to designing a tablet demo app which showcased what the product could do. They definitely didn’t need two internship people for this project but we made it work!
The most stand-out thing to me about the whole internship was the lack of market research within the team – I don’t think there was any! The product was designed for professional athletes and physiotherapists, yet I really couldn’t see how the two main sources of data it could measure would be useful for either party. I was pretty sure athletes wouldn’t want an app to count their reps when they could do it in their heads and I was pretty sure that physios were happy measuring range of motion with a plastic goniometer (and patients with swollen knees wouldn’t be able to fit on the knee sleeve). I raised these points and the company asked me to speak to my personal physio and his feedback was that he would have no use for the knee sleeve; however, the company decided to carry on with these functions as the main focus of the knee sleeve measurements and I think this was because measuring this data was most achievable in the short term. The whole thing was proper baffling!
However, by the end of the internship we had produced a really nice demo app. I had learned a lot about design in terms of how to design a whole app! We generally started with sketches of designs which then were digitised into low fidelity wireframes and then developed into the high fidelity end version. I also learned about some really helpful tools that designers use such as font identifies and colour pallet finders. We produced a design document which communicated in detail our designs to the engineers who were going to make the app. And I had a very valuable insight into a start-up company which was chaotic yet friendly.
My supervisor on the project was great to work with. He made sure we got the most out of the internship and had fun whilst doing it, and he created a very safe space between the three of us. The company had a very inclusive and supportive atmosphere and they made us feel like part of the team. I think the product has a lot of potential but needs developing further which would mean a later release date. I’m most looking forward to seeing what happens with the knitted technology sensors as they can have many potential applications such as in furniture or shoes.
My studio in Nottingham – Primary – is running a large crowd funding campaign to support developing the building and keeping the arts resilient in Nottingham post the pandemic. They are offering an opportunity to receive artworks, art books, postcards and more in return for support for their developments.
Primary is a local artist-led contemporary visual arts organisation, based at the old Douglas Road Primary School in Radford, Nottingham. They run a free public programme of events and exhibitions, and provide studio spaces to over 50 resident artists. They are a vital arts space for the city. They have worked regularly with Horizon and the Mixed Reality Lab through my work and other collaborations with researchers.
Have you been affected by not seeing your family and friends during Covid-19 restrictions?
Horizon CDT PhD student Mel Wilson (2018 cohort) is looking for participants to help with her research into the effects of Covid-19 on children and young people.
You can find out more details on how to participate here.
For any additional information or queries please feel free to contact Mel at Melanie.Wilson@nottingham.ac.uk.
Within the last decade or so, cyberincidents have made headlines and have become top strategic risk factors for enterprises. These incidents have not spared even high-profile enterprises and government bodies. Despite significant investments in cyberdefense, these entities are still considered soft targets by attackers. It has become clear that the weakest link in the security chain is the human factor.
Negligence is a key aspect of human fallibility. Employees and contractors fail to heed security training, enterprise policies, and applicable laws and regulations, which may be regarded as mere check-the-box exercises at the time of joining the enterprise. Negligent insiders are responsible for 62 percent of cyberincidents.1
Consequently, cybersecurity management can no longer be treated as something distinct from the business or as merely an IT department issue. Senior leadership must enhance the enterprise’s cybersecurity strategy by ensuring a security risk-aware culture and working with employees, contractors, regulators, peer organizations and third-party suppliers to reduce the risk of cyberincidents. Ownership of cybersecurity risk at the top helps secure the trust and confidence of all stakeholders while setting the appropriate tone.2
Intra- vs. Cross-Organizational Cybersecurity Management
The growing number of insider threats, the expanding regulatory requirements to safeguard personal and sensitive data, the complexity of responding to changing attack vectors, and the pressure created by these circumstances demand a shift in cybersecurity management from intraorganizational to cross-organizational. In cross-organizational cybersecurity management, the sharing of threat intelligence is of paramount importance.3 This includes information that can mitigate insider threats, such as background checks to determine credit rating, employment history and criminal convictions. Intraorganizational cybersecurity management, in contrast, caters to a noncollaborative and independent type of security management,4 which leads to a siloed approach and enables insider threats to materialize and expand effortlessly.
