Day 1 :
Keynote Forum
Shabir Momin
ZengaTV, Singapore
Keynote: Data mining, context creation which lead to sale
Time : 08:45 - 09:25
Biography:
Shabir Momin became the youngest CTO, he was also awarded as the Entrepreneur of the Year in 2013 by TIE. He has had a successful track record in various technology and business positions at a CXO level for few years before he became an entrepreneur. He has sold few ventures in the past and his current ventures that he has founded and co-founded are ZengaTV, one of the leading OTT services in India, OneDigital Entertainment Largest, a Digital content company in India, OneAxcess.com. He is a successful Entrepreneur and a professional with an excellent track record in technology innovation, especially in the digital media and convergence technology. In the past, he has been the Head of Asia for a technology innovation company called Picsel Technologies (UK) and Sentac Inc. (USA). He has also been CEO Asia for I-Connect Inc., a US based MNC, an operation comprising more than 9000 employees working out of the Asia Pacific region.
Abstract:
The world is evolving faster than we know. Brands communication and sales approach are changing and now becoming more driven by data mined, predictive and AI-based decision making. Gut calls will still be there but would be taking a back seat. While the data-driven market is growing exponentially, brands these days are not yet using the data-driven information to do the predictive sale. The Deep analysis can also be used for decision making strategy to do right positioning among its competition. The data-driven ecosystem will grow manifold in the near future resulting in the data explosion. With this, brands use the data for better outcomes if used strategically through predictive analytics which helps to understand the business insights. The challenge which the brands face is that they do not know which data to collect and how to analyze the collected data. A lot of brands are facing the same issue. It is a matter of utmost importance for any business survive first and then drive its growth, therefore it is necessary to build the right data science strategy through collecting the right data along with the right analysis to build the expected business ecosystem to get the best results.
Keynote Forum
Anu Kukar
KPMG, Australia
Keynote: Risk management as you go for implementing emerging technologies AI, RPA & ML
Time : 09:25 - 10:05
Biography:
Anu helps organizations reduce the cost of effective risk management through:
- Applying data, digital and emerging technologies for better risk outcomes
- Integrating a RiskLens on emerging technology and transformation initiatives such as: AI, Machine Learning, RPA, IoT, Cyber, XTechs, Vx, Chatbots etc.
- Equipping Risk Teams with new skills, behaviour and mindsets for tomorrow and the future
Anu brings 18 years of experience across Risk & Compliance management, Internal Audit, Governance, Regulatory, Management Consulting and Tax. She has also worked across many industries: Insurance, Bank, Government, Corporates, Manufacturing, Energy and Telecommunications. She is also a global speaker and has spoken at conferences in Dubai, Denmark, Singapore, Thailand, India and Australia. Anu is a graduate from Australian Institute of Company Directors (AICD), a Chartered Accountant (ICAANZ) and holds a Bachelor of Commerce in Accounting and Information Systems (UNSW). Certifications from HarvardX in Cyber & Data risk management, MIT in Artificial Intelligence (ML, RPA, NLP)
Abstract:
Help! My Bot is not listening to me. Can a Bot be risky? Can a Bot be non-compliant? Can a Bot be governed?
Whether you are choosing the business process, undertaking a proof of concept or piloting for RPA- are you making the most common GRRC mistake? Having set up a project team ensuring project risks are managed is usually done by everyone. Then there is identifying the new risks arising from RPA such as reputational risks, impact on employees, increased cyber risk, privacy and security etc. This is usually considered as part of the business case and project implementation. Managing risk during the change, such as undertaking RPA implementation, can often lead to elements of the risk and compliance management framework being overlooked or forgotten. Imagine your implementing your RPA project and forget to ensure your Business Continuity Plan (BCP) reflects the change in staff and the requirements to support your bots which have not been implemented. Your workforce composition and location has no doubt changed and so will your business requirements. Or take the vendor or strategic alliances agreements you have entered into to deliver this project and support the business in meeting their strategy, objectives and servicing their customer needs. Have you notified the regulator if it is a material provider? What about the contract arrangements, SLA’s, cybersecurity how they will be monitored to ensure reputational, operational, strategic, compliance risks are appropriately managed. Assessing the impact and implementing changes to all the impacted components of the risk and compliance management framework can save lots of unwanted headache financially and non-financially! The element of good governance and commercial risk management is often overlooked, left too late or the team is fatigued out by the 3 mentioned components-
(1) Project risk management
(2) Identifying new risks and
(3) Managing risk during change
What is equally if not the critical component of GRRC management in implementing RPA is considered it at each of the stages choosing the process, proof of concept, pilot, implementation, and post-implementation. Hear, see and learn practical ways to integrate and consider GRRC into the relevant stage of your RPA journey and ensure your bot is listening to you!
