Global AI Student Conference December 2022

Introduction to Azure cognitive services in the Power Platform

I will talk in depth about azure cognitive services in the power platform a...

Panshak Koproda

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iShare Donation Platform

The best way is to adopt the idea of the sharing economy and decentralize ...

Jerry Lee

Andy Lum

Hok Lai Liu

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AI-voice-assistant-using-python

This session will explain how to build a voice assistant that will recog...

Anaam Sayeda

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AI Builder in Power Platform

Artificial Intelligence builder is one of the capabilities of Microsoft...

Shadrack Kiprotich

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Dive into AI and create your 1st bot

In this session, we will walk you through the basic concepts of AI. Get...

Tina Popli

Aditi Sharma

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Disaster Risk Monitoring Using Satellite Imagery

Learn how to build and deploy a deep learning model to automate the detec...

Kevin McFall

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Foundations of causal inference and open source causal analysis tools

Many key data science tasks are about decision-making. They require unders...

Emre Kiciman

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Smart Parking in Modern Cities: Challenges & Solutions

The presentation will address ML-related challenges of emerging intelligent...

Vadim Porvatov

Anastasia Martynova

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Breast Cancer prediction using automated ML

A mini-project related to « Breast Cancer prediction using AutomatedML »,...

Hadil Ben Amor

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AI in Tracking Air Quality

The session will showcase a Nairobi-based project using AI to track air...

Sifa Kinoti

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Introduction to Named Entity Recognition using Azure Language

Have you ever wondered how you can extract entities from unstructured text...

Konstantinos Kyriakos Sitistas

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Hybrid Model Approach for Real-Time Acoustic Anomaly Detection using Time Series

Detecting anomalous behaviours help to find new knowledge of a given phe...

Sahan Dissanayaka

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Towards Responsible AI

When we talk about AI, we usually mean a machine learning model that is...

Luis Beltran

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Data Science and AI in Africa: The Impact of Communities

In recent times, Data Science and AI is growing drastically within African...

Frank-Felix Felix

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Machine Learning at Green In Tech

Let's learn to develop sustainable solutions with machine learning to...

Nicolas Chavez

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Automating my Dog with Azure Cognitive Services

Like many terrier owners, I have a problem. My dog is overworked from the...

Matt Eland

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The 4 Types of Machine Learning

AI and Machine Learning are all the rage, but did you know that there are a...

Frank La Vigne

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Generate out of the world images with Azure and Stable Diffusion

Have you always wanted to have a photo in space, swimming through Atlantis...

Felipe Flores

David Lazaro

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Panel AI in education

TBA...

Kevin McFall

Gabriela de Queiroz

Noah Gift

Ajit Jaokar

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iShare Donation Platform

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The best way is to adopt the idea of the sharing economy and decentralize the donation process like AirBnB or Uber without bottlenecks. iShare is a platform to make use of Azure Cognitive services to match donors, students and volunteers quickly with AI.

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Jerry Lee

HD in Cloud and Data Center Administration Student, IVE Hong Kong

Andy Lum

HD in Cloud and Data Center Administration Student, IVE Hong Kong

Hok Lai Liu

HD in Cloud and Data Center Administration Student, IVE Hong Kong

AI Builder in Power Platform

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Artificial Intelligence builder is one of the capabilities of Microsoft Power Platform that enables developers to add intelligence to their business solutions. It is a component that is built on Power Platform. Citizen developers can leverage this tool by using pre-built AI solutions and also they can be able to build on custom solutions to enable fast delivery of their business services. Using this tool an organisation can save up to 300 hours per year on the manual processes.
The session willl involve a walkthrough of AI Builder and a demo on how you can improve the business processes using AI Builder. I will also get a chance to talk about the new updates on AI builder that came out of the Microsoft Ignite. A case scenario of a store that needs to track customers 500 sale receipts processed daily using an intelligent solutions. The demo will involve using custom AI solution.

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Shadrack Kiprotich

Microsoft MVP Business Applications

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Dive into AI and create your 1st bot

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In this session, we will walk you through the basic concepts of AI. Get ready to build your 1st AI-powered chatbot using Bot Services and Bot Framework composer. A chatbot is an AI-powered software application that simulates human-like conversations with actual humans through text or voice apps. With Azure Bot Framework Composer and Bot Service, you can design chatbots that are more than a communication tool. Bot Framework Composer is an open-source IDE that enables you to manage conversational experiences.

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Tina Popli

Gold Microsoft Learn Student Ambassador | Software Developer Intern

Aditi Sharma

Beta Microsoft Learn Student Ambassador

Foundations of causal inference and open source causal analysis tools

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Many key data science tasks are about decision-making. They require understanding the causes of an event and how to take action to improve future outcomes. Machine learning (ML) models rely on correlational patterns to predict the answer to a question but often fail at these decision-making tasks, as the very decisions and actions they drive change the patterns they rely on. Causal inference methods, in contrast, are designed to rely on patterns generated by stable and robust causal mechanisms, even as decisions and actions change. With insights gained from causal methods, the new, growing field of causal machine learning promises to address fundamental ML challenges in generalizability, interpretability, bias, and privacy.

