ML&AI Approach to User Understanding Ecosystem at VCCorp: Applications to News, Ads, and E-commerce
Nowadays, computer vision algorithms – automated translation, image recognition – have surpassed others in the industry, even humans. AI technology improves human life, facilitating their working performance, thanks to the breakthroughs in computational technology with the rapid development of hardware (CPUs/GPUs). In this presentation, we will be discussing AI platforms in VCCORP, the challenges and possibilities.
Dr. Hoang Anh Tuan – VCCorp (Vietnam)
Tuan Hoang is the Chief Technology Officer of Admicro – VCCORP – a company pioneer in technology and software development in Vietnam. Tuan has over 10 years of experience in the field of intelligence and large-scale processing system. His numerous contributions mainly focus on the AI applications, big data processing services which are able to server millions of customers and internet users in Vietnam.
Analyzing Daily Activity Logs for Smart Interaction
Collecting and analyzing daily activity logs can provide potential insights for better understanding and possible optimization for individual and organizational activities and operations. There are multiple sources to gather information in various formats during daily activities. People usually post photos, video clips, or messages to their social channels everyday. People may record their daily activities with wearable cameras or other types of sensors. Millions of surveillance cameras capture various events in traffic systems, offices, or supermarkets. It is an increasing demand to process and analyze such information, mostly in visual format, to develop useful services and utilities for smart environments.
In this talk, we present several modalities to analyze and interact with daily activity logs to develop potential applications for smart environments. Our proposed systems are based on practical social needs and aim to provide people natural experience with smart services and utilities.
– People can access to augmented data and services for tourism or shopping by recognizing the current context and retrieving similar known cases.
– Lost items can be found or memories can be retrieved or verified by searching daily logs.
– Reminiscence can help people to positively revive past memories and connections with their relatives.
– Regular events and anomalies can be detected from surveillance systems for appropriate actions.
– Event simulation in virtual or mixed reality environments can be generated from real life data for education and training.
We also discuss about privacy and security issues in collecting and analyzing daily activity logs.
Assoc. Prof. Tran Minh Triet – VNUHCM University of Science (Vietnam)
Minh-Triet Tran obtained his B.Sc., M.Sc., and Ph.D. degrees in computer science from University of Science, VNU-HCM, in 2001, 2005, and 2009. He joined the University of Science, VNU-HCM, in 2001. His research interests include cryptography and security, computer vision and human-computer interaction, and software engineering. He was a visiting scholar at National Institutes of Informatics (NII, Japan) in 2008, 2009, and 2010, and at University of Illinois at Urbana-Champaign (UIUC) in 2015-2016.
He is currently Head of Software Engineering Laboratory and Deputy Head of Artificial Intelligence Laboratory, University of Science, VNU-HCM. He is also the Deputy Head of Software Engineering Department, Faculty of Information Technology, University of Science, VNU-HCM. He was a member of the Executive Committee of the Information Security Program of Ho Chi Minh city. He is a member of the Management Board of Vietnam Information Security Association (South Branch) and also a member of the Executive Committee of ICT Program for Smart Cities (2018-2020) of Ho Chi Minh city.
AI in Healthcare – Opportunities for Vietnam
“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”
(Clive Humby, UK Mathemetician and architect of Tesco’s Clubcard, 2006)
Healthcare has been long understood as the most promising application area for AI. In the past five years, 300 deals in the field of healthcare AI have been closed, with total investments of over USD 2 billion. This trend is accelerating quickly.
The two most active areas of research and deployment are Medical Imaging & Diagnostics (e.g. automated detection of medical conditions on X-Ray) and Patient Data & Risk Analytics (e.g. identifying patients with high risk of stroke from their past medical record), both of which require vast amount of labeled data.
Dr. Tran Dang Minh Tri (Dimitry Tran) – Harrison-AI (Australia)
In a world where algorithms are open-sourced and processing power is easily accessible over the cloud, the future superpowers in healthcare AI will be the countries that best capture and apply their population’s health data to develop machine learning solutions.
Every single day, each Vietnamese hospital create tens of thousands of new data points – X-Ray images, CT scans, blood tests, disease diagnoses. All these data are the crude oil that currently being wasted. How do we refine this oil to run the healthcare AI machine?
How do we – government, hospitals, tech companies, AI researchers – work together to capture this opportunity and make Vietnam into a healthcare AI superpower in the next 3 years?
Dimitry Tran (Trần Đặng Minh Trí), a health care innovator with bases in Australia and Vietnam, is a co-founder of Harrison-AI with his brother Aengus Tran (Trần Đặng Đình Áng).
