MBZUAI Talks Webinars

The role of AI in Revolutionizing the Robotics Industry

Date: November 3rd 
Time: 6pm – 7:15pm GST

Deployment of autonomous vehicles on public roads promises increases in efficiency and safety, and requires evaluating risk, understanding the intent of human drivers, and adapting to different driving styles. Autonomous vehicles must have intelligent situation awareness and behave in safe and predictable ways without requiring explicit communication.

This talk describes new machine learning algorithms that enable increased capabilities for autonomous vehicles. Specifically, we will address how to integrate risk and behavior analysis in the control look of an autonomous car. I will also describe how Social Value Orientation (SVO), which captures how an agent’s social preferences and cooperation affect their interactions with others by quantifying the degree of selfishness or altruism, can be integrated in decision making and provide recent examples of developing and deploying self-driving vehicles with adaptation capabilities.

Speaker: Professor Daniela Rus

Board Member @ MBZUAI

Moderator: Dr. Behjat AlYousuf

EVP Outreach & Engagement and Acting Chief Operating Officer @ MBZUAI

 

Evolution of Artificial Intelligence: Past, Current and Future

Date: October 6th 
Time: 6pm – 7:15pm GST

In this talk, I will highlight the major developments and breakthroughs in AI over the past decades and glance into its potential future. As we move through the history of AI developments, we will look at the inception of AI as a field, its historical perspective in the context of other scientific disciplines, major breakthroughs and notable events.

I will discuss in detail recent breakthroughs in deep learning and discuss the state-of-the-art deep learning-based methods in computer vision, image understanding, natural language processing, autonomous driving, game play and reinforcement learning. Finally, I will discuss the limitations of AI, possible future research directions and challenges associated with AI research.

Speaker: Dr. Munawar Hayat

Computer Vision Department @ MBZUAI

Biometric Recognition: How do I Know Who You are?

Date: September 1st
Time: 6pm – 7pm GST

Biometric recognition refers to the automated recognition of individuals based on their biological and behavioral traits such as fingerprint, face, iris, and voice. The first scientific paper on automated fingerprint matching was published by Trauring (1963). Since then, progress in representation and recognition approaches has enabled biometric systems to accurately recognize individuals in real-time in applications ranging from unlocking personal smartphones to large-scale national ID and law enforcement systems. Despite this progress, a number of challenges and lack of understanding continue to inhibit the full potential of biometrics. In this talk I would like to share with you some of these challenges, requirements, opportunities for basic and applied research, and some ongoing projects in my laboratory.

Speaker: Professor Anil K Jain

Board Member @ MBZUAI

Moderator: Professor Ling Shao

EVP & Provost @ MBZUAI

 

How Does AI Help Fight the COVID-19 pandemic?

Date: August 4th
Time: 6pm – 7pm GST

There is no doubt that Artificial Intelligence (AI) is becoming an integral part of our everyday life. During the COVID-19 pandemic, AI has been extremely crucial in tackling not only the healthcare consequences of the disease but also other important implications which affect social, economic and policy making decisions. In this talk, I will present some innovative AI solutions which helped fight the pandemic on different scales. I will discuss how and where AI help

  • Detect, respond and recover from the pandemic
  • Predict infection
  • Facilitate healthcare solutions
  • Accelerate research to understand and treat COVID-19

Finally, I will touch on issues which emerge with using AI in fighting the pandemic such as privacy, the need for big data, generalisability of solutions, data noise, and human acceptance.

I illustrate these developments from my own work in: (i) imaging the liver and related organs for (non-alcoholic) fatty liver disease, steatohepatitis, liver cancer, and COVID recovery; and (ii) breast cancer. I conclude by looking forward to just a few of the many opportunities that are ripe for development.

Speaker: Dr. Mohammad Yaqub

Computer Vision Department @ MBZUAI

The role of AI in Revolutionizing the Robotics Industry

Date: November 3rd
Time: 6pm – 7:15pm GST

Deployment of autonomous vehicles on public roads promises increases in efficiency and safety, and requires evaluating risk, understanding the intent of human drivers, and adapting to different driving styles. Autonomous vehicles must have intelligent situation awareness and behave in safe and predictable ways without requiring explicit communication.

This talk describes new machine learning algorithms that enable increased capabilities for autonomous vehicles. Specifically, we will address how to integrate risk and behavior analysis in the control look of an autonomous car. I will also describe how Social Value Orientation (SVO), which captures how an agent’s social preferences and cooperation affect their interactions with others by quantifying the degree of selfishness or altruism, can be integrated in decision making and provide recent examples of developing and deploying self-driving vehicles with adaptation capabilities.

