General Data Protection Regulation is about to be applicable as from 25 May 2018. Its long-arm teritorrial reach brings obligations not only to EU establishements, but to US based companies as well. Global connection through internet especially underlines the likelihood of such broad application and it will impact US businesses.One of the prerequisits for safe transfer of data between the EU and US is already accomplished by the EU-US Privacy Shield agreement. The European Commission has considered this agreement as providing adequate guarantees for transfer of data. Under Privacy Shield scheme companies may self-certify and adhere to principles stated therein. Yet, there is still less then 3000 companies in the US participating in the Privacy Shield. But GDPR safeguards have still to be followed. Below, we shall look at some of the most profound aspects of compliance with GDPR for the US (non-EU) based companies.
Data protection officer
Although it is not obligatory pursuant the GDPR, it is advisable that a company appoints a data protection officer (‘DPO’) or designate that role to a specific position in the company. DPOcan also be externally appointed. There may be a single DPO for several companies or several persons designated with DPO role in one company. The position needs not necessarily to follow such a title, but it may be a privacy officer, compliance officer, etc. Such person should possess expert knowledge about the GDPR and data privacy, and may have legal, technical or similar background. GDPR was not specific as to requirements of that person, apart from possesing expert knowledge. Role of DPO is toinform, monitor, advise, the controller, processor or employees, to cooperate with supervisory authority, provide training of staff, help in performing data protection impact assesment.
Data Protection Impact Assesment
The further step that companies affected by the GDPR including US companies should do in order to evaluate the risk of data breach is to perform a data protection impact assesment (‘DPIA’). DPIA is a thorough overview of the processes of the company, and can be done with the help of data protection officer. It may include a form or a template with a series of questions, which have to be answered for each processing activity. DPIA has to be detailed and cover all operations in the company. The function of DPIA is to predict situations in which data breaches may occur, and which include processing of private data. DPIA should contain, pursuant to Article 35 of the GDPR, a systematic description of the envisaged processing operations and the purposes of the processing, an assessment of the necessity and proportionality of the processing operations in relation to the purposes, an assessment of the risks to the rights and freedoms of data subjects referred to in paragraph, the measures envisaged to address the risks, including safeguards and security measures. DPIA is a very useful way of showing compliance and it is also a tool that would help to company at the first place, to have an overview of processing activities and an indication of where a breach could happen.
A US company (non-EU based company) has to appoint an EU representative if its businessrelates to offering of goods or services to natural persons in the EU, including even free goods or services, or when processing is related to monitoring of behaviour of data subjects in the EU. Behaviour may include monitoring internet activity of data subjects in order to evaluate or predict her or his personal preferences, behaviors and attitudes. EU representative is not obligatory when the processing is occasional or does not include processing on a large scale of special categories of data such as genetic data, biometric data, data concerning health, ethnic origin, political opinions, etc. and when it is unlikely to result in a risk to the rights and freedoms of natural persons. However, given that the exceptions from the duty of designation of EU representative are pretty vague, in most cases companies whose operations are not neglectable towards persons in the EU would have to appoint a reprsentative. Location of such representative would be in one of the EU Member states where the data subjects are located. Representative should perform its tasks according to the mandate received from the controller or processor, including cooperating with the competent supervisory authorities regarding any action taken to ensure compliance with this Regulation, and he/she is also liable and subject to enforcement in case of non-compliance.
GDPR is overwhelmed with one key word of respect the privacy:consent. If companies wish to process data of natural persons that are in the EU, they must first obtain consent to do that. Consent must be freely given, informed, specific and unambigous.
Freely givenconsent presupposes that data subject must not feel pressured, or urged to consent, or subjected to non-negotiable terms. Consent is not considered as freely given if the data subject has no genuine or free choice.Data subject must not feel reluctant to refuse consent fearing that such refusal will bring detrimental effect to him/her. If the consent is preformulated by the controller, which is usually the case, the language of the consent must be clear and plain and easily understandable for the data subject. Further, if there are several purposes for the processing of certain data, consent must be given for every purpose separately. Consent must be specific and not abstract or vague. Silence, pre-ticked boxes or inactivity is not to be considered as consent under GDPR.