The Human Side of Organizations
The human work motivation and management Theory Y proposes an environment in which leading by example extends respect, dignity and inspiration to employees, encouraging them to become ethical and disciplined in accepting and conforming to the enterprise’s security culture.5 In contrast, Theory X takes a cynical view of human nature and leads to an adversarial relationship between leaders and employees.6 Social learning theory suggests that weak leadership is to blame for an apathetic and uncooperative workforce; thus top management should be held accountable for the security culture, ensuring its acceptance by articulating its core ethical values and principles through verbal expressions and reminders.7
Consider the example of a security audit conducted in a Theory X vs. Theory Y enterprise. In a Theory X enterprise, there is a bureaucratic chain of command. The auditor discovers a problem and reports it to the information security officer. The security officer passes the information on to the department head, who, in turn, informs the team leader of the non-compliance issue. The team leader summons the employee or employees closest to the source of the problem. This creates a confrontational environment because the employees may have been unaware that their activities were being audited.
In a Theory Y enterprise, the auditor collaborates with the relevant employees when setting the objectives of the audit and engages them directly when a problem is discovered, thus enabling them to own and address the problem. The auditor’s report still climbs the official ladder, but by the time it arrives at the top, the employees have already taken the appropriate steps to mitigate the issue. Employees appreciate feedback from the top and recognize that the enterprise is not interested in punishing them. Such an up-front approach creates mutual trust, respect and an improved security culture.
Conclusion and Recommendations
Most enterprise leaders are not experts in cybersecurity management, but such expertise is not required to make effective decisions. Leaders should take the following steps:
Train employees properly, and make sure that they are aware of proper procedures. This goes a long way in mitigating cybersecurity risk and improving the enterprise’s security posture.
Integrate human resources management processes into the cybersecurity strategy to identify and address any potential insider threats that could lead to data breaches and result in regulatory fines, damage to business reputation and financial losses. The motive is not always financial gain; it could be vengeance on the part of a disgruntled employee or contractor due to a denied promotion, unfair treatment or poor working conditions. Although malicious acts constitute only 23 percent of all incidents, their impact can be far reaching.8
Create a security culture that belongs to everyone, articulate security goals and monitor the enterprise’s security posture from the outset. An enterprise’s security culture dictates the behavior of its employees and the enterprise’s success in sustaining an adequate security posture.
Ensure that the security culture is inclusive and permeates all parts of the enterprise.
Foster transparency, develop trust and enhance communications in both directions (bottom up and top down), which will facilitate collaborative ideas, better coordination and positive results.
Nevertheless, ownership of cybersecurity risk at the top is key to getting the security culture right and fostering the desired security behaviors.
“AN ENTERPRISE’S SECURITY CULTURE DICTATES THE BEHAVIOR OF ITS EMPLOYEES AND THE ENTERPRISE’S SUCCESS IN SUSTAINING AN ADEQUATE SECURITY POSTURE.”
Author’s Note
The views expressed in this article are the author’s views and do not represent those of the organization or the professional bodies with which he is associated.
Endnotes
Ponemon Institute, 2020 Cost of Insider Threats Global Report, USA, 2020, https://www.proof point.com/us/resources/threat-reports/ 2020-cost-of-insider-threats
Bandura, A.; “Social Cognitive Theory: An Agentic Perspective,” Annual Review of Psychology, vol. 52, February 2001, https://www.annualreviews.org/doi/abs/ 10.1146/annurev.psych.52.1.1
Abiteboul, S.; R. Agrawal; P. Bernstein; M. Carey; S. Ceri; B. Croft; D. DeWitt; M. Franklin; H. Garcia Molina; D. Gawlick; et al.; “The Lowell Database Research Self-Assessment,” Communications of the ACM, vol. 48, iss. 5, May 2005, http://dl.acm.org/citation.cfm?doid= 1060710.1060718
Settanni, G.; F. Skopik; Y. Shovgenya; R. Fiedler; M. Carolan; D. Conroy; K. Boettinger; M. Gall; G. Brost; C. Ponchel; M. Haustein; H. Kaufmann; K. Theuerkauf; P. Olli; “A Collaborative Cyber Incident Management System for European Interconnected Critical Infrastructures,” Journal of Information Security and Applications, vol. 34, part 2, June 2017, p. 166–182, https://www.sciencedirect.com/science/article/abs/pii/S2214212616300576
McGregor, D. M.; Human Side of Enterprise, McGraw-Hill, USA, 1957
The summer school programme I enrolled on during this year’s summer was the 3rd edition of the International Summer School Programme on Artificial Intelligence with the theme Artificial Intelligence from Deep Learning to Data Analytics (AI-DLDA 2020).