Keynote Forum
Mahmoud Moussa
Microsoft Corporation, UAE
Keynote: Search the world like you search the web (computer vision and object detection)
Time : 10:30 - 11:10
Biography:
Mahmoud Moussa is a Cloud Solution Architect for Big Data and AI in Microsoft, with the Middle East and Africa Coverage. 16 Years of Experience in the field of Data and a variety of Business Markets Bridging the Technology and Business is the key focus.
Abstract:
The world is Getting Smarter, Imagine you can search your physical World same way you search the web, With the Advances of Artifical Intelligence and Cameras we Currently have, People can look for objects, People the same way we search the internet. From a factories to hospitals the technology can provide a great help into tune the life we have and make us do things more efficient, Object Detection is tightly coupled with Object Tracker and not just identifying Objects but also tracking them, during this talk we will discuss the different algorithms and market trends in both object detection and object tracker and some real-life examples to apply the technology to business solutions. The 30 minutes talk will discuss the different algorisms and techniques that can help both developers and data scientist understand the best fit for each in building business solutions.
Algorithms discussed,
- YOLO
- Tensorflow Object Detection
- MobileNet
- Mask R CNN
- BOOSTING Tracker
- MIL Tracker
- KCF Tracker (Kernelized Correlation Filters)
- CRSY Tracker
With the help of Microsoft Azure Cognitive Services can help developers with a limited Machine learning and Artifical Intelligence Knowledge build cutting-edge solutions that cover lots of the use cases in the business with a minimal amount of coding and reach an outstanding solution.
Keynote Forum
Gerald C Hsu
EclaireMD Foundation, USA
Keynote: Health-maintaining tips for diabetes travelers
Time : 10:00-11:00
Biography:
Gerald C Hsu has completed his PhD in Mathematics and has been majored in Engineering at MIT. He has attended different universities over 17 years and studied seven academic disciplines. He has spent 20,000 hours in T2D research. First, he studied six metabolic diseases and food nutrition during 2010-2013, then conducted research during 2014-2018. His approach is math-physics and quantitative medicine based on mathematics, physics, engineering modeling; signal processing, computer science, big data analytics, statistics, machine learning and AI. His main focus is on preventive medicine using prediction tools. He believes that the better the prediction, the more control you have.
Abstract:
For the past 6.5 years (2012-2018), the author has made 179 trips by air which included 69 long-haul travels and 110 short-distance travels. The average trip was 14 days. This paper provides his experience on maintaining his health during traveling days. Prior to 2015, both of his daily average glucose and Metabolism Index (MI), which has a 73.5% break-even level, were high. After 2015, his glucose and MI levels improved to a healthy state; however, he did not meet his own targets- glucose 117 mg/dL and MI 59%. Nevertheless, by following the guidelines listed below from the period after 2015, the author had better results. Therefore, other busy T2D travelers can also maintain their healthy level of both glucose and metabolism during their traveling days by using the same method. The traveling tips summary- (1) Try to avoid having meals at the airport, airline lounge and in-flight food. (2) Don’t indulge yourself, avoid soft drinks, high carbs/sugar food (<15 grams/meal); eat mostly vegetables (size: ~2 fists) and eat berries and tomatoes, not overly sweet fruits. (3) Maintain exercise regimen. After eating, find places to walk 4,000 steps. If inside the airport, walk along the hallway between gates, wherever is safe. (4) Drink 2,000 to 3,000 cc of water each day, dress comfortably, control your weight, maintain sufficient sleep hours, keep a positive mindset and avoid getting sick or injured.