Informed consent means that data subject must know what the consent is for. He/she must be informed about what the consent will bring and there must not be any unknown or undeterminedissues. It is a duty of controller to inform data subject about scope and purpose of consent, and such information must be in clear and plain language. But, one must be careful that, as today in the world of fast moving technologies we face overflow of consentsa person has to give in short period of time, there may be an occurrence of ‘click fatigue 1’, which would result in persons not reading the information about the consent and clicking routinely without any thorough thinking. So, the controllers would have to make, by their technical design, such form of a consent, that would make the person read and understand his or her consent. It could be a combination of yes and no questions, changing of place of ticking boxes, visually appealing text accompanying consent, etc.
Consent must be unambiguous, or clearly given. There must not be space for interpretation whether consent is given for certain purpose or not. As to the form of the consent, it may be by ticking a box, choosing technical settings and similar (Recital 32 GDPR).
Data subject gives his consent for the processing of his personal data. However, companies have to bear in mind that data concept in the EU is broadly understood, and that it includes all personally identifiable information (PII), ranging from obvious data such as name and postal address, to less obvious data, but still PII covered by GDPR, such as IP address . On the other hand the IP address is not that clearly considered as PII in the US. In that regard, the protection in the US must be stricter, obliging US based companies to also apply broader EU standards.
Privacy by design implemented
Privacy by design is a concept which brings together the legal requirements and technical measures. It is a nice and smooth way of incorporating law into technical structure of business. Privacy by design, if applied properly at the outset, shall ensure the compliance with the GDPR requirements. It should point out to principles of data minimisation, where only data which is necesssary should be processed, storage limitation, which would provide for a periodic overview of storage and automatic erasure of data no longer necessary.
One of the ways of showing compliance through the privacy by design is ‘pseudonymisation’. Pseudonymization is, according to GDPR, referred to as the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information. Such additional information must be kept separately, so that it cannot be connected to identified or identifiable natural person.Pseudonymisation is not anonymisation and should not be mixed with it. Anonymisation is a technique which results in irreversible deidentification, and since it completely disables identification it is not subject of data protection under GDPR. Pseudonymisation only reduces the likability of a dataset with the original identity of a data subject, and is accordingly a useful security measure .
Binding corporate rules
Binding corporate rules (‘BCR’) include set of principles, procedures andpersonal data protection policies as well as a binding clause adopted by the company and approved by competent supervisory authority. Adopting binding corporate rules is not a simple process but means being on a safe track. It is one of the safeguards envisaged by the GDPR. BCR should include according to Article 47 of the GDPR, the structure and contact details of company, categories of personal data, the type of processing and its purposes, application of general data protection principles (such as purpose limitation, data minimisation, limited storage periods, data quality, data protection by design and by default, legal basis for processing, processing of special categories of personal data, ..), rights of data subjects, the tasks of data protection officer, complaint procedures, mechanisms for reporting to the competent supervisory authority, appropriate data protection training to personnel, indication that BCR are legally binding. BCR should additionally be accompanied with privacy policies, guidelines for employees, data protection audit plan, examples of the training program, description of the internal complaint system, security policy, certification process to make sure that all new IT applications processing data are compliant with BCR, job description of data protection officers or other persons in charge of data protection in the company.
Make your compliance visible
Well, if your company has performed all of the above, it has to make it visible. Companies, that are covered with the GDPR, not only do they have to comply, they have to show that they comply. GDPR puts an obligation on controllers to demonstrate their compliance.
From the first contact with the controller, the website must give the impression of compliance. BCR, privacy policies,DPO contact details must be visible in order that data subject may address him in case of data risk or breach. EU representative’s name and contact must be put forward in order to be accessible by the supervisory authority in the EU. Contact form for data subjects with options for access, right to object, erasure, rectification, restriction, should be there.Organisational chart of the company, flow of data transfer demonstrated by data flow mapp.These are only some of the most imporant features that have to be followed.
Non-compliance is a very costly adventure. The adventure that businesses will try to avoid. With systematic planning and duly analysing the necessity of compliance with GDPR, and with clearly defined processes, US companies can put many benefits for the business and attract and encourage data subjects in the EU to freely entrust their datato them. This is a thorough process, but worth accomplishing.
 Article 29 Working Party Guidelines on consent,p. 17
 According to judgment of the Court of Justice of the EU of 19 October 2016,in case C 582/14,
 Article 29 Data Protection Working Party, Opinion 05/2014 on Anonymisation Techniques adopted on 10 April 2014 p. 3
Your new digital rights across Europe during summer holidays
This summer, European citizens will enjoy more digital rights than ever before. Following the end of roaming charges across the European Union last year, holidaymakers can now travel with their online TV, film, sports, music or e-book subscriptions at no extra cost. In addition, everyone across Europe can enjoy world-class data protection rules that ensure all Europeans have better control over their personal data.