The organisers of the program were the University of Udine, Italy, in partnership with Digital Innovation Hub Udine, Italian Association of Computer Vision Pattern Recognition and Machine Learning (CVPL), Artificial Intelligence and Intelligent Systems National Lab, AREA Science Park and District of Digital Technologies ICT regional cluster (DITEDI).
Usually, the AI-DLDA summer school program is held in Udine, Italy, however, following the development of the COVID-19 situation, this year’s edition of the AI-DLDA summer school program was held totally online via an educational platform and it lasted for 5 days starting from Monday 29th June until Friday 3 July 2020. There were about 32 PhD students from over 8 different countries participating in the summer school as well as masters students, researchers from across the world and several industry practitioners from Italian industries and Ministers.
School Structure
The school program was organised and structured into four intensive teaching days with keynote lectures in the morning sessions and practical workshops in the afternoon sessions. The keynote lectures were delivered by 8 different international speakers from top universities and high profile organisations. Both lectures and lab workshop sessions were delivered via a dedicated online classroom.
Key Note Lectures and Workshops
Day 1, Lecture 1:The first keynote lecture delivered was on the theme, Cyber Security and Deep Fake Technology: Current Trends and Perspectives
Deep Fake Technology are multimedia contents which are created or synthetically altered using machine learning generative models. These synthetically derived multimedia contents are popularly termed as ’Deep Fakes’. It was stated that with the current rise in ’Deep Fakes’ and synthetic media content, the historical belief that images, video and audio are reliable records of reality is no longer tenable. The image in figure 1 below shows an example of Deep Fake phenomenon.
The research on Deep Fake technology shows that the deep fake phenomenon is growing rapidly online with the number of fake videos doubling over the past year. It is reported that the increase in deep fakes is sponsored by the growing ubiquity of tools and services that have reduced the barrier and enabled novices to create deep fakes. The machine learning models used in creating or modifying such multimedia content are Generative Adversarial Fusion Networks (GANs). Variants of the techniques include StarGANs and StyleGANs.
Figure 1: Deep Fake Images
The speakers presented their own work which focused on detecting deep fakes by analyzing convolutional traces [5]. In their work they focused on the analysing images of human faces,by trying to detect convolutional traces hidden in those images: a sort of fingerprint left throughout the image generation process. They propose a new Deep fake detection technique based on the Expectation Maximization algorithm. Their method outperformed current methods and proved to be effective in detecting fake images of human faces generated by recent GAN architectures.
This lecture was really insightful for me because I got the opportunity to learn about Generative Adversarial Networks and to understand their architectures and applications in real-world directly from leading researchers.
Day 1, Lecture 2:Petia Radeva from the University of Barcelona gave a lecture on Food Recognition The presentation discussed Uncertainty modeling for food analysis within end-to-end framework. They treated the food recognition problem as a Multi-Task Learning (MTL) problem as identifying foods automatically from different cuisines across the world is challenging due to the problem of uncertainty. The MTL Learning problem is shown in figure 2 below. The presentation introduced aleatoric uncertainty modelling to address the problem of uncertainty and to make the food image recognition model smarter [2].
Figure 2: Food Image Recognition Problem
Day 1, Lecture 3: The final keynote lecture on day 1 focused on Robotics, on the topic: Learning Vision-based, Agile Drone Flight: from Frames to Event Cameras which was delivered by Davide Scaramuzza from University of Zurich.
He presented on several cutting edge research in the field of robotics including Real time, Onboard Computer Vision and Control for Autonomous, Agile Drone Flight [3]. Figure 3 below shows autonomous drone racing from a single flight demonstration.
Figure 3: Autonomous Drone Racing
The presentation also involved an update of their curent research on the open challenges of Computer vision, arguing that the past 60 years of research have been devoted to frame based cameras, which arguably are not good enough. Therefore, proposing event -based cameras as a more efficient and effective alternative as they do not suffer from the problems faced by frame based cameras. [4]
Day 1, Workshop Labs:During the first workshop we had practical introduction to the Pytorch Deep Learning Framework and Google Colab Environment. This was led by Dott. Lorenzo Baraldi from University of Modena and Reggio Emilia.
Day 2, Lecture 1: Prof. Di Stefano, gave a talk on Scene perception and Unlabelled data using Deep Convolutional Neural Networks. His lecture focused on depth estimation by stereo vision and the performance of computer vision models against the bench marked Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) data set. He also discussed novel advancements in the methods used in solving computer vision problems such as Monocular Depth Estimation problem, proposing that this can be solved via Transfer learning. [10].
