AI algorithms, systems and platforms provide tremendous opportunity to impact almost all aspects of our lives. Such systems are already in wide use in diverse industries including HR, manufacturing, finance, retail and healthcare. While optimizing traditional quality metrics like accuracy, precision, performance, one needs to make sure that the systems are Fair, Explainable and Transparent. These features are key to develop trusted AI. In this talk, we will go over these topics with examples, algorithms, results and open areas which require attention from AI Research community.

Sameep Mehta is a senior manager and STSM at IBM Research India. He joined IBM Research after completing his Ph.D. from The Ohio State University in 2006. His current research interests are in AI & Machine Learning, He spends lot of time to develop algorithms and systems to infuse trust, privacy and safety in AI Systems and Platform.

Dr. Shankar Ramamoorthy is currently working as Chief Customer Success Officer at Harman Connected Services , helping the Software Enabled Business of Harman. He was earlier Quality Business Partner –at Amdocs. - where he evangelized and implemented 40 patented Test Management Framework machine using BI/Analytics.

Dr Shankar is a TQM ( Total Quality Management) professional, who has spent much of his 26-years career managing change and improving software Quality Engineering efficiency through Data and Metrics driven Quality Management Systems.

He believes in evangelizing , coaching and mentoring test teams through inspirational leadership.

Shankar has a vast experience in setting up Test COE( Centre of Excellence),and has successfully carried out 6 rollouts on TPI/TMMI/Test Maturity frameworks for several companies.

He has handled the entire gamut of testing landscape right from Pre- Sales, Sales, Delivery and instituted a process temper in his earlier assignments.

Empathy is the ability to put ourselves in someone else’s shoes. Some theories and better understand empathy as a natural process, but there are positive and negative aspects to it. In the same way, we can imitate a smile; we can imitate a frown and expressions of outrage.

In the words of – Albert Einstein “Empathy is patiently and sincerely seeing the world through the other person’s eyes. It is not learned in school; it is cultivated over a lifetime.

So how do we cultivate empathy and be certain that empathy is inculcated in our society and also in the development process of new products and services?

Rapid progress in artificial intelligence has enhanced the human factor of machines. Like humans, machines can be influenced by humans with diverse ethical values. The A.I. consciousness of tomorrow should have the capacity for intelligent, emotional interactions and relationships.

It doesn’t seem unreasonable that a machine would have an acute emotional component. Our society could not survive if our empathic abilities: goodwill, humanity, and altruism were removed from our human experience, so why should we remove these abilities from a machine

To unite and enhance our life experiences with the technology we must create, develop, think or most likely “feel” this new revolution from an emotional point of view. These conscious items, robots, entities will not only be crafting or recoding our relationships to medicine but also means of transportation and communications technology, especially the internet.

In looking at AI’s brief history, represented through innovations like chatbots, we come across ethical challenges that we must overcome to ensure AI is not adversely moulded, to harm users.

At its core, AI can bring out the best and worst in humanity. This increases the need to ensure AI is introduced in the right situations and in the right way. Just as society is built upon a contract of expected behaviour, we will need to design AI systems to respect and fit with our social norms.

Karma Bhutia is Founder / CEO of iShippo.com & Demi Solutions – A Serial Entrepreneur, Public Speaker, Influencer, Mentor, StartUp Enthusiast with interest in Data Science, Natural Language Processing, Machine Learning, Artificial Intelligence, IoT and Robotics. He co-founded SourceN – a successful software consulting firm; which was acquired by HolidayIQ & Quikcilver - Amazon & Accel funded companies.

Karma is an inventor with patents to his name & was featured by Forbes in 2016. He is a recipient of “NICT” award for innovation & outstanding contribution in Information Technology. He is an eNorthEast awardee for eGovernance & citizen service delivery, mBillionth-2015 awardee for Mobile Governance and Manthan-2015 awardee.

linkedIn: in/karmabhutia

twitter @iambhutia

Assisted or Supervised models of machine learning are a great boon to automate many mundane tasks in ERP world. Supervised model combined with hypothesis models helps in creating “situations” and in predicting possible outcomes to a given situation. Simple cases of Critical Value Methods and p-value methods can be used to provide insights before user takes an action in ERP. In this presentation we will use the above methods to solve a problem of how invoices are matched with vendor payments.

Use Case:
Account Receivable accountants have to match incoming payments with open customer invoices that the payments are intended to clear. This is a laborious task riddled with many incorrect matches and subsequent reversals and painstakingly slow process.

Using Machine Learning capabilities, the matching engine can learn from accountants’ past manual actions, capturing much richer detail of customer- and country-specific behavior and use hypothesis models to propose possible outcomes.

Sr Director - S4HANA Product Management APJ Drive innovation and S4HANA adoption in APJ Market Unit 4 US Patents in Netweaver area (Technology Utility patents) 2 Business cases authored in IIMA Regular speaker in technology events

Convolutional Neural Networks (CNNs) are powerful models that achieve impressive results for image classification. The presenter will go over the overall architecture of a CNN and its practical applications.

