• 01

    Keynotes

    • Ashtaang AI - Eight Layers of an AI Stack for Complex Ecosystems by Dr. Shailesh Kumar

    • Adopting AI in Enterprises by Dakshinamurthy V Kolluru, PhD

    • AI and Ethics by Toby Walsh, PhD

    • Applying AI to Real World Use Cases by John Montgomery
  • 02

    Demo Talks

    • Value of Analytics is in Consumption - Operationalize It by Saptarishi Dutta

    • Conversion as a Service: Challenges and opportunities for Legacy System Migration by Ian Ghent

    • Responsible AI with Azure Machine Learning by Mehrnoosh Sameki, PhD

    • Improving Your Data Visualization Flow with Altair and Vega-Lite by Rachel House

    • How Does Data Automation Change Working Lives? by Simon Asplen-Taylor and Torgil Hellman
  • 03

    Data Engineering & MLOps

    • Non-Parametric PDF Estimation for Advanced Anomaly Detection by Kuldeep Jiwani

    • Privacy-Law Aware ML Data Preparation by Venkata Pingali, PhD

    • Supply Path Optimization in Video Advertising Landscape by Ujwala Musku

    • A Spurious Outlier Detection System For High Frequency Time Series Data by Soham Chakraborty, PhD

    • AI in Manufacturing - Improving Process using Prescriptive Analytics by Upasana Roy Chowdhury and Aravind Kondamudi

    • Machine Learning and Data Governance in Telecom Industry by Sharmistha Chatterjee

    • How to Maximize Business Value from Data Science by Simon Asplen-Taylor and Torgil Hellman

    • SQL for Data Science by Duhita Khadepau

    • Why you Need Data Warehouse Automation Now More than Ever by Bryan Thomas

    • Empower your Organization with Data Driven AI by Prof. Carol Hargreaves

    • Building a Network Analysis App in Python by Ian Hansel

    • Journey of Jakarta Smart City from Data Analytics Perspective: Building Advanced Analytics & Data Science Capabilities by Juan Intan Kanggrawan
  • 04

    Data Visualization

    • Text Extraction from Images Using Deep Learning Techniques by Rajesh Shreedhar Bhat and Pranay Dugar

    • Learning Maps from Geospatial Data Captured by Logistics Operations by Dr. Manjeet Dahiya

    • Imagededup - Finding Duplicate Images Made Easy! by Dat Tran and Tanuj Jain

    • The Four Keys to Data Storytelling by Isaac Reyes
  • 05

    Deep Learning

    • On-Demand Accelerating Deep Neural Network Inference via Edge Computing by Darshan Ganji and Deepesh Agrawal

    • Coronavirus: Through The Lens Of AI by Parthiban Srinivasan, PhD

    • Deep Reinforcement Learning Based RecSys Using Distributed Q Table by Ravi Ranjan

    • Rethinking Object Detection by Alisher Abdukhaev

    • AI Singapore's Journey into the World of Federated Learning by Jianshu Weng, PhD
  • 06

    Machine Learning

    • Indian Sign Language Recognition (ISLAR) by Akshay Bahadur

    • CRESST:Complete Rare Event Specification using Stochastic Treatment by Debanjana Banerjee

    • AI-in-a-Box: Demystifying the Future of Businesses by Ashish Malhotra

    • Automated Ticket Routing for Large Enterprises by Priyanshu Jain

    • Internalizing Machine Learning by Akshay Dixit

    • Simplify Experimentation, Deployment and Collaboration for ML and AI Models by Kuldeep Singh

    • Metamorphic Testing for Machine Learning Models with Search Relevancy Example by Vinayaka Mayura G G

    • Model Interpretability and Explainable AI in Manufacturing by Pooja Balusani

    • Privacy Preserving Machine Learning Techniques by Amogh Kamat Tarcar

    • Unsupervised Learning Approach for Identifying Retail Store Employees Using Footfall Data by Soumya Jain

    • Machine Health Monitoring with AI by Sri Vallabha Deevi, PhD

    • Quantization To The Rescue: An Edge AI Story by Ashwathi Nambiar

    • Machine Learning with Spark by A M Aditya

    • Don’t Ask for Trust, be Trustworthy: Building Trust Infrastructure for AI by Pia Andrews

    • Playing Peek-a-Boo on a Unified Analytics Platform by Ian Ghent

    • Machine Learning as a Service: Challenges and Opportunities by Shou-De Lin, PhD

    • Dask-image: Distributed Image Processing for Large Data by Genevieve Buckley

    • Reinforcement Learning: Concepts, Challenges and Opportunities by Dr. Ankur Narang

    • AI for Good - an Ideal or a Necessity? by Ethel Karskens

    • Data Science and Machine Learning At Scale by Hugo Bowne-Anderson, PhD

    • Accessible AI and ML for the Data Scientist by Graham Williams, PhD
  • 07

    NLP

    • Accelerating NLP Model Training and Deployment with PyTorch by Prasanth Pulavarthi

    • How to Operationalize Ethics in Data and AI by Angela Kim

    • Uncover Hidden Business Insights from Unstructured Data by Dr. Lau Cher Han

    • Natural Language Querying for Industry Grade Data Analytics Systems by Piyush Arora, PhD

    • Data Augmentation for NLP by Anuj Gupta, PhD

    • Normalizing User-Generated Text Data by Piyush Makhija
  • 08

    Research Frontiers

    • Developing a match-making Algorithm between Customers and Go-Jek Products! by Gunjan Dewan

    • Portfolio Valuation for a Retail Bank using Monte Carlo Simulation and Forecasting for Risk Measurement by Kavita Dwivedi

    • How to Establish a Successful, Sustainable and Scalable Data Science and AI Capability within an Organisation by Dr. Alex Antic

    • Human-Machine Partnerships to enable Human and Planetary Flourishing by Theresa Anderson, PhD

    • AI Developments and Applications for Healthcare by Ethan Tu

    • Researchmap: a Platform for Science of Science Policy by Dr. Noriko Arai