Prof. Jordi Garcia
Associate (tenured) Professor
Design and definition of a global distributed data management architecture for smart cities, through a Fog-to-Cloud (F2C) resources management framework. Considering all data lifecycle stages, from creation to consumption, including data preservation. Effective data collection and storage for efficient real-time data access and Big Data processing.
Prof. Jordi Garcia Almi単ana
Associate (tenured) Professor
Polytechnic University of Catalonia , Spain
Campus Nord Modul C6 – 120 C/ Jordi Girona, 1-3 08034 Barcelona
Dr. Salman Ahmed Shaikh
GeoFlink: A Distributed and Scalable Framework for the Real-time Processing of Spatial Data Streams
Apache Flink is an open-source system for scalable processing of batch and streaming data. Flink does not natively support efficient processing of spatial data streams, which is a requirement of many applications dealing with spatial data. Besides Flink, other scalable spatial data processing platforms including GeoSpark, Spatial Hadoop, etc. do not support streaming workloads and can only handle static/batch workloads. To fill this gap, we propose GeoFlink, which extends Apache Flink to support spatial data types, indexes and continuous queries over spatial data streams. To enable efficient processing of spatial continuous queries and for the effective data distribution across Flink cluster nodes, a gird-based index is introduced. GeoFlink currently supports spatial range, spatial kNN and spatial join queries on several spatial data types including point, line and polygon. In this talk, I will discuss several existing scalable spatial data processing frameworks and will go through the technical details of GeoFlink and its applications.
Salman Ahmed Shaikh
Artificial Intelligence Research Center (AIRC)
National Institute of Advanced Industrial Science and Technology (AIST)
Tokyo Waterfront 2-4-7 Aomi, Koto-ku, Tokyo 135-0064 JAPAN
Email: [email protected]
Prof. Dr. Noman Islam
Professor, Head MS/PhD Program and Head of Department
Title: Deep Learning for Computer Vision and Natural Language Processing
Abstract: Deep Learning is an advanced form of machine learning comprising multiple processing units (neurons) connected in various layers. The information is processed through these layers in hierarchical fashion like a distillation pipeline. In this workshop, we will go through various real world examples of deep learning in the domain of computer vision and natural language processing. We will review convolutional neural networks (CNN) and long short term memory model (LSTM), and apply them for solving various problems. All the practicals will be done in Tensorflow 2.0.
Affiliation: Professor, Head MS/ PhD Program and Head of Department (HoD),
Iqra University (http://iqra.edu.pk/iuk)
Engr. Sumair Hamza
Sr. Software Engineer & Seasoned Trainer
Title: Understanding Mono-Repo architecture and optimizing scalability of applications
Abstract: Scaling an application is one of the core challenges in Software development, here you’ll have an e-commerce app all ready to handle thousands of users but then one day you put up a black Friday sale and out of nowhere get an influx of users which your system isn’t ready to handle and the overall site goes down. Mono-Repos can help us break our application into separate individual chunks or modules, which would run independently from one another and would give you an overall look and feel of a single app. This helps in load distribution and create stateless components. In this talk, we’ll talk about the basics of what a Mono-Repo architecture and how it can help us in application scaling. How big companies like Netflix, Hobsons, etc. are using them to handle the influx of users on their site. We’ll look into an extensive example of how things are working on the back and some getting started tools to help you get started quickly.
Affiliation: 10Pearls, Digital Transformation Consulting Services and Solutions (https://10pearls.com)
Dr. Nawab Muhammad Faseeh Qureshi
Title: Smart Grid
Affiliation: Sungkuynkwan University, South Korea
Dr. Manzoor Ahmed Hashmani
Title: IoT enabled blockchain for Halal Food trackability and traceability.
Affiliation: Associate Professor at University of Technology PETRONAS, Malaysia. Head (High Performance Cloud Computing Center) Head (Data Science Cluster Department of Computer and Information Sciences) Universiti Teknologi PETRONAS, Malaysia
Zul H. Kazani
Innovation Evangelist, Aspiring Neuroscientist, Strategist, Speaker, Practitioner
Title: Electroceuticals: from Molecules to Electrons – Era of the Exponential “You”
Affiliation: X-Founder / CEO – RKaz Technology Partners (M) Sdn Bhd President Globall Operations – The Brain Stimulation Clinic, USA Co-Founder – InfoFacturers