- WORKSHOP
Session Introduction
Manoj Mishra
Union Insurance, UAE
Title: Emerging trends in machine learning
Time : 11:25 - 12:10
Biography:
Abstract:
- Machine Learning | Artificial intelligence applications | Deep Learning | Deep Learning Frameworks | Data analytics in cloud | Pattern Recognition | Facial Expression and Emotion Detection | Artificial Neural Networks (ANN) & Chainer | Augmented Reality (AR) and Virtual Reality (VR)
Chair
Shabir Momin
ZengaTV, Singapore
Co-Chair
Santosh Godbole
SSN Solutions Limited, India
Session Introduction
Harshavardhana Kikkeri
Kaaya Tech Inc, USA
Title: Heralding the era of machine teaching – where you clothes become your virtual AI trainer
Time : 13:10 - 13:40
Biography:
Abstract:
Santosh Godbole
SSN Solutions Limited, India
Title: Applying big data analytics and machine learning in precision marketing
Time : 13:40 - 14:10
Biography:
Abstract:
Biography:
Abstract:
Ahmed AlMaqabi
Almaqabi, Kingdom of Bahrain
Title: Could machine learning and other technologies disrupt audit industry ?
Time : 14:40 - 15:10
Biography:
Abstract:
Kai Khalid Miethig
Tariq Faqeeh Engineering, Bahrain
Title: W-AI-STE and architecture waste management in buildings with the support of machine learning and artifical intelligence
Time : 15:30 - 16:00
Biography:
Abstract:
Abed Benaichouche
Inception Institute of Artificial Intelligence, Abu Dhabi, UAE
Title: Overview of recent advance of deep learning application in computer vision
Time : 16:00 - 16:30
Biography:
Abstract:
- POSTER PRESENTATION 16:30-17:30
Session Introduction
Balasubramanyam Pisupati
Robert Bosch Engineering and Business Solutions Limited, India
Title: Ensemble of time series forecasting in complex structure
Biography:
Abstract:
Beesung Kam & Byung Kwan Choi
Pusan National University, South Korea
Title: Predicting future rank and score of graduation by using student’s status and temporal behavior
Biography:
Abstract:
Semakula Abdumajidhu
Makerere University, Uganda
Title: Sooty mold effect on cassava yields using convolutional neural networks
Biography:
Abstract:
Rohit Agarwal & Gaurav Pawar
Mobisy Technologies Pvt Ltd, India
Title: An overview of deep learning based object detection techniques in retail domain
Biography:
Abstract:
Biography:
Abstract:
Aisha Al Owais
Sharjah Center for Astronomy and Space Sciences, UAE
Title: Deep learning - An application of machine learning to classify images
Biography:
Abstract:
Living in the 21st century, mankind’s most powerful weapon is technology. The field of technology we are interested in is computer science, specifically Artificial Intelligence (AI). As the name suggests, AI is about turning devices into intelligent agents that take actions based on the environment they perceive. They are also flexible in terms of changing their goal- what they are meant to do as well as adjusting their actions depending on its changing environment. What makes AI agents peculiar is their ability to learn and remember from their mistakes. Furthermore, Machine Learning (ML) is one of AI’s applications that enable systems to learn automatically, improve through experience and adjust its actions without human intervention. This takes us to Deep Learning (DL), a new subfield of ML concerned with algorithms inspired by the structure and function of the human’s brain called artificial neural networks. It has networks which are capable of learning data obtained from instructed or unlabeled data; therefore it is also known Deep Neural Network (DNN). All those terms lead us to what we are mostly interested in, Convolutional Neural Networks (CNNs), which is a deep neural network that is particularly wall-adapted to classify images, in our case to classify images of meteorites.
