Event Schedule

The topic would cover the importance of extracting intelligence from both internal and external data which is unstructured in nature, with realworld business case studies and examples, methodologies to manage and handle the unstructured data life cycle management, tools and technologies, the future of unstructured data and its impact to organizations.

Philip Varughese is a Data Science Leader. Philip brings around 15 Years of rich and extensive cross functional experience and expertise in the IT field with 13+ Years of Experience in Enterprise Data Strategy, Analytics, BigData, Business Intelligence and Digital Transformation with Experience in Consulting, Research, Enterprise Performance Management, Delivery & Centre of Excellence.

He is an invited Key-Note Speaker on BigData, Analytics, Digital Transformation & Cyber Intelligence in various National & International Conferences and Leading Academia.

Philip has handled key business management roles with IBM, CSS Corporation, Chimera Technologies, Seventhsense Technologies and Socratic Learning Inc. at Domestic and International level.

Qualification:

Philip is a Post Graduate in Mathematics and, also holds Master of Philosophy in Mathematics and Diploma in Computer Applications

A few of the institutes, conferences and organizations, where Philip regularly speaks:

i. International Cyber Security & Policing Conference
ii. DRDO & CSI National Conference for IT in Defence
iii. ICAI – Institute of Chartered Accountants of India national conferences
iv. Indian Institute of Science, Bangalore
v. Vellore Institute of Technology (VIT University)
vi. Manipal University, Bangalore
vii. Amrita University, Bangalore
viii. Jain University, Bangalore
ix. T. John Group of Institutions, Bangalore
x. Mount Zion Group of Institutions, Kerala
xi. New Horizon Group of Institutions, Bangalore
xii. Gyan Ganga Group of Institutions, Bhopal, Madhya Pradesh
xiii. XIME – Xavier's Institute of Management & Entrepreneurship
xiv. Don Bosco Institute of Technology, Bangalore

In past few decades, Business Process Transformation has been one of the strategic focus areas for most of the Business Houses, primarily to enhance their productivity & efficiency. This also helps them laying foundation of growth & new opportunities at the same time. After successfully leveraging strategies like, outsourcing, low cost locations & Business process optimization, now the focus is on "Technology". Exponential growth in Technology advancement clubbed with focused approach from IT Industry, is resulting in suite of amazing solution patterns having capability to solve almost every other possible use case falling under Business Process Transformation. Industry has observed exponential growth and evolution of Robotic Process Automation (RPA) technologies in last 2-3 Years. The growth will continue for next couple of Years with primary focus on innovation and stabilization. Currently, I see the following emerging trends as RPA plus in this space,
1. Virtual workforce as-a TRUE Service "Human workforce leveraging digital workforce as and when needed, with the right alignment of RPA Infrastructure and Product licensing strategy…"
2. Intelligent RPA execution "Robots to execute Business processes with little more intelligence beyond pre-defined business rules…"
3. Image Reading Capability "Leveraging AI to read Images beyond typed text…"?
4. Un-structured natural language text reading Capability "Making sense out of natural language in Industrialized manner…"
5. Evolution of true Digital Platform "Providing capability to seamlessly integrate multiple technologies on a common platform…"
6. Extending RPA to other areas "Applying RPA beyond Business Process Automation…"
7. Business domain specific Solutions "Moving away from one-size-fit-all Approach…"

I plan to include live demonstrations of most of these concepts along with its commercial implications…

With 21+ Years of experience in planning, developing and implementing avant-garde information solutions, for both custom and product based Client strategic Initiatives, Nishant Goel is currently leading his own Venture called “BOT mantra” as founder & CEO. Having worked extensively in Process Automation area and associated with Industry leading brands like Tata, GE, Accenture & Mphasis, He comes with detailed understanding of corresponding technology stack, industry trends, implementation nuances and commercial implications.

The world is witnessing the advent of Industrial Revolution 4.0 and its phenomenal impact on nature, human race, industry and many other spheres. This is an upheaval that is helping mankind make giant leaps across the global economy. We are now making rapid strides where we are witnessing digital disruptions in the form of Artificial Intelligence, Robotic Process Automation, IOT and Block-Chain. The dawn of this new era promises to be very different from its previous versions. At the heart of this digital revolution is Data Explosion and this has led to reimagining the way business is conducted across different Industry segments.

