ABSTRACT

Patient care is changing rapidly from a generic to a much more personalized approach. In addition, healthcare systems are shifting their focus from diagnosis to early disease interception and even disease prevention. Such a personalized and preventative approach to healthcare requires disruptive technology solutions to closely monitor one’s health.

This talk will discuss the trends in health care and life science technologies that enable early diagnosis, disease prevention and effective personalized therapies. Examples of such technologies are high-precision medical-quality wearables and connected health sensors, and systems to integrate complex lab analytics and diagnostics into a consumer-friendly package.

BIO

Dr. Peumans holds a Ph.D. in electrical engineering from Princeton University, and a bachelor’s and master’s degree from the Katholieke Universiteit Leuven. Prior to joining imec, Dr. Peumans was a professor of electrical engineering at Stanford University. He is the recipient of an NSF CAREER award and a Belgian-American Educational Foundation honorary fellowship. He currently leads imec’s life science technologies program.

ABSTRACT

The modern revolution in Information Technology (IT) has allowed us to interact in advanced ways with a plethora of technological artefacts. This has led to new shapes of user interfaces (UIs) and styles of interaction. Today’s UIs range from simple mobile input devices with touchscreens and clickable symbols, to home appliances with physical buttons and smart displays, to immersive environments with augmented and virtual reality. The general feeling is that such an increased interactivity is a positive feature. However, differently from the majority of web and software tools, consumer electronics products are sold for a large part based on the functionalities they offer, and an excess of functionalities is likely to lead to less usable products. In addition, consumer electronics products are becoming more and more networked and part of a large ecosystem of connected devices, and today many of the most serious usability problems are caused by the ecosystem as a whole, not by the UIs of the individual products.

Since the majority of end-users of consumer electronics products simply want their tasks done in the best way, a possibility to make such products more usable is the transfer of (part of) the task execution workload from the user to the system, as it is done in so-called smart systems. Then, the possible gain in usability needs to be precisely evaluated. Unfortunately, traditional user evaluation techniques from the Human-Computer Interaction (HCI) field fail to properly measure the usability of consumer electronics products, for which it would be required to observe the end-users conducting their own activities with the products for extended time frames. This is very expensive in terms of the time required to collect the data, strongly limiting the number of user tests that can be performed and, consequently, reducing the reliability of the evaluation techniques. To mitigate the above issues, it is becoming common practice to capture the interactions with UIs during daily use and save them into log files for later analysis using dedicated log studies.

In this talk, after having introduced an HCI perspective over consumer electronics, we analyze the transition that is taking place in the HCI field towards the use of log studies in order to build frameworks for capturing actual user behavior (and not recalled behaviors or subjective impressions) and, consequently, effectively evaluating the usability of any kind of modern interactive device.

BIO

Ibrahim Gedeon is one of the global telecommunications industry’s eminent thought leaders. He has carved out an international career by combining tremendous insight and skill as an applied scientist with a lighthearted and non-conventional approach to leadership. As Chief Technology Officer for TELUS, a leading national telecommunications company in Canada, he is responsible for all technology development and strategy, security, service and network architecture, service delivery and operational support systems, as well as service and network convergence, and network infrastructure strategies and evolution. Under his leadership the TELUS wireless broadband network has become one of the best in the world.

Within industry Ibrahim has held leadership roles and chaired many events in the IEEE and received the IEEE Canada's Outstanding Canadian Engineer Award in 2001. He serves on the board of the Next Generation Mobile Networks Alliance, the Alliance for Telecommunications Industry Solutions and the Institute for Communication Technology Management. He has a Bachelor's degree in Electrical Engineering from the American University of Beirut and a Master’s in Electronics Engineering from Carleton University. In 2010, Ibrahim received a Honourary Doctor of Laws degree from the University of British Columbia. In 2014, he was elected as a Fellow of the Canadian Academy of Engineering (CAE) in recognition of his significant contributions to the field of engineering. He has been named five times to the Global Telecoms Business magazine’s GTB Power 100, a list of the 100 most powerful and influential people in the telecoms industry.

ABSTRACT

With the promise of making life easier, more convenient and fun, consumers are turning to more and more devices to simplify their lives. And yet, consumer technology is really just a mosaic of badly integrated applications. At TELUS, putting customers first isn't just about ease of use. Instead, incorporating security and privacy from the onset, or by design, is an absolute necessity to safeguarding our customers' lives.

ABSTRACT

In recent years machine learning (ML) and Artificial Intelligence (AI) methods have begun to play a more and more enabling role in the sciences and in industry. In particular, the advent of large and/or complex data corpora has given rise to new technological challenges and possibilities.

The talk will connect two topics (1) explainable AI (XAI) and (2) ML applications in sciences (e.g. Medicine and Quantum Chemistry) for gaining new insight.

Specifically I will first introduce XAI methods (such as LRP) that are now readily available and allow for an understanding of the inner workings of nonlinear ML methods ranging from kernel methods to deep learning methods including LSTMs. In particular XAI allows to unmask clever Hans predictors.

Then, ML for Quantum Chemistry is discussed, showing that ML methods can lead to highly useful predictors of quantum mechanical properties of molecules (and materials) reaching quantum chemical accuracies both across chemical compound space and in molecular dynamics simulations. Notably, these ML models do not only speed up computation by several orders of magnitude but can give rise to novel chemical insight.

Finally, I will analyse morpholocal and molecular data for cancer diagnosis; also here highly interesting novel insights can be obtained.

Note that while XAI is used for gaining a better understanding in the sciences, the introduced XAI techniques are readily useful in other application domains and industry as well.