Senior Manager with 19 years of I.T. experience in IT/Business Consulting, Strategy and Delivery management in the Analytics space. Winner of the IT NEXT CIO 100 award – an all INDIA Leadership Talent Hunt program, INSEAD Business School Alumni and graduated from ISB in Certificate in Business Analytics program. Invited as a speaker in multiple Data Science summits.

World over AI (aka artificial intelligence) is taking businesses by storm on account of a disruptive takeover of various human oriented tasks by AI enabled software programs. While several domains including healthcare, driverless cars, games etc are talked of in context of AI, I would speak on an area where Indian IT industry has pioneering achievements,namely, software engineering.

My talk will focus on various aspects of software engineering activites in IT services, right from software testing and valiation, to software maintenance to infra maintenance. Primarily I will talk of the current trends in use of AI for each of the software engineering activities like Infra support, Testing and Software Maintenance. While AI is the theme, there will be coverage of using data based software analytics to intelligently augment current software engineering processes.

Practical case studies of AI based automation will be presented in context of AI in Software validation, Software Maintenance and Infra Automation.

Srinivas Padmanabhuni is a Ph.D. in Artificial Intelligence. He is the chief Mentor for Tarah technologies an AI consulting company through which he does marquee training and strategic consulting work in AI for enterprises, a pressing need now in the market. Srinivas Padmanabhuni is currently founding CityMandi.com a next generation AI enabled smart B2B startup in Food Tech. He has been conferred the title of Eminent Engineer by IEI for his lifetime contributions. He is also a mentor and Governance Board member of Totalstart. an entrepreneurship development organization. He specializes in areas of software engineering, services computing, business process management, artificial intelligence, big data and machine learning. He has consulted for several Global 2000 enterprises, delivered over 100 invited talks, has around 7 granted & 15 filed patents, over 70 international referred publications, and one published book by Wiley to his credit. He is the Past President of ACM India. Earlier, he was a Principal Research Scientist and Associate Vice President at Infosys where he overlooked the university innovation ecosystem, alongside research and innovation group in Infosys Labs. He has conducted several CXO level technology led innovation workouts at over 50 marquee customers. He has won several awards including the excellence award for Innovation at Infosys, Research excellence award at University of Alberta, and Merit award at IIT Kanpur

He has worked in multiple startups out of USA, Canada and India. Dr. Srinivas holds a doctorate degree in computing science from University of Alberta, Edmonton ,Canada, specializing in AI. Prior to Ph.D. he secured his B.Tech and M.Tech in computer science from Indian Institutes of Technology at Kanpur and Mumbai respectively.

Specialties: innovation, research, design thinking, machine learning, AI, mining software repositories,thought leadership,global software development,mentoring,technology architecting, soa, bpm

Conversational systems (chatbots) are increasingly becoming popular for providing timely, low cost and personalized experience while supporting customers. Large companies like Google and IBM have thrown their hat into the game by providing frameworks. However, based on our first hand experience in developing these for our Fortune 500 customers, lot of the magic happens in the ML models, and these models get increasingly complex when you want to engage customers for multiple turns in a specific business workflow. In this presentation, I will detail the lay of the land, our experience, and some best practices for developing these systems.

Samik Raychaudhuri, Ph.D., currently Director of Data Sciences and ML at [24]7.ai Pvt. Ltd., has over 15 years of experience developing products in predictive analytics and mathematical optimization. Prior to joining [24]7, he was leading the research of the analytics engine of Oracle Crystal Ball, an enterprise product for risk modeling and analysis. Samik has an M.S. and Ph.D. in Operations Research from University of Wisconsin, Madison, USA, and a B.Tech. degree in Industrial Engineering and Management from Indian Institute of Technology, Kharagpur, India. In [24]7, he is involved in designing and prototyping cutting edge technology solutions for real-time prediction problems at scale using big data, machine learning and AI, in the customer support domain.

The Speach will focus on the adoption of various AI/ML technologies in the enterprise in various verticals like Telecom, Manufacturing in digital analytics to claims processing and impact on the customer Experience mapping to various problem classes in AI space. We will also present TechM acumos Platofrm, an Open source eco system which we are building to provide a way of sharing models in AI and software infrastructure required for rapid development and deployment. We will also try to touch upon the bottlenecks in AI adoption and possible solutions.

Second part will focus on how AI can make improvement in areas Natural Language Processing, Natural Language Understanding, Text Analysis, Image Recognition and Video Processing. Cognitive systems can help parse the meaning of content and make decisions based on those meanings. artificial intelligence is transforming document management In many ways

Automatic classification and processing of huge doc corpus Data Recognition and extraction from variety of documents Advanced security, Data Protection and GDPR support Text Analytics, Entity Extraction and Data insights Improve Content Findability and user experience

20+ years of experience as a Technologist building software products for valley companies (Sun, Yahoo!, eBay,Informatica), valley startups(i2 SRM/rightworks), partnering with startups like Hazelcast, currently building digital platforms for Enterprise customers and leading AI adoption for enterprise.