Andrus Ansip, Vice-President for the Digital Single Market said: “Europeans are already starting to feel the benefits of the Digital Single Market. This summer you will be able to bring your favourite TV programmes and sports matches with you wherever you travel in the EU. By the end of this year, you will also be able to buy festival tickets or rent cars online from all over the EU without being geo-blocked or re-routed.”
Věra Jourová, Commissioner for Justice, Consumers and Gender Equality added: “The digital world offers tremendous opportunities, but also challenges; for example, our personal data is a useful asset for many companies. With the modern data protection rules we have put in place, Europeans have gained control over their data whenever they shop, book their holidays online or just surf the internet.”
Mariya Gabriel, Commissioner for the Digital Economy and Society said: “We are improving the daily life of our citizens, be it end of roaming charges or safer online environment. By completing all our digital initiatives we will bring even more positive change to consumers and businesses alike.”
Digital rights already in daily use
Since June 2017, people have been able use their mobile phones while travelling in the EU just like they would at home, without paying extra charges. Since the EU abolished roaming charges, more than five times the amount of data has been consumed and almost two and a half times more phone calls have been made in the EU and the European Economic Area.
Since April 2018, consumers can access online content services they have subscribed to in their home country also when travelling across the EU, including among other films, series and sports broadcasts (see examples in factsheet).
Under the new data protection rules which have been in place across the EU since 25 May 2018, Europeans can safely transfer personal data between service providers such as the cloud or email; everyone now has the right to know if their data has been leaked or hacked, or how their personal data is being collected. Furthermore, with the ‘right to be forgotten’, personal data has to be deleted upon request, if there are no legitimate reasons for a company to keep it.
Finally, with the net neutrality rules applying since spring 2016, every European has access to open internet, guaranteeing their freedom without discrimination when choosing content, applications, services and information of their choice.
With some digital rights already in place, there is more to come in the upcoming months. From September, Europeans will have increasingly the right to use their national electronic identification (eID) across the whole EU to access public services.
As of December, everyone will benefit from the free flow of non-personal data, as they will have access to better and more competitive data storage and processing services in the EU, thus complementing the free movement of people, goods, services and capital. Entrepreneurs meanwhile will have the right to decide where in the EU they store and process all types of data.
As of 3 December, Europeans will be able to shop online without unjustified discrimination wherever they are in the EU. They will not have to worry about a website blocking or re-routing them just because they – or their credit card – come from a different country.
As of next year, citizens will be able to compare parcel delivery costs more easily and benefit from more affordable prices for cross-border parcel delivery.
Agreed rules on value added tax for e-commerce will allow entrepreneurs to take care of their cross-border VAT needs in one online portal and in their own language.
With the recently agreed European Electronic Communications Code, Europeans will have the right to switch internet services and telecoms providers in a simpler way. They will also have the right to receive public alerts on mobile phones in case of an emergency. The new rules will also guarantee a better and more affordable connectivity across the EU.
With the updated rules for audiovisual media, Europeans will have the right to a safe online environment that protects them from incitement to violence, hatred, terrorism, child pornography, racism and xenophobia.
The Digital Single Market strategy was proposed by the Commission in May 2015 to make the EU’s single market fit for the digital age – tearing down regulatory walls and moving from 28 national markets to a single one. This has the potential to contribute €415 billion per year to our economy and create hundreds of thousands of new jobs.
Three years later, the strategy is well on its way: 17 legislative proposals have been agreed on, while 12 proposals are still on the table. There is a strong need to complete our regulatory framework for creating the Digital Single Market. Thanks to this the value of Europe’s data economy has the potential to top €700 billion by 2020, representing 4% of the EU’s economy.
Artificial intelligence: Between myth and reality
Are machines likely to become smarter than humans? No, says Jean-Gabriel Ganascia: this is a myth inspired by science fiction. The computer scientist walks us through the major milestones in artificial intelligence (AI), reviews the most recent technical advances, and discusses the ethical questions that require increasingly urgent answers.
A scientific discipline, AI officially began in 1956, during a summer workshop organized by four American researchers – John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon – at Dartmouth College in New Hampshire, United States. Since then, the term “artificial intelligence”, probably first coined to create a striking impact, has become so popular that today everyone has heard of it. This application of computer science has continued to expand over the years, and the technologies it has spawned have contributed greatly to changing the world over the past sixty years.