BIO

Klaus-Robert Müller is a Professor for Machine Learning at the department of Computer Science at Technische Universität Berlin and at the Department of Cognitive Science and Engineering at Korea University, Seoul. For 5 years he was director of the Bernstein Center for Neurotechnology, from 2014 I became Co-director of the Berlin Center for Big Data and from 2018 he simultaneously became director of the Berlin Machine Learning Center. In 2012, Klaus-Robert Müller was elected to be a member of the German National Academy of Sciences – Leopoldina, in 2017 of the Berlin Brandenburg Academy of Sciences and also in 2017 as an external scientific member of the Max-Planck Society (MPII). Among other awards in 2014, he received the Berlin Science prize awarded by the governing Mayor of Berlin; in 2017 the Vodafone Innovation Award. Over all, there are more than 40 full time researchers under his direct supervision. His research interest is in the field of machine learning, deep learning and data analysis covering a wide range of theory and numerous scientific (Physics, Chemistry, Neuroscience and Biomedical Engineering) and industrial applications.

ABSTRACT

Robots can be very useful to restore movement abilities of upper and lower limbs. First, they can promote neurorehabilitation as training devices after neurological injuries such as spinal cord injury (SCI), traumatic brain injury and stroke. Second, they can be used as assistive devices to support patients or elders with gait impairments in daily life situations. However, current mechatronic solutions are still too bulky and their sensory technologies and control strategies are still too primitive to allow the correct motion intention. Therefore, they do not provide effective assist-as-needed support and are too inconvenient to use. In this talk I will present new patient-cooperative controllers, intention detection strategies and virtual reality technologies that will improve the rehabilitation of arm movements and gait. I will also present the Cybathlon, which is a new kind of Olympics-style championship, where people with physical disabilities compete against each other at tasks of daily life, with the aid of robotic technologies. The next Cybathlon will take place in Zurich, on May 2nd and 3rd 2020.

ABSTRACT

Cybersecurity is one of the key risks for any business today. Growing attack surface includes amateur threats, such as phishing, and sophisticated distributed denial of service attacks. Prevention is nearly impossible. Given enough time attackers will get in: cost of attack is low and automated probing will find a weakness. Advanced persistent threats show hackers are patient. Defense depends on security analysts who are rare, without training, and with high turnover. AI/ML can help with detection of threat signatures across the corporation and with advisory to security analysts. AI/ML can drive down response times from (hundreds of) hours to seconds and scale analyst effectiveness from 1 or 2 incidents to 1000s. With adequate knowledgebase, it can preserve corporate knowledge and transfer response learnt by AI to new analysts.

To advance the adoption of AI/ML applied to cybersecurity, HPE is partnering with IEEE, SEI, and universities around the world. We are defining an annual grand challenge in applying AI/ML to cybersecurity, comprised of: 1) arena/rodeo to operate the challenge; 2) standards for operational metrics (preventing attacks; ensuring AI performs as expected); training data; workflows integrating AI into current processes; and human-machine teaming model; 3) knowledgebase for network traffic capture; policy for AI/ML configuration; AI strategies; execution environment; and capturing security analyst knowledge. Over years, grand challenge will result in a repository of training data, sharing data logs and attack details. As a result it will increase adoption of AI/ML in cybersecurity and reduce attacks.

BIO

Dejan Milojicic is a distinguished technologist at Hewlett Packard Labs, Palo Alto, CA (1998-) leading system software teams over 4 continents and projects with budgets of hundreds US$M. He worked at the OSF Research Institute in Cambridge, MA and at the Mihajlo Pupin Institute in Belgrade, Serbia. Milojicic received his PhD from Kaiserslautern University, Germany; and his MSc/BSc from Belgrade University, Serbia. He was a technical director of the Open Cirrus Cloud Computing Testbed, with academic, industrial and government sites in the US, Europe, and Asia. He has published 2 books and 180 papers; he has 37 granted patents. He is an IEEE Fellow (2010) and ACM Distinguished Engineer (2008). Milojicic was on 8 PhD thesis committees and taught Cloud management course at SJSU. As president of the IEEE Computer Society (2014), he started Technology Predictions, the top viewed CS news. As the industry engagement chair, he started IEEE Infrastructure’18 conference.

• Consumer Behavior on Social Networks
• Consumers and Digital Marketing (E-Commerce and Mobile APP)
• Consumers in the Era of Connected Objects

• Wireless Technologies
• AI and Chatbots will impact the workforces?
• Connected Clouds (Public, Private, Hybrid)
• Blockchain applications beyond cryptocurrency
• Data is key to companies being able to make good decisions about products, services, employees, strategy and more
• Compliance with Europe’s General Data Protection Regulation (GDPR)
• AR Yes, VR (Still)
• IoT, AI, Machine Learning and Edge are deeply interconnected
• ITaaS allows scalability for the latest technology
• IT Security

Standardization

Testing

complexity management

In the consumer goods industry, manufacturers are generally divided into "white goods" (particularly household appliances), "brown goods" (consumer electronics),"gray goods" (Information and communication technology) and in Germany also in so-called "red goods" (thermal technology). These companies are geared towards the specific needs of their end users (B2C), however, they also need to consider the specific interests of their retailers (B2B). Trendsetting product innovations with great application benefits and tailor-made functionality are topics that help them penetrate the market. The complexity management plays an important role in this process. Only those who rapidly build product and production architectures in line with the market needs and establish at the same time an agile organization can withstand the high pressure of global competition.