Harrison-AI is a Sydney-based healthcare artificial intelligence lab. Taking the implementation path, Harrison-AI seeks to bring the latest developments in AI to solve the biggest challenges in healthcare – making it better and cheaper for all. In 2017, Harrison-AI made a breakthrough in the field of reproductive health. The technology is now patent-pending and undergoing multi-national and multi- centre clinical trial with a global healthcare provider.
Dimitry is the Head of Innovation at Ramsay Health Care – a USD 10 billion enterprise, and one of the largest hospital operators in the world with over 200 facilities in Australia, France, UK, Indonesia and Malaysia. In this role, Dimitry works on growing innovative care models and technologies to expand healthcare services and improve patient outcomes.
He is also a founding investor and on the board of directors of MediRecords.com – the first cloud-based doctor practice management software in Australia.
Dimitry is a Honorary Associate at the Hoc Mai Foundation, a 20-year-old charity operated by University of Sydney Medical School in partnership with Hanoi Medical University. He is also the Co-Founder and Chairman of the Centre for Healthcare Improvement (CHIRvn.org), a social enterprise with the goal of accelerating the pace of change and ‘make healthcare better for patients, professionals and population’ in Vietnam.
Dimitry holds the Chartered Financial Analysts (CFA) designation, Executive MBA degree from the University of New South Wales, and Executive Education Certificate from Harvard Business School. He is studying toward the Master of Applied Science in Patient Safety and Healthcare Quality degree at Johns Hopkins University.
Dimitry graduated first in his class at Bond University, where he completed bachelor degrees in Accounting and Finance and was the recipient of the Dean Scholarship and University Medal.
Fostering the communities of robotics and AI in Vietnam and in International
Siloed development, wasted labor, and high start-up cost are limiting the pace of robotics innovation. With Kambria, our mission is to accelerate this process – enabling faster, cheaper, and easier robotics development and adoption by everyone. In this talk we will discuss the unique game-theoretical design of Kambria based on blockchain and crypto-economics to align the incentives of all key stakeholders in the robotics community. Ultimately, the Kambria platform will foster an ecosystem where collaborators, top developers, and companies, who share our passion for robotics technology will deliver affordable and impactful robots to end users. We will then discuss how Kambria could help build a strong AI and robotics community in Vietnam to capture the upcoming opportunities. We will also give a quick demo of our first robot and an arm prototype manufactured based on 3D-printing technology. Our mission is to equip Vietnam with the engineering talents and the manufacturing capabilities to become a significant AI & Robotics hub in the world.
Dr. Vu Duy Thuc – Ohmilabs (USA)
Graduated from Carnegie Mellon with a BS and Stanford with a PhD both in Computer Science, Ohmnilabs’ CEO and co-founder Thuc Vu is an expert in Artificial Intelligence and Algorithms. His ambition is to bring robots into every home to create a positive impact in people’s life. And Kambria – a decentralized AI and Robotics platform – is his next move to bring this goal one step closer to reality. He previously founded Katango and Tappy which were quickly acquired by Google and Weeby.co, respectively. He also invests in early stage startups and helps grow the ecosystem in Vietnam. Apart from being an entrepreneur, Thuc is also a Research Scientist and Assistant Professor at John Von Neumann Institute of Vietnam National University. As a way to pay it forward, Thuc co-founded VietSeeds in 2011, a nonprofit organization empowering hundreds of underprivileged students with excellent academic record in Vietnam. In 2017, he was named as one of the “40 Under 40” of Silicon Valley by the Silicon Valley Business Journal for his tireless effort to bring about a significantly positive impact in the business world.
AI and data in cancer research
Artificial intelligence is playing an increasingly important role in cancer research. Advancement in acquisition technologies has led to largescale data production of various molecular readouts. Coupled with smart learning algorithms, this brings exciting challenges and opportunities for early detection, diagnostic, treatment selection and monitoring of cancers. Is it possible to identify cancers early in a non-invasive manner? Can cross-cancer analysis offer guidance to treatment of patients whose tumors reside in a different organ and yet sharing driver gene mutations with other tumors that have previously been successfully managed?
In this presentation, I will survey current methods and data in cancer genomics and proteomics with a view towards real-life applications. I will also discuss sustainable software tools and computing infrastructures to maintain the momentum of AI in the field of cancer research.