However, the success of the term AI is sometimes based on a misunderstanding, when it is used to refer to an artificial entity endowed with intelligence and which, as a result, would compete with human beings. This idea, which refers to ancient myths and legends, like that of the golem [from Jewish folklore, an image endowed with life], have recently been revived by contemporary personalities including the British physicist Stephen Hawking (1942-2018), American entrepreneur Elon Musk, American futurist Ray Kurzweil, and proponents of what we now call Strong AI or Artificial General Intelligence (AGI). We will not discuss this second meaning here, because at least for now, it can only be ascribed to a fertile imagination, inspired more by science fiction than by any tangible scientific reality confirmed by experiments and empirical observations.
For McCarthy, Minsky, and the other researchers of the Dartmouth Summer Research Project (link is external)on Artificial Intelligence, AI was initially intended to simulate each of the different faculties of intelligence – human, animal, plant, social or phylogenetic – using machines. More precisely, this scientific discipline was based on the conjecture that all cognitive functions – especially learning, reasoning, computation, perception, memorization, and even scientific discovery or artistic creativity – can be described with such precision that it would be possible to programme a computer to reproduce them. In the more than sixty years that AI has existed, there has been nothing to disprove or irrefutably prove this conjecture, which remains both open and full of potential.
In the course of its short existence, AI has undergone many changes. These can be summarized in six stages.
The time of the prophets
First of all, in the euphoria of AI’s origins and early successes, the researchers had given free range to their imagination, indulging in certain reckless pronouncements for which they were heavily criticized later. For instance, in 1958, American political scientist and economist Herbert A. Simon – who received the Nobel Prize in Economic Sciences in 1978 – had declared that, within ten years, machines would become world chess champions if they were not barred from international competitions.
The dark years
By the mid-1960s, progress seemed to be slow in coming. A 10-year-old child beat a computer at a chess game in 1965, and a report commissioned by the US Senate in 1966 described the intrinsic limitations of machine translation. AI got bad press for about a decade.
The work went on nevertheless, but the research was given new direction. It focused on the psychology of memory and the mechanisms of understanding – with attempts to simulate these on computers – and on the role of knowledge in reasoning. This gave rise to techniques for the semantic representation of knowledge, which developed considerably in the mid-1970s, and also led to the development of expert systems, so called because they use the knowledge of skilled specialists to reproduce their thought processes. Expert systems raised enormous hopes in the early 1980s with a whole range of applications, including medical diagnosis.
Neo-connectionism and machine learning
Technical improvements led to the development of machine learning algorithms, which allowed computers to accumulate knowledge and to automatically reprogramme themselves, using their own experiences.
This led to the development of industrial applications (fingerprint identification, speech recognition, etc.), where techniques from AI, computer science, artificial life and other disciplines were combined to produce hybrid systems.
From AI to human-machine interfaces
Starting in the late 1990s, AI was coupled with robotics and human-machine interfaces to produce intelligent agents that suggested the presence of feelings and emotions. This gave rise, among other things, to the calculation of emotions (affective computing), which evaluates the reactions of a subject feeling emotions and reproduces them on a machine, and especially to the development of conversational agents (chatbots).
Renaissance of AI
Since 2010, the power of machines has made it possible to exploit enormous quantities of data (big data) with deep learning techniques, based on the use of formal neural networks. A range of very successful applications in several areas – including speech and image recognition, natural language comprehension and autonomous cars – are leading to an AI renaissance.
Many achievements using AI techniques surpass human capabilities – in 1997, a computer programme defeated the reigning world chess champion, and more recently, in 2016, other computer programmes have beaten the world’s best Go [an ancient Chinese board game] players and some top poker players. Computers are proving, or helping to prove, mathematical theorems; knowledge is being automatically constructed from huge masses of data, in terabytes (1012 bytes), or even petabytes (1015 bytes), using machine learning techniques.
As a result, machines can recognize speech and transcribe it – just like typists did in the past. Computers can accurately identify faces or fingerprints from among tens of millions, or understand texts written in natural languages. Using machine learning techniques, cars drive themselves; machines are better than dermatologists at diagnosing melanomas using photographs of skin moles taken with mobile phone cameras; robots are fighting wars instead of humans; and factory production lines are becoming increasingly automated.