20+ years of rich expertise in global consulting, architecture & transformation engagements helping clients visualize their digital future, translating business needs, desired outcomes into technology strategies and digital enterprise architecture plans to keep pace in digital age thus controlling the costs and mitigating business risks while building and adapting cutting edge AI solutions

Expertise in digital enterprise architecture, consulting assignments resulting in business transformation, innovation, accelerating strategies to unlock opportunities, optimize processes and uncover cost savings with implementation road map positioning various solutions like Cloud, Mobile, Social, IoT, Cognitive, Automation, Machine Learning and Big Data Analytics across domains.

Worked for Enterprise like Apple, Citibank, cisco, PACCAR, NISSAN, AJG, Guardian, Vodafone, AT&T, GE, Franklin Templeton, Maybank, OCBC Bank, M&T Bank, HP, McGraw-Hill, Delta Dental & many other customers

A gathering of people have long held considerable power. Whether the purpose was for demonstrations, protests, civilian movements or for more peaceful purposes, related to corporate events and business gatherings. Marketers have always been interested in getting a sense of the crowds, whether it was to get an approximate headcount of the gathering or to get their finer demographical attributes. However, the means to get this information have been limited and there have been several technological challenges in implementing robust, non-intrusive solutions around this.

The use of video footages to count people offers some potential, but until recently wasn’t adequately solved. With an appropriate solution, crowd counting through video can provide powerful traffic flow measurement with real-time or periodic reporting. Combining traffic data with other operational data provides end users with the methodology to accurately increase customer service during key selling periods, reduce costs during slow selling periods, and determine the effectiveness of advertising expenses and promotional campaigns.

A number of solutions have been developed using OpenCV and Machine learning to count people and none of them is perfect. To boost the system's accuracy, researchers have switched to Deep-learning AI that takes advantage of neural networks to process images. This innovation enables video to move beyond security applications and to provide valuable business data in the areas of Gaming, Retail, Transportation, Education, Financial, Government etc.

This talk will present some of these more sophisticated solutions with some examples and a working demo of a prototype.

Abhishek Vagrecha is a Data Science Engineer with experience in Deep Learning and Enterprise product research and development. He is passionate about technology, data and building solutions for real-world business problems. At present he is working in the areas of AI – Deep learning applied to Audio and video analysis. Earlier, he has worked at Edgeverve systems in the process and video mining space, Semantic modelling and Conversational engines. Currently, working at Gramener in AI Labs.

Ranjan Balappa, currently working as a Senior Data Specialist at Gramener. He has worked on data visualization, Machine learning, and Deep learning. He is also Co-founder of company “Wx + b” where we conduct Bootcamp in colleges for students and teachers on Machine learning/Deep Learning. His keen interest is to make our agriculture better with AI.

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 within the overall global economy. While Industrial Revolution 1.0 introduced mechanization and steam engines, Version 2.0 ushered in mass production and assembly line. Industrial Revolution 3.0 was all about software, automation and computers. We are now making rapid strides into the next phase, a phase which is going to witness digital disruptions in the form of Artificial Intelligence, Virtual Reality, Block-Chain and Robotics. The dawn of this new era promises to be very different from its previous versions. The pace of growth is tremendous and is powered by a strong foundation of Data. 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 a summary of digital disruption in the clinical world with special reference to the field of Machine Learning

Shankar has more than 22 years of experience in the field of IT Services, BPO & CRO, devoted primarily to establishing Large Offshore Development Centers with a major focus on the areas of People, Process and Technology. An expert in implementing business operations and in strategizing talent retention programs, Shankar has been highly instrumental in launching long-lasting delivery platforms that provide strong quality of service with consistently predictable outcomes.

Current Role - As Vice President (FSPx India - Biostats, CDM and Analytics), Shankar has end to end responsibility for Business Functions in India related to the FSP functions which include Biostats Programming, Data Management Programming, Statistics, Predictive Analytics, Visual Analytics, Technology, Innovation & Customer Support.

Qualifications -
- Holds a PGDGM from NMIMS, Mumbai
- Certified in Machine Learning & Analytics
- Trained in Six Sigma Black Belt
- Certified SCRUM Master

Specialties: Strategic Leadership (Defining & Implementing the vision, mission and goals of the India Unit), General Management - Metrics Driven Management across Business Functions, Workforce Analytics, Talent Acquisition, Financials and Administration, Innovation (Launching Innovation Platforms on Artificial Intelligence, Machine Learning and Robotic Process Automation)

AI is by far is the most important topic that’s being spoken about as the game changer of our times. Businesses are taking advantage of the advancement in algorithms and technology not just to improve productivity but also disrupt the way business is being done. At the same time there is a lot of hype & confusion around terms/ concepts like machine learning, deep learning, NLP, NLG all being touted as on form of AI or other. The focus of this session would be on developing a quick common understanding of these areas followed by a few business scenarios & demos where NLP, Machine Learning, Intelligent Automation etc have been used to solve some key challenges, moving towards attaining true AI.

Shivakumar Krishnamurthy is the Co-Founder of Prescience Decision Solutions, a company focused on providing solutions that weave ML and AI in every aspect of the data value chain to help companies become more Prescient. His first brush with neural networks was over 20 years back and has spent most of his time since then in the technology space, prior to founding Prescience. He has a B.Tech degree from IIT – Delhi and MBA from IIM – Lucknow