This keynote will articulate the need for a thriving innovation engine for emerging markets. It will shed light on what are the key ingredients required to spur innovation that solves problems, improves lives of people, and fuels the economic engine of emerging economies. It will help us understand how these ingredients work and blend together to create the magic of innovation learning from other parts of the world. Furthermore, this talk will also delve into observed trends in various technologies considering the future we are heading towards.
University of Bahrain
I show the relationship between handling information from two different perspectives; classical and quantum. This comparison show that IT, computer Science, mathematics and physics are integrated sciences. I review some basic tools that are used in computations and their corresponding in the quantum domain. I introduce an application that is based on the main principles of quantum mechanics. Finally, I will discuss the possibility of secure communication via freezing the travelling information between any two users in a quantum network.
Universiti Teknologi PETRONAS
The pipeline infrastructure has reached over three million km globally and the investment continue to grow at about $40 billion a year for expansion and maintenance of the assets. The aging infrastructure, IT systems complexity and capabilities to leverage growing amounts of data continue to be challenging as it is estimated that less than 25% of the data generated for any given pipeline is used to formulate data-driven decisions.
Big data analytics (BDA) and machine learning (ML) capabilities has been deployed quite substantially to reduce downtime and potential for human errors in the life cycle of a pipeline operation. Such analytics rely on the conceptual understanding of big data, framework, infrastructure and physical execution of these systems. This discussion is intended to explore the practical aspects of implementing the technologies as well as the issues and challenges of big data namely the velocity, volume, veracity and variety in managing the pipeline integrity for future research.
Associate Professor & Associate Dean,
Habib University, Pakistan.
Optimal control (OC) is concerned with finding control laws for dynamic systems which achieve the desired control while optimizing a cost or reward function. Optimization is a unifying theme between optimal control and machine learning (ML) as much of ML deals with making a learning agent behave in such a way as to either maximize a reward criterion or minimize an error criterion. This is especially true for reinforcement learning (RL) where the learning agent takes actions to maximize a well-defined cumulative reward.
Reinforcement learning has been successfully used for developing programs that learn to play certain board games, such as Backgammon, at expert or even champion level. It has come into more prominence recently due to spectacular successes of Alpha Zero which learns to play Chess, Shogi and Go by playing against a copy of itself.
In this talk, we will give a general overview of optimal control and various techniques for solving optimal control problems. This will be followed by an overview of reinforcement learning along with a discussion of the type of problems for which this technique is suitable.
As Dynamic programming–and Bellman's equations which arises from the application of DP – provide a common framework for solving OC as well as RL problems, a portion of the talk will be devoted to algorithms for solving to Bellman's equation.
Fast University, Pakistan
Multi-label and Multi-target learning are challenging research problems due to the fact that each example may belong to a varying number of classes and targets respectively. This problem can be further aggravated by high dimensionality and complex correlation among labels. In this talk, I will discuss research problems in these areas including state of the art techniques. I will also discuss some recent contributions of our research group at FAST NUCES, Karachi Campus in these areas with applications in image / video retrieval, text retrieval etc.
Mohammad Ali Jinnah University, Pakistan
A recognized and innovative professional having vast experience as a Senior Administrator, Academician, Researcher, and IT / IS consultant for large scale complex business problems, particularly related to E-Governance, Educational Planning, IT and Technical & Vocational Education.
He graduated in Computer System Engineering and completed his MS and PhD from Computer Sc., New York, USA.Currently he is President of Mohammad Ali Jinnah University. He worked as IT consultant insome National & International organizations and also involve into Designing, planning and management of IT institutions, and offshore software organizations. His primary research interest is Ubiquitous Computing, Multimedia & Graphics, Knowledge Management, Mobile &Adhoc Networks, and E-Health, E-Education and Learning and Teaching theories.
He worked on several projects with USAID, CIDA, World Bank and EU. He developed several policy and strategic documents on Educational reforms with and without technology.