Scientists are also using AI techniques to determine the function of certain biological macromolecules, especially proteins and genomes, from the sequences of their constituents ‒ amino acids for proteins, bases for genomes. More generally, all the sciences are undergoing a major epistemological rupture with in silico experiments – named so because they are carried out by computers from massive quantities of data, using powerful processors whose cores are made of silicon. In this way, they differ from in vivo experiments, performed on living matter, and above all, from in vitro experiments, carried out in glass test-tubes.
Today, AI applications affect almost all fields of activity – particularly in the industry, banking, insurance, health and defence sectors. Several routine tasks are now automated, transforming many trades and eventually eliminating some.
What are the ethical risks?
With AI, most dimensions of intelligence ‒ except perhaps humour ‒ are subject to rational analysis and reconstruction, using computers. Moreover, machines are exceeding our cognitive faculties in most fields, raising fears of ethical risks. These risks fall into three categories – the scarcity of work, because it can be carried out by machines instead of humans; the consequences for the autonomy of the individual, particularly in terms of freedom and security; and the overtaking of humanity, which would be replaced by more “intelligent” machines.
However, if we examine the reality, we see that work (done by humans) is not disappearing – quite the contrary – but it is changing and calling for new skills. Similarly, an individual’s autonomy and freedom are not inevitably undermined by the development of AI – so long as we remain vigilant in the face of technological intrusions into our private lives.
Finally, contrary to what some people claim, machines pose no existential threat to humanity. Their autonomy is purely technological, in that it corresponds only to material chains of causality that go from the taking of information to decision-making. On the other hand, machines have no moral autonomy, because even if they do confuse and mislead us in the process of making decisions, they do not have a will of their own and remain subjugated to the objectives that we have assigned to them.
13 Health Tech Innovators Changing the World
Thirteen early career scientists from across the Asia-Pacific who are revolutionizing healthcare technology have been named finalists for the 2018 APEC Science Prize for Innovation, Research and Education.
From new preventative treatments to enhanced threat detection to rapid recovery solutions, the cross-border research breakthroughs developed by these innovators under 40 years of age were recognized in accordance with this year’s ASPIRE Prize theme: Smart Technologies for Healthy Societies.
The winner will be announced by science and technology officials and industry representatives from the APEC Policy Partnership on Science, Innovation and Technology when they convene in Port Moresby in August. The winner will also receive USD 25,000 in prize money sponsored by Wiley and Elsevier, publishers of scholarly scientific knowledge.
Meet the 2018 ASPIRE Prize Finalists:
Dr Madhu Bhaskaran
Associate Professor, RMIT University, Melbourne, Australia
Field of research: Electronic materials engineering
Dr Bhaskaran’s work transforms the way we imagine, use and interact with electronic devices and sensors. She has developed ways to combine functional oxide materials processed at high temperatures with elastic and plastic materials. Her work has led to the development of wearable elastic electronics and sensors including gas and UV sensors and flat optical devices—all of which are stretchable, optically transparent and as thin as a nicotine patch. An example of an application includes the development of devices to detect amount of exposure to UV rays which contribute to skin cancer.
Dr Daniel Fuller
Assistant Professor and Canada Research Chair in Population Physical Activity, Memorial University of Newfoundland
Field of research: Human kinetics and public health
Dr Fuller’s research involves designing healthier cities by using mobile health technologies like wearable devices, mobile phones, machine learning and geographic information science to increase physical activity. He works closely with cities and local community organizations to evaluate the impact of existing interventions such as bicycle share programs, bridge construction and snow clearing on physical activity.
Dr Pablo González Muñoz
Assistant Professor, Pontificia Universidad Catolica De Chile
Field of research: Host-pathogen interactions, human viruses, immunology, microbiology and immune evasion
Dr González studies the virus herpes simplex-2 (HSV-2), a virus that currently affects about 500 million people for which a vaccine is not available. Dr González has worked with at least five human pathogens. Through his research, he has developed a fast, affordable and easy-to-use diagnostic kit to detect viral infections for different tissues that can be used in rural areas.
Dr Liu Guanghui
Professor, Institute of Biophysics, Chinese Academy of Sciences
Field of research: Stem cells and healthy aging
Dr Liu researches aging, organ and tissue homeostasis, and aging-associated diseases. Through his work, he has discovered therapeutic interventions to allow for the “healthy aging” of human stem cells. Dr Liu’s work continues to enhance the study and treatment of disorders related to aging.