Nabil Belgasmi
Banque de Tunisie, Tunisia
Title: Multiobjective deep reinforcement learning approach for ATM cash replenishment planning
Biography:
Abstract:
- PRODUCT LAUNCH BY SHABIR MOMIN & SANTOSH GODBOLE (11:10 - 11:25)
Session Introduction
SHABIR MOMIN & SANTOSH GODBOLE
SSN Solutions, London
Title: Product Launch
Time : 11:10 - 11:25
Biography:
Abstract:
- WORKSHOP
Session Introduction
Tanya Dixit and Sriharsha Allenki
Qualcomm, India
Title: Deep Learning – A beginner’s guide to start coding neural networks and apply in areas of computer vision and natural language processing
Time : 11:25 - 12:10
Biography:
Abstract:
- Workshop
Chair
Tanya Dixit & Sriharsha Allenki
Qualcomm, India
- Computer Science and Technology | Machine Learning | Big Data, Data Science and Data Mining | Big Data Analytics | Business Intelligence | The role of AI & Machine Learning in Medical Science | Deep Learning | Object Detection with Digits | Computer Vision and Image Processing | Pattern Recognition | Robotic Process Automation (RPA) | Natural Language Processing (NLP) and Speech Recognition | Deep Learning Frameworks
Chair
Niladri Shekhar Dutta
Ericsson, UAE
Co-Chair
Abbas M Al-Bakry
University of Information Technology and Communications, Iraq
Biography:
Abstract:
Jayatu Sen Chaudhury
American Express, India
Title: Machine learning applications in credit card domain
Time : 13:10 - 13:40
Biography:
Jayatu Sen Chaudhury is the Vice President, Global Commercial and Merchant Data Science and Head of Enterprise Digital & Analytics India for American Express, India. Prior to this role, he was the Head of Global Information Management, Big Data Labs & Advanced Risk Capabilities. He has been a part of American Express since 2001, working in the various decision science functions for both US and international markets. He has earned his PhD in Financial Economics from IGIDR, Economic Research Institute funded by the Central Bank of the Country (Reserve Bank of India). Prior to joining American Express, he has worked in decision science for two years each in GE Capital and ICICI Bank.
Abstract:
Given the huge volumes of data available (both structured and un-structured) for American Express card members, American Express has adopted machine learning in all its core business processes of credit and fraud risk management, marketing analytics and operations. Work entailed building in-house data warehouses with right level of privacy controls and then using state of art machine learning algorithms from open sources to solve unique business problems across various business verticals. Adoption of machine learning has ensured building of robust economic models leveraging the best possible information, delivering the highest predictive power with utmost accuracy. The models are updated at the highest possible frequency ensuring the models incorporate the most recent information. This has led to significant improvement in the controls for fraud risk and also improved the targeting of appropriate segments with far higher accuracy in marketing. As a part of the presentation, 3-4 actual use cases of core American Express processes and how machine learning has completely changed the game will be discussed. Discussion will also include the new areas where company is thinking of doing research and bringing the best value for its card members.
Niladri Shekhar Dutta
Ericsson, UAE
Title: The advent of big data analytics in the world of ICT and digital
Time : 13:40 - 14:10
Biography:
Niladri Shekhar Dutta is a seasoned professional with more than 13 years of global consulting experience. He is a Consulting Practitioner with focus on operations and transformation consulting for top-tier telecommunication operators globally. He has worked in more than 30+ consulting engagements in varied culture and markets across Western Europe, Middle East, North and Central Africa, India and New Zealand. His expertise is primarily around C-level advisory, digital transformation, digital enterprise architecture, business and operational process management, IT operational strategy, digital risk and revenue management consulting. He is responsible for driving consulting business across the MEA region for Ericsson and is involved in both sales and delivery. He has his MBA in Marketing and Finance from Symbiosis, Pune, India and is an Engineering graduate in Electronics from University of Nagpur, India. He is presently also undergoing a specialized PG program from MIT Sloan and Columbia facilitated by Emeritus on Digital Business.