In this talk, you will learn about the fundamentals of causal inference, including how a target question of cause and effect can be captured in a formal graphical model and answered systematically using available data. We will introduce a four-step causal modeling framework for analyzing decision-making tasks and walk-through code examples using the DoWhy, EconML libraries and ShowWhy no-code tools.

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Emre Kiciman

Senior Principal Researcher, Microsoft

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Smart Parking in Modern Cities: Challenges & Solutions

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The presentation will address ML-related challenges of emerging intelligent parking guidance systems: parking lot occupancy detection and parking space availability forecasting. Along with the general information regarding the topic, we intend to discuss recently conducted computational experiments worldwide and introduce our state-of-the-art results.

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Vadim Porvatov

MSc student at University of Amsterdam

Anastasia Martynova

NUST MISIS

Hybrid Model Approach for Real-Time Acoustic Anomaly Detection using Time Series

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Detecting anomalous behaviours help to find new knowledge of a given phenomenon since anomaly behaviours rarely occurred and give better insights to prevent those instances in the future. Usually, anomaly behaviours happen unexpectedly due to the unconscious nature of the objects. This project will directly or as a first insight helps to prevent happening severe anomaly behaviours generated in real-time via helping to diagnose them as early as possible.

Thus far, an increasing number of machine learning and deep learning algorithms have been developed to detect anomalies, but only a few applications focus on detecting acoustic anomalies
in real time. With respect to that, the core contribution of this research project is given by delivering an improved hybrid model architecture to capture more time series features for Real-Time Acoustic Anomaly Detection and enable it to use in the above
scenarios effectively.

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Sahan Dissanayaka

Final Year Computer Science Undergraduate at University of Colombo School of Computing

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Towards Responsible AI

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When we talk about AI, we usually mean a machine learning model that is used within a system to automate something. For example, a self-driving car can take images from sensors. A ML model can use these images to make predictions (example: the object in front of us is a tree). The car uses these predictions to make decisions (example: turn left to avoid the tree). We refer to this entire system as Artificial Intelligence.

This is just an example. AI can be used for anything, from insurance underwriting to cancer detection. The defining characteristic is that there is no limited human involvement in the decisions the system makes. This can create many potential problems and companies need to define a clear approach to the use of AI. Responsible AI is a governance framework intended to do exactly that.

Responsible AI can include details about what data can be collected and used, and how the models should be implemented, evaluated and monitored. You can also define who is responsible for the negative results of the AI implementation. You can define specific approaches and others more open to interpretation. They all seek to achieve the same thing: to create AI systems that are interpretable, fair, secure, and respectful of user privacy.

The objective of this session is to talk about the responsible use of Artificial Intelligence in the generation of fair, equitable and explainable machine learning models.

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Luis Beltran

Microsoft MVP

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Automating my Dog with Azure Cognitive Services

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Like many terrier owners, I have a problem. My dog is overworked from the constant need to monitor multiple streets to bark at squirrels or passers by. I'd like to free up more of his time and energy for snuggling and play but the outdoors must still be monitored. Thankfully, it turns out that much of what my dog does, Azure Cognitive Services can help with.

In this talk we'll use this absurd premise to explore progressively enhancing applications through the Azure Cognitive Services speech, vision, and text APIs. We'll look at object detection, facial APIs, text to speech, speech to text, and language understanding.

By the end of this session you'll have more of an understanding of what Azure Cognitive Services can do and the basics of how to interact with them from code so that you, like my dog, can take advantage of pre-trained machine learning models to enhance devote more of your energy to other areas.

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Matt Eland

Instructor at Tech Elevator

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Generate out of the world images with Azure and Stable Diffusion

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Have you always wanted to have a photo in space, swimming through Atlantis or soaring through the skies? Meet Stabble Difussion, a deep learning, text-to-image model that is primarily used to generate detailed images conditioned on text descriptions. With this model and Azure App Services you will learn how to create all kinds of amazing images of yourself and other people.

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Felipe Flores

Microsoft Learn Student Ambassador

David Lazaro

Microsoft Learn Student Ambassador

Panel AI in education

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TBA

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Kevin McFall

Learn image segmentation from a Master Instructor from NVIDIA's Deep Learning Institute

Gabriela de Queiroz

Principal Cloud Advocate - AI/ML/DS

Noah Gift

Founder at Pragmatic AI Labs and Duke Executive in Residence

Ajit Jaokar

Visiting fellow: Department of Engineering Science - University of Oxford and Course Director: Artificial Intelligence: Cloud and Edge Implementations - University of Oxford

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