This latest reincarnation has a lot to contribute to the world of Clinical Research. And this session attempts to provide examples of digital disruption in the world of Clinical Drug Discovery and Development.

While AI and Automation helps in implementing an innovation Solution, TRIZ helps in the process of innovation. The combination of TRIZ along with AI an RPA tools can help in building a framework of Innovation and not just productivity and cost saving.

TED speaker, Author of "Business Innovation & Transformation using TRIZ" with Worlds number one Quality Publisher, Innovator of 'Athena' the worlds most intelligent Chatbot, a result oriented Quality & Project Management professional, with 11 years of experience in IT, Supply Chain and Consulting across 18 countries in Asia, Europe and Asia. Published numerous white papers and articles on TRIZ, innovation and project management with renowned journals, featured twice on ASQ TV, Times of India, News Minute, Indian Express and other media. I hold the position of ASQ's Influential Voice of Quality with proven abilities in strategic planning, Project management,and improving efficiency of operations through Six Sigma and Lean Methodology.

Specialities: Six Sigma, TRIZ, Lean and IT Project Management, Supply Chain Management, Agile

The Digital evolution is not a myth! It is a reality. Industries have transformed from a rugged looking shop-floor to the state-of-the-art facilities. It encompasses the gamut of technologies ranging from mobility, robotics, sensors, big data, analytics, Industrial Internet of Things (IIoT), Artificial Intelligence (AI), Virtual Reality (VR), mechatronics, cyber-security and cloud computing in so-called 3rd technology platform. It's no longer a lame shop-floor with machines churning in and out as you'd imagine.

Perhaps, every machine will be packaged with sensors, IoT device capabilities to transmit data back and forth to process information enabled via Wi-Fi. These are known as smart machines. These smart factories are evolving with the capacity to be completely autonomous and take appropriate actions. Thus, industrial machines will be transcended into intelligent machines that are capable of thinking beyond human imagination as these cognitive systems are evolving. It will continue to transform Industries to be completely autonomous and not just automating processes. It's not a sci-fi movie; it's real and the transformation is happening here and now.

Prashant KUMAR is an AI Enthusiast and an author with 13+ Year of Experience in areas of in Business Transformation, Business / IT alignment, Merger and Acquisitions, Program Management Enterprise Architect & Business Intelligence, currently working on Digital transformation

By Qualification he is MS in Computer science with specialization in Artificial Intelligence and Intelligent Systems, He is an Alumnus of IIM Bangalore

Publication

Recently published a Book called Digital Transformation Industry 4.0

Discuss applications in ML and DL such as predictive analysis, computer vision, speech recognition and time-series

I will be covering how an organization can strategize and initiate RPA within their organization through the below steps.

1. Conceptualize an Operating Model for RPA in alignment with the existing model
2. How to discover which operational area has to be taken first for testing the RPA capability.
3. How to select RPA Tool and Delivery Partner
4. Build a POC for a minimum viable process
5. Strategize the RPA transformation and scaled it up
6. Establish a Centralized Command center for Support and maintenance

Jineesh is a well-known thought leader and well experienced project manager with over 10 years of experience in implementing highly innovative back-office technology solutions for large Investment Management, Banking and Insurance clients across US, Europe, Singapore, and UAE. After completing MBA in Finance & International Business from Marshall University, USA (2007), he worked with Cognizant Technology Solutions for more than 9 years and during his tenure he has been honored with "Frontline Leadership Award" in 2012, "Idea Champion" in 2013 and "Raising Star of Continental Europe" in 2014.

This topic will cover use cases that we are currently trying to tackle in primary healthcare. It is especially controversial since RPA has to work together with extremely skilled doctors. I will cover the approaches to take to identify the right use cases for RPA in general and a template for solutions.

Deep Learning Basics
1 What is deep learning?
2 Use-case driven understanding(Machine Vision and Natural Language).
3 The building blocks

• Neurons
• Activation functions
• Back propagation algorithm
• Optimization
• Adaptive learning

Deep Learning for Machine Vision
1 Introduction to problem and data-set
2 Working on the cloud, including keras and tensorflow
3 Building your first Deep Learning Model - Multi-layer Perceptron (MLP)

Convolutional Neural Networks (CNN)
1 Architecture and Concept of CNN(Convolution, Padding, Strides, Max-pooling and Dropouts)
2 Build your second Deep Learning Model - CNN [If time permits]
3 Tricks to improve your model

• Augment your training data
• Batch normalization