• 18:00

    Welcome & Introduction

  • 18:05
    Sergey Karayev

    Presentation: AI Assistance for Grading Handwritten Free Responses

    Sergey Karayev - Co-Founder & CTO - Gradescope

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    AI Assistance for Grading Handwritten Free Responses

    Gradescope by Turnitin is a web application that enables instructors to grade their existing paper-based exams and homework, via scanning student work in first. Our goal is to save the instructors as much time as possible with AI-assistance. For example, we group answers to fill-in-the-blank questions by content, such that instructors grade each unique answer only once, instead of grading the same answer many times, as on paper. In this talk, Sergey will share recent work on AI-assistance for short-answer questions, where several sources of complexity prohibit an easy solution. First, student handwriting can be messy and often mixes math and science notation and diagrams with text. Second, grouping similar answers together is a known challenge in natural language processing. Third, grouping answers also depends on instructor intent and their grading rubric, which tightly links potential ML solutions to UX interfaces.

    Sergey Karayev’s goal is to develop and deploy AI systems to improve human life. In 2014, he finished a PhD in Computer Science at UC Berkeley and co-founded Gradescope, an AI-assisted platform for instructors to grade exams, homework, programming projects, and labs. In 2018, Gradescope was acquired by Turnitin, where Sergey now heads development of AI for STEM. Sergey is also an instructor of a weekend program and University of Washington course on Full Stack Deep Learning.

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  • 18:20
    Kian Katanforoosh

    Presentation: AI Career Pathways

    Kian Katanforoosh - Lecturer - Stanford University / Workera

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    AI Career Pathways

    Companies everywhere are building AI teams, but it’s still unclear what aspiring machine learning engineers, data scientists, and software engineers should focus on when applying for AI jobs. This talk results from more than 100 interviews with data science and machine learning leaders. It illustrates the importance of self-assessment in making good career choices and walks you through different types of AI organization, different roles within them, the tasks you can work on, and the skills recruiters are looking for in each role.

    Kian Katanforoosh is a technology entrepreneur and lecturer at Stanford University, where he teaches Deep Learning in the Computer Science department with Prof. Andrew Ng. He is the founder of Workera, a company that measures the skills of data scientists, machine learning engineers, and software engineers, and serves them AI career opportunities, and is a founding member of deeplearning.ai. He co-created the Deep Learning Specialization on Coursera with Andrew Ng. From 2014 to 2016, Kian co-founded and co-led Daskit, a French start-up developing in-classroom ed-tech solutions for universities.

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  • 18:35
    Vinod Bakthavachalam

    Systems for Feedback and Novelty in Deep Learning: A Case Study From Coursera

    Vinod Bakthavachalam - Senior Data Scientist - Coursera

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    CourseMatch: Using Word Embeddings for Scaling Access to Online Education during COVID

    At Coursera our mission is to provide everyone, anywhere access to high quality education to transform their lives. As the COVID crisis forces teaching and learning to shift online, there is an acute need to support both universities and students at this time. To enable universities and students to take advantage of the large number of high quality, online courses on Coursera, we have utilized word embeddings to map on-campus university catalogs to their online Coursera equivalents, ensuring students can continue their studies and universities can support their programs. During this presentation we will review the theory behind world embeddings and discuss this novel application in greater detail.

    Vinod Bakthavachalam is a Data Scientist working with the Content Strategy and Enterprise teams, focusing on using Coursera's data to understand what are the most valuable skills across roles, industries, and geographies. Prior to Coursera, he worked in quantitative finance and studied Economics, Statistics, and Molecular & Cellular Biology at UC Berkeley.

  • 18:50

    Q&A with the Speakers

  • 19:00


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