20 - 20 October 2021

Conversational AI in Retail Summit Conversational AI in Retail Summit schedule

Conversational AI for Enterprise Summit

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  • Time in PDT

  • 08:00
    Jinjin Zhao


    Jinjin Zhao - Senior ML Scientist/Science Lead - Amazon

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    Jinjin is a Senior Applied/ML Scientist at Amazon with 6+ years of research and practical application experience in a few domains (Supply Chain, Retail, Advertising and recommender systems, Voice assistant, AI Education). Jinjin has been devoted to AI Education since early 2018. During the past 2-3 years, she was able to publish 10 research papers at various conferences (ACM [email protected], AAAI, EducationDataMining, etc) and there are more under double-blind peer review. She is enthusiastic at research and bringing researchers together for bigger wins and also leads the dWdt initiative for mentoring and guiding junior scientists and engineers for their growth in research and practical AI applications.


  • 08:05
    Shivani Poddar

    How to Transform your Company with Conversational AI - 3xing Product, People and Processes

    Shivani Poddar - Tech Lead (Machine Learning/AI) - Facebook

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    How to Transform your Company with Conversational AI - 3xing Product, People and Processes

    Why is it that traditionally the area where assistants are most valuable are corporate/enterprise settings, however the most pervasive are personal assistants? Why is it that the average Joe who has never had a human assistant is expected to leverage a digital one? Answering these questions leads us to one of the most underutilized markets in the world of conversational AI, Enterprise/Corporates. With this talk I explore the next leaps that conversational AI can make (and is making), from building contextualized transcriptions, note taking, meeting summaries to scheduling meetings and reminders, how conversational AI is ready to disrupt businesses of today and tomorrow. While we explore the possibilities of tomorrow, I will also chalk out some of the pitfalls of these systems, and how to hedge against them both as a developer and as a business employing these conv AI systems.

    Key Takeaways:

    • State of conversational Assistants for Enterprise Use cases

    • Key areas where conv AI is ready to disrupt the market

    • Pitfalls of these conv AI systems and how to avoid them

    Shivani is an machine learning engineer on the Facebook Assistant team working on both the product and research arms around machine learning reasoning for assistants, and multi-modal assistants of the future. Before Facebook, she was at Carnegie Mellon University, where she helped build the CMU Magnus system for social chit chat ground up for the first wave of Amazon Alexa Prize Challenge. She has also published work on modeling user psychology, and building argumentation systems that help in negotiation. Her research background spans across-disciplines such as computer science, psychology and machine learning.

  • 08:30
    Bala Maddali

    Training Agents to Better Inform Customers

    Bala Maddali - Director, Conversational AI - Verizon

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    Bala Maddali is an Innovator, strategist, influencer, insights-driven leader who is passionate about the convergence of people, products, experience, and technology. He is currently leading the Ai-driven conversational Experiences for the Verizon Consumer group. He has a proven track record in leading and driving strategy, transformation, and commercialization of next-generation digital experiences, conceptualizing and enabling industry best and first solutions to delight customers and enable sustainable growth and value. He has 12 patents in the area of mobile and TV second screen convergence experience, social TV, and voice & gesture-based app interactions. Recipient of 4 CXO 100 Awards and multiple product launch awards.


  • 08:55
    German I Parisi

    Using AI to Discover Consumption Patterns

    German I Parisi - Director of Applied AI - McD Tech Labs, McDonald's

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    Toward Lifelong Conversational AI

    Conversational agents have become increasingly popular in a wide range of business areas. Prominent examples of applications that have been transforming speech-to-speech interactions are Amazon’s Alexa, Apple’s Siri, and McDonald’s voice-activated drive-thru. Companies from various industries are now exploring new ways of building products and services that rely on robust natural language interactions. A major technical challenge is how these solutions can efficiently incorporate new knowledge and increase performance over time while confining computational cost and addressing the current limitations of artificial learning systems designed to perform best in benchmark datasets. In this talk, I will introduce and discuss state-of-the-art machine learning technology in conversational AI with the ability to acquire, fine-tune, and transfer knowledge from large and continuous streams of data. The systems can learn in correspondence to novel interactions or the necessity to enrich domain-specific knowledge and logic. I will focus on scalable deep learning models for end-to-end natural language understanding and hybrid approaches to lifelong conversational agents in multiple application domains.

    German I. Parisi is the Director of Applied AI at McD Tech Labs in Mountain View, California, a Silicon Valley-based research center established by McDonald’s Corporation to advance the state of the art in AI-powered technology systems for customer interaction and support. He is also an independent research fellow of the University of Hamburg, Germany, and the co-founder and board member of ContinualAI, the largest research organization and open community on continual learning for AI with a network of over 600 scientists. He received his Bachelor's and Master's degree in Computer Science from the University of Milano-Bicocca, Italy. In 2017 he received his PhD in Computer Science from the University of Hamburg on the topic of multimodal neural representations with deep recurrent networks. In 2015 he was a visiting researcher at the Cognitive Neuro-Robotics Lab of the Korea Advanced Institute of Science and Technology (KAIST), South Korea, winners of the 2015 DARPA Robotics Challenge. His main research interests include human-robot interaction, continual robot learning, and neuroscience-inspired AI.

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  • 09:20


  • 09:30
    AI Lead

    Enhancing the Post Purchase Landscape & Customer Care

    AI Lead - - Sama

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    Sama provides accurate data for ambitious AI. The company’s high-quality training data platform is trusted by the world’s most ambitious organizations to develop accurate machine learning models. Used by over 25% of Fortune 50 companies such as Walmart, Google and Microsoft, Sama specializes in image, video and sensor data annotation and validation for machine learning algorithms in industries including manufacturing and robotics, bio and medtech, autonomous vehicles, entertainment, e-commerce, retail, and agriculture.

  • 09:55

    Improving the Shopping Journey: From Recommendations to Orders

  • 10:20


  • 10:45


  • 10:55

    PANEL: How Can We Deliver Seamless Experiences with Conversational AI in Retail?

  •  Jayesh Govindarajan


    Jayesh Govindarajan - SVP of Data Science & Engineering - Salesforce

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    Jayesh is the Senior Vice President of Data Science and Engineering at Salesforce. He leads Einstein for CRM -- a suite of machine learning services to automate customer interactions and enhance productivity for sales and service agents. Jayesh also oversees Einstein Bots, a platform that powers conversational AI and automation across all Salesforce clouds . Jayesh joined the company in 2016 through the acquisition of his data science startup, MinHash. Prior to founding his own company, Govindarajan spent nearly a decade in engineering leadership roles at Oracle and Avaya. He received his Master’s in Computer Science from WPI.

  • Jean-Leah Njoroge


    Jean-Leah Njoroge - Director - Conversational AI - Lowe's Companies

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    Passionate about harnessing AI & Machine Learning at the intersection of Science, Technology and Engineering, Jean has led teams and developed models for leading universities and Fortune 100s – benefitting customer experience, patent mining, manufacturing and more. Leveraging big data analytics, she has guided technology innovation from idea to commercialization and/or implementation and partnered with C-Suite and Executive stakeholders to mastermind innovation that supports business strategy.

    Currently, as a Director of Conversational AI as Lowe’s, Jean where she is focusing on the development and optimization of Lowe’s Conversational AI models such as Natural Language Understanding, Named Entity Recognition, and Text Mining to create a seamless customer dialogue experience.

  • 11:30


  • 12:00


Conversational AI for Enterprise Summit

Conversational AI for Enterprise Summit

20 - 20 October 2021

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