Abstract:
With the advent of technology transformation in the fast changing and ever evolving world of Information, Communications and Technology (ICT), the importance of data is supreme. This is often being referred to as big data and is perhaps the single most entity which forms the backbone of any major transformation within any large global corporation across industries. Data is no longer being looked and used as a tactical medium for storage or operations; on the contrary it becomes extremely strategic in nature. In fact the 3 main pillars of today’s disruptive world of digital are driven by big data, IoT and cloud. Out of which big data is the nucleus of transformation. In the world of digital, this is very well centered on three main life cycle entities. They are the customer, the product and the revenue. Each of these, i.e. customer life cycle, product life cycle and revenue life cycles behave very differently from one another. The practical emphases of data in each of these entities are also very different and unique. The concepts of big data within these 3 life cycles are core to the change we witness in the world of digital. Each data entity centered on these life cycles is instrumental in C-level decision making and major change management that happens within the organization. The data element acts as a central aspect to strategic decisions whether it comes to newproduct/service development or behavior of customer or user data, appreciation or acknowledgement of revenue. All use cases around big data will be largely centered on these and any specific case would be a secondary derivation of the above. With big data being so strategic in nature a large part of the focus has now shifted to data extraction and normalization to ensure meaningful information is extracted and utilized for business benefits by customers. Like the traditional mindset used to be, focus was largely around data operations and reporting. We will soon see a world where we cannot live without any form of data and in truest sense the phrase big data would essentially be big and super imposed in all aspects of our lives, right from our behavior, buying and consumption of products and services to distribution of our resources. The extraction and transformation of data for key benefits will be very much a business as usual thing, without which survival will become questionable within ICT industry, especially whilst looking at the concept of digital disruption. This article largely focuses on the key aspects of the same within the world of ICT and how a corporation is heavily dependent on such aspects for generation of its sales and management of its operations.
Manoj Mishra
Union Insurance, UAE
Title: Data virtualization - Using data virtualization for an integrated analytics platform
Time : 14:10 - 14:40
Biography:
Abstract:
Eman AbuKhousa & Najati Ali-Hasan
UAE University, UAE
Title: Predictive big data analytics and healthcare fraud - From detection to prevention
Time : 14:40 - 15:10
Biography:
Eman Abu Khousa is a Researcher-Instructor (Big Data Applications) at the College of Information Technology, UAE.
Najati Ali Hasan is an experienced health information technology (IT) professional with 25-year experience in the field. Najati is an expert in advising GCC clients on strategies for selections & implementations of health IT with focus on achieving demonstrable clinical, operational and financial benefits. Najati is well versed in the revenue-cycle-management (RCM) field with knowledge of the various nuances and requirements of GCC countries. Najati’s other areas of expertise include smart use of health IT for enhanced patient experience, EDI, data analytics and applications of Artificial Intelligence/Machine Learning (AI/ML) in healthcare. Najati has co-authored three articles for conferences and journals – one having received a best-paper award. Najati’s work experience spans top USA medical centers to world class suppliers of health IT.
Abstract:
Tilila El Moujahid
Microsoft Corporation, UAE
Title: Using genomics cloud platform and machine learning for genome variant analysis
Time : 15:10 - 15:40
Biography:
Abstract:
Abbas M Al-Bakry
University of Information Technology and Communications, Iraq
Title: Computer aided diagnosis In cloud environment based on multi agents system
Time : 16:00 - 16:30
Biography:
Abstract:
Rohit Agarwal & Gaurav Pawar
Mobisy Technologies Pvt Ltd, India
Title: An overview of deep learning based object detection techniques in retail domain
Time : 16:30 - 17:00
Biography:
Gaurav Pawar has completed his BE degree in Electronics and Telecommunication with more than 3 years of practical hands-on experience in computer vision and machine learning. He is specialized in building quick prototypes using python environment by leveraging GPU platform. He has expertise in using popular deep learning libraries such as TensorFlow, PyTorch and Keras. Currently, he is interested in solving data science problems in Indian retail industry using images and other source of data.
Abstract:
Sharan Kumar Santhanakrishnan & Rakhsanth Rammohan
St.Josephs’s College of Engineering, India
Title: Efficient way for detecting and tracking of object irrespective of speed of the motion
Time : 17:00 - 17:30
Biography:
Abstract:
Aisha Al Owais
Sharjah Center for Astronomy and Space Sciences, UAE
Title: Deep learning - An application of machine learning to classify images
Time : 17:30 - 18:00
Biography:
Abstract:
Session Introduction
Jayatu Sen Chaudhury
American Express, India
Title: Machine learning applications in credit card domain
Biography:
Abstract:
Niladri Shekhar Dutta
Ericsson, UAE
Title: The advent of big data analytics in the world of ICT and digital
Biography:
Abstract:
Chair
Abbas M Al-Bakry
University of Information Technology and Communications, Iraq