Dr. Pham Viet Thang – VU University Medical Center (Netherland)
Pham Viet Thang received a BSc degree in computer science from RMIT University, Australia in 1998. After a brief period working as teaching assistant at Vietnam National University in 1999, he joined the Intelligent Systems Lab Amsterdam, the Netherland where he earned a doctoral degree on the topic of machine learning and computer vision. During this period, he devised new methods for Bayesian network classification, support vector classification, boosting algorithms, and sparse representation of images. Since 2006, he has been working first as research scientist and now as assistant professor at the Cancer Center Amsterdam, VU University Medical Center, the Netherlands. His current interest is to advance computer algorithms to explore the vast amount of data in cancer research. A highlight of his work is the development of statistical methods for significance analysis of mass spectrometry-based proteomics data.
Application of artificial intelligence techniques in building economic-financial forecast models on high dimensional data sets.
Forecasting in the economic-financial field plays a very important role for the direction and regulation of the government, the development and implementation of business-production strategies of enterprises, investment and consumption of people. So far, the econometric approach based on a combination of mathematics, economic theory and statistical prediction with regression techniques, remains the most popular and important one to make forecasts in the field of economics and finance.
With the increasing economic globalization and the rapid development of science and technology, each event in the field of economics – finance is affected by many other economic-financial and social factors in the country as well as abroad. The current econometric approach to build economic-financial forecasting models is not applicable to input data sets with high dimensions and it is a very big challenge for the implementation of economic-financial forecasts.
The purpose of this report is to present some approachs of application of artificial intelligence techniques in building economic-financial forecasting models on huge input data sets. Artificial intelligence techniques are very useful for dimensionality reduction of input data sets and to improve the quality of forecasting models built under the econometric approach. Some forecasting models in the economic – financial field built arcoding to the mentioned approachs on the real data sets of the economy show that the forecast accuracy by the models is not only increased but also can use these models for evaluation of the impact of economic-financial shocks as well as of many other external factors. Some new researchs by author and some open issues will also be presented and discussed in this report.
Assoc. Prof. Do Van Thanh – Nguyen Tat Thanh University (Vietnam)
Assoc. Prof. PhD. Do Van Thanh was a senior researcher, deputy director of the National Center for Socio-Economic Information and Forecasts, Ministry of Planning and Investment, and a part – time lecturer of the Information Technology Department, University of Technology, Hanoi National University. Now he is a full time lecturer, the Information Technology Department, Nguyen Tat Thanh University. He received PhD’s degree in Information Technology in 1996 from the Vietnamese Academy of Science and Technology. His research interests include Data Analysis and Data Mining, Knowledge representation and automatic reasoning, Economic – Financial Analysis and Forecast. He is the author and co-authors of more than 70 peer – reviewed publications concerning the all fields above. He has strong experience in knowledge discovery in databases and building economic-financial forecast models.
AI in 5G networks
The telecommunications industry have pursued efforts to realize the idea of 5G networks. Besides increasing speeds and more efficient utilization of spectrum, a main goal is to establish the foundation and the common framework of new innovative network services.
5G operators may create new revenue streams from hosting 3rd party applications in their infrastructure in addition to the provisioning of their own services.
To achieve the aims of 5G, the development of scalable self-managed software and cloud platforms that supports the rapid deployment of services are needed. European Telecommunications Standards Institute (ETSI) has specified the Network Functions Virtualisation concept where Network Services are constructed by an appropriate chaining of
Network Functions (either physical network functions or virtualized network functions — VNF). The NFV initiative transformed the way telecom network operators architect their networks. It embraced virtualization techniques widely used in the IT industry and introduced the Infrastructure-as-a-Service cloud computing model into the Telco world.Some use cases of 5G applications have strict requirements (i.e., high availability and low latency for VR, AR, V2X, etc.) that can be achieved by the careful engineering, the new operating rules of cloud platforms and the optimal placement of application components. In the talk, the application possibilities of AI will be outlined for the efficient operation and management of 5G networks.
Prof. Do Van Tien – Budapest University Of Technology And Economics (Hungary)
Tien Van Do received the M.Sc. and Ph.D. degrees in telecommunications engineering from the Technical University of Budapest, Hungary, in 1991 and 1996, respectively. He is a professor in the Department of Telecommunications of the Budapest University of Technology and Economics, and a leader of Communications Network Technology and Internetworking Laboratory. He habilitated at BME, and received the DSc from the Hungarian Academy of Sciences in 2011. He has participated and lead work packages in the COPERNICUS-ATMIN 1463, the FP4 ACTS AC310 ELISA, FP5 HELINET, FP6 CAPANINA projects funded by EC (where he acted as a work package leader). He led various projects on network planning and software implementations that results are directly used for industry such ATM & IP network planning software for Hungarian Telekom, GGSN tester for Nokia, performance testing program for the performance testing of the NOKIA’s IMS product, automatic software testing framework for Nokia Siemens Networks. His research interests are queuing theory, telecommunication networks, cloud computing, performance evaluation and planning of ICT Systems. He is also a board member of Discrete Dynamics in Nature and Society, Hindawi.