Dr Chairul Hudaya
Assistant Professor, University of Indonesia
Field of research: Electrical power and energy materials
Dr Hudaya researches affordable smart energy storage technology for healthy societies, especially those living in remote and isolated areas. His two main projects include: 1) a portable energy storage device used with an infant incubator, serving premature infants; and 2) a smart monitoring system installed in a laptop enabling nurses to communicate in remote, off-grid areas.
Dr Choongik Kim
Associate Professor, Sogang University
Field of research: Wearable/flexible electronics, organic/polymeric materials, semiconductors
Dr Kim researches and develops novel electric materials for use in wearable devices, including activity monitoring bracelets, smart watches and GPS enabled shoes. In 2007, as published in Science, he was the first to expand upon the relationship between electric materials and electronic device performance. Dr Kim’s research is used to develop the core technology for new wearable technologies, leading to more real-time applications that can support meaningful improvements in health outcomes.
Dr Siti Hamidah Mohd Setapar
Associate Professor, Universiti Teknologi Malaysia
Field of research: Micellar nanotechnology, extraction of national products, product development from natural ingredients, cosmetic formulation and separation processes
Dr Mohd Setapar’s research focuses on micellar nanotechnology, a cutting-edge technology used in skincare and cosmetics to improve the effectiveness of the skin cleansing process and enhance the absorption capacity of cosmetic ingredients into the skin. She has commercialized a range of cosmetic and skincare products through her university spin-off company. Dr Mohd Setapar’s mission is to empower Malaysian women with safer, high-quality cosmetic products and to make available high-value cosmetics combining micellar nanotechnology with local natural extracts at lower prices.
Dr Mario Antonio Jiz II
Research Institute for Tropical Medicine
Field of research: Immunology
Dr Jiz researches schistosomiasis, a disease caused by parasitic worms that is second only to malaria as the most devastating parasitic disease. Dr Jiz develops vaccines for schistosomiasis and has patented a large scale production of a solution for the body to induce immunity against the disease.
Dr Vladislav Voitenkov
Ministry of Economic Development of the Russian Federation
Field of research: Clinical neurophysiology, infections of the nervous system, encephalitis, meningitis, myelitis and inflammatory polyneuropathy (Guillain-Barré syndrome)
Dr Voitenkov’s work focuses on understanding neurology and functional diagnostics, especially in the aging process. He studies the rare disease, inflammatory polyneuropathy (Guillain-Barré syndrome), where the body’s immune system attacks your nerves, paralyzing a person’s entire body.
Dr Daniel Shu Wei Ting
Assistant Professor, Duke-NUS Medical School, NUS
Field of research: Artificial intelligence using deep learning in screening for diabetes eye screening
Dr Daniel Shu Wei Ting’s work focuses on screening techniques for diabetic retinopathy, an eye disease for people with diabetes, which can lead to loss of vision. He has led a large research team in building the world’s first artificial intelligence system using deep learning to detect three potentially blinding conditions.
Dr Ming-Kai Pan
Physician Principle Investigator, NTUH
Field of research: Neurology—movement disorders
Dr Pan specializes in human physiology and mouse models of neurological disorders. His work is focused on discovering novel ways to measure brain physiology for movements which have implications for Parkinson’s disease, essential tremors and cerebellar ataxic disorders. Dr Pan has also invented smart technology to identify the most common movement disorders affecting 20 per cent of the elderly population.
Dr Wanpracha Art Chaovalitwongse
Professor, University of Arkansas, Fayetteville
Field of research: Data analytics, machine learning, artificial intelligence, health informatics, medical imaging analysis and medical decision making
Dr Chaovalitwongse’s research focuses on data analytics in medical and healthcare applications, especially in analyzing brain activity to predict and monitor epilepsy. Through his work, he has developed solutions for problems caused by attention deficit/hyperactivity disorder, Alzheimer’s disease, Parkinson’s disease, non-small cell lung cancer, sarcoma and esophageal cancer.
Dr Kara Spiller
Assistant Professor, Drexel University
Field of research: Biomedical engineering
Dr Spiller focuses her research on the design of “smart” biomaterials that can control the behavior of immune cells to promote tissue repair and wound healing. She has developed a point-of-care diagnostic to tailor optimal treatment for patients based on the state of their immune system according to factors such as age, genetics and nutrition.
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