Day 2, Lecture 2:In addition, Prof. Cavallaro from Queen Mary University of London delivered a lecture on Robust and privacy-preserving multi-modal learning with body cameras.
Lab2 – Part I:Sequence understanding and generation still led by (Dott. Lorenzo Baraldi, University of Modena and Reggio Emilia)
Lab2 – Part II: Focused on Deep reinforcement learning for control (Dott. Matteo Dunnhofer, University of Udine)
Day 3, Lecture 1 keynote lecture focused on Self Supervision Self-supervised Learning: Getting More for Less Out of your CNNs by Prof. Badganov from University of Florence. In his lecture he discussed self-supervised representation learning and self-supervision for niche problems [6].
Day 3 lecture 2was done by keynote speaker, Prof. Samek from Fraunhofer Heinrich Hertz Institute on a hot topic in the field of Artificial Intelligence on Explainable AI: Methods, Applications and Extensions.
The lecture covered an overview of current AI explanation methods and examples of real-world applications of the methods. We learnt from the lecture that AI explanation methods can be divided into four categories namely perturbation based methods, Function based methods, Surrogate based methods and Structure based methods. We learnt that structure-based methods such as Layer-wise Relevance Propagation (LRP) [1] and Deep Taylor Decomposition [7] are to be preferred over function-based methods as they are computationally fast and do not suffer the problems of the other types of methods. Figure 4 shows details of the layer-wise decomposition technique.
Figure 4: Layer-wise Relevance Propagation
Overall, it was concluded that the decision functions of machine learning algorithms are often complex and analyzing them can be difficult. Nevertheless, levering the model’s structure can simplify the explanation problem. [9].
Lab3 – Part I:Lab 3 covered Going Beyond Convolutional Neural Networks for Computer Vision led by Niki Martinel and Rita Pucci from University of Udine
Lab3 – Part II: Going Beyond Convolutional Neural Networks for Computer Vision (Dott. Niki Martinel and Dott.ssa Rita Pucci, University of Udine)
Day 4: The final keynote lecture was done by Prof. Frontoni on Human Behaviour Analysis. This talk concentrated on the study of human behaviours specifically Deep Understanding of shopper behaviours and interactions using computer vision in the retail environment [8]. The presentation showed experiments conducted using different shopping data sets for tackling different retail problems including user interaction classification, person re-identification, weight estimation and human trajectory prediction using multiple store data sets.
The second part of the morning section on Day 4 was open for PhD students to present their research works to participants on the program.
Lab4 – Part I: Machine and Deep Learning for Natural Language Processing(Dott. Giuseppe Serra and Dott.ssa Beatrice Portelli , University of Udine)
Lab4– Part II: Machine and Deep Learning for Natural Language Processing (Dott. Giuseppe Serra and Dott.ssa Beatrice Portelli , University of Udine)
Concluding Remarks
The summer school programme offered us the benefit of interacting directly with world leaders in Artificial Intelligence. The insightful presentations from leading AI experts updated us about the most recent advances in the area of Artificial Intelligence, ranging from deep learning to data analytics right from the comfort of our homes.
The keynote lectures from world leaders provided an in-depth analysis of the state-of-the-art research and covered a large spectrum of current research activities and industrial applications dealing with big data, computer vision, human-computer interaction, robotics, cybersecurity in deep learning and artificial intelligence. Overall, the summer school program was an enlightening and enjoyable learning experience.
References
Sebastian Bach, Alexander Binder, Gr´egoire Montavon, Frederick Klauschen, Klaus-Robert Mu¨ller, and Wojciech Samek. On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation. PloS one, 10(7):e0130140, 2015.
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Davide Falanga, Kevin Kleber, Stefano Mintchev, Dario Floreano, and Davide Scaramuzza. The foldable drone: A morphing quadrotor that can squeeze and fly. IEEE Robotics and Automation Letters, 4(2):209–216, 2018.
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Fourth-year Horizon CDT PhD student Serena Midha is recruiting participants to take part in a research study.
Serena is researching mental workload from a daily life perspective. Serena and her team are aiming to gather a full 5 days of subjective workload levels, as well as data on what activities were being done to generate these ratings. They also want to further their understanding of people’s personal experiences of mental workload.
Participant requirements:
Android Users
Office workers outside of academia
Without clinical history of anxiety or depression
Participants will be offered £75 for participating in the study.
More information about the study can be found here.