Speaker: Professor Daniela Rus 

Board Member @ MBZUAI

Moderator: Dr. Behjat AlYousuf 

EVP Outreach &Engagement and Acting
Chief Operations Officer @ MBZUAI

Evolution of Artificial Intelligence: Past, Current and Future

Date: October 6th
Time: 6pm – 7:15pm GST

In this talk, I will highlight the major developments and breakthroughs in AI over the past decades and glance into its potential future. As we move through the history of AI developments, we will look at the inception of AI as a field, its historical perspective in the context of other scientific disciplines, major breakthroughs and notable events.

I will discuss in detail recent breakthroughs in deep learning and discuss the state-of-the-art deep learning-based methods in computer vision, image understanding, natural language processing, autonomous driving, game play and reinforcement learning. Finally, I will discuss the limitations of AI, possible future research directions and challenges associated with AI research.

Speaker: Dr. Munawar Hayat  

Computer Vision Department @ MBZUAI

Biometric Recognition: How do I Know Who You are?

Date: September 1st
Time: 6pm – 7pm GST

Biometric recognition refers to the automated recognition of individuals based on their biological and behavioral traits such as fingerprint, face, iris, and voice. The first scientific paper on automated fingerprint matching was published by Trauring (1963). Since then, progress in representation and recognition approaches has enabled biometric systems to accurately recognize individuals in real-time in applications ranging from unlocking personal smartphones to large-scale national ID and law enforcement systems. Despite this progress, a number of challenges and lack of understanding continue to inhibit the full potential of biometrics. In this talk I would like to share with you some of these challenges, requirements, opportunities for basic and applied research, and some ongoing projects in my laboratory.

Speaker: Professor Anil K. Jain 

Board Member @ MBZUAI

Moderator: Professor Ling Shao

EVP & Provost @ MBZUAI

 

How Does AI Help Fight the COVID-19 pandemic?

Date: August 4th
Time: 6pm – 7pm GST

There is no doubt that Artificial Intelligence (AI) is becoming an integral part of our everyday life. During the COVID-19 pandemic, AI has been extremely crucial in tackling not only the healthcare consequences of the disease but also other important implications which affect social, economic and policy making decisions. In this talk, I will present some innovative AI solutions which helped fight the pandemic on different scales. I will discuss how and where AI help

  • Detect, respond and recover from the pandemic
  • Predict infection
  • Facilitate healthcare solutions
  • Accelerate research to understand and treat COVID-19

Finally, I will touch on issues which emerge with using AI in fighting the pandemic such as privacy, the need for big data, generalisability of solutions, data noise, and human acceptance.

I illustrate these developments from my own work in: (i) imaging the liver and related organs for (non-alcoholic) fatty liver disease, steatohepatitis, liver cancer, and COVID recovery; and (ii) breast cancer. I conclude by looking forward to just a few of the many opportunities that are ripe for development.

Speaker: Dr. Mohammad Yaqub

Assistant Professor

AI in Medical Imaging: With Examples from Cancer, COVID, and the Metabolic Syndrome

Date: July 7th
Time: 6pm – 7pm GST

Medical imaging has been developing rapidly providing important information to clinicians. It is increasingly quantitative – delivering precise numbers rather than pictures that rely on interpretation by a clinician. AI underpins medical image analysis because: medicine is complex so doctors need assistance; and because doctors are drowning in data when they need information.

I illustrate these developments from my own work in: (i) imaging the liver and related organs for (non-alcoholic) fatty liver disease, steatohepatitis, liver cancer, and COVID recovery; and (ii) breast cancer. I conclude by looking forward to just a few of the many opportunities that are ripe for development.

Speaker: Professor Sir Michael Brady

Interim President @ MBZUAI

Moderator: Professor Ling Shao

EVP & Provost @ MBZUAI

 

AI in Medical Imaging: With Examples from Cancer, COVID, and the Metabolic Syndrome

Date: July 7th
Time: 6pm – 7pm GST

Medical imaging has been developing rapidly providing important information to clinicians. It is increasingly quantitative – delivering precise numbers rather than pictures that rely on interpretation by a clinician. AI underpins medical image analysis because: medicine is complex so doctors need assistance; and because doctors are drowning in data when they need information.

I illustrate these developments from my own work in: (i) imaging the liver and related organs for (non-alcoholic) fatty liver disease, steatohepatitis, liver cancer, and COVID recovery; and (ii) breast cancer. I conclude by looking forward to just a few of the many opportunities that are ripe for development.

Speaker: Professor Sir Michael Brady

Interim President @ MBZUAI

Moderator: Professor Ling Shao

EVP & Provost @ MBZUAI

 

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