General Game Playing: a Challenge for AI
Games represent an exciting challenge for Artificial Intelligence. The ability of computers to confront human beings in a convincing manner, or even to defeat them, fascinate most people. Besides, games are a good framework to test algorithms developed for more general problems. Thus games are a good area to test out AI techniques and to develop new approaches. Recently, stronger results were provided and, for many games, computer skills are far away from human abilities.
We focus in this talk on the challenge of General Game Playing. The topic of General Game Playing (GGP) is to develop artificial agents able to play any game, without human intervention. The rules of each game are described in a declarative representation language, called Game Description Language (GDL). These rules are given to the agent only a few minutes before playing, which makes it difficult to apply current techniques. We discuss in this talk the difficulty of this challenge, some recent results and some possible applications in real life.
Assoc. Prof. Sylvain Lagrue – University of Artois (France)
LAGRUE Sylvain is an Associate Professor of Computer Science at Université d’Artois/CRIL CNRS UMR 8188 (France). His research includes Artificial Intelligence, Knowledge Representation, Uncertainty in AI and Games. He is currently invited at the VNU in the framework of the EU Project Aniage.
Answer set programming and its Applications
ASP is an emerging declarative programming paradigm. It has been used in several practical applications. This talk will present the basic idea of ASP and demonstrates its use in several applications such as distributed constraints optimization problems, reasoning about truthfulness of agents’ statements, smart home scheduling etc.
Prof. Tran Cao Son – New Mexico State University (USA)
Tran Cao Son received his doctoral degree from the University of Texas at El Paso in 2000. He is currently a Computer Science Professor at the New Mexico State University in Las Cruces. Before joining NMSU, he was a post-doc at the Knowledge System Laboratory at Stanford University for almost a year. His main research interests are in knowledge representation and reasoning, especially logic programming and answer set programming and its applications in planning, negotiation, and multi-agent systems.
Developing Intelligent Systems based on Internet of Things: Some preliminary results
Recently, there has been a great interest to develop intelligent systems based on Internet of Things (IoT), which connects physical objects like sensors nodes to collect real time data accessible through the Internet. Nowadays, in simple terminology, IoT includes almost things such as cell phones, building maintenance services, jet engine of an airplane. It also aids clinicians in diagnosis of heart monitor implant or farmers in a biochip transponder in farm animals. The IoT-connected devices transfer data over a network and are the component members of IoT. In this talk, we would like to summarize our preliminary recent achievements in developing intelligent systems based on IoT typically smart city, electricity generation system, and air pollution minimization: A smart city utilizes the information and communication technology to make efficient consumption of limited resources like space, mobility, energy, etc. This research focuses on developing an effective system for impairments monitoring, traffic monitoring, and smart city innovation with digitalized software for fast and effective implementations; Electrical energy generation from multiple sensors for household appliances and industrial areas is conducted. Electricity from the renewable energy sources such as stress generated by the body weight, heat generated by human body, and movements of the body can be measured by different sensors and transferred to the control system for storing; Air pollution minimization is performed using IoT. Various sensors have been used such as temperature sensor, humidity sensor, smoke sensor and many others to collect data from dust and environment. This model allows finding vehicles which releases more carbon dioxide to reduce the pollution.
Assoc. Prof. Le Hoang Son – VNU University of Science (Vietnam)
Le Hoang Son obtained the PhD degree on Mathematics – Informatics at VNU University of Science, Vietnam National University (VNU). He has been promoted to Associate Professor in Information Technology since 2017. Currently, Dr. Son works as a researcher and Vice Director at the Center for High Performance Computing, VNU University of Science, Vietnam National University. His major field includes Artificial Intelligence, Data Mining, Soft Computing, Fuzzy Computing, Fuzzy Recommender Systems, and Geographic Information System. He is a member of International Association of Computer Science and Information Technology (IACSIT), Center for Applied Research in e-Health (eCARE), Vietnam Society for Applications of Mathematics (Vietsam). Dr. Son serves as Editorial Board of International Journal of Ambient Computing and Intelligence (IJACI, SCOPUS), Editorial Board of Vietnam Journal of Computer Science and Cybernetics (JCC), Associate Editor of International Journal of Engineering and Technology (IJET), Associate Editor of Neutrosophic Sets and Systems (NSS), and Associate Editor of Vietnam Research and Development on Information and Communication Technology (RD-ICT).