AI Seminar

Artificial Intelligence Seminar
for exceptionally passionate students.

Talks given Exclusively by PhDs, Alumni and Students from

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Creativity & Artificial Intelligence

Friday, Feb 11th 4pm EST

Aarshavi Shah

MIT

Computer Science

Personal Background

Aarshavi has previously worked on research projects in ML and AI at MIT Media Lab and CSAIL (MIT), and Space Systems Lab. She currently develops products at Gritay, working towards creating experiences and tools that enable humans for creative human expression. 

Talk Brief

Ever wondered how Artificial Intelligence can finish a music piece by Beethoven? Or how Da Vinci would have painted San Francisco?
Let's find out the how Artificial Intelligence can be creative.

We will discuss

- AI generated Media
- GANs.

AI vs Corruption

Saturday, Feb 12th 4pm EST

Jorge Nam Song

Stanford University

Management Science & Engineering

Personal Background

Jorge has a background in Finance and Data Science. Since the beginning of the COVID-19 pandemic, he has been using data science and machine learning to advise on policy recommendations and combat corruption in Paraguay, creating a more transparent business ecosystem in Paraguay.

Talk Brief

Corruption is still one of the biggest challenges to prosperity for many countries. Often times, when we talk about fighting corruption, we think about better leaders and authorities. However, research has demonstrated that Artificial Intelligence can become a critical tool in this fight, serving as an objective anti-corruption agent.

We will discuss

- Corruption as a societal issue.
- Common initiatives to fight corruption.
- Advancement of technology for transparency
- Hope for AI in the anti-corruption field.
- Examples of AI in anti-corruption.

AI + Animal Welfare

Sunday, Feb 13th 4pm EST

Abhishek Garg

Stanford University

Computer Science

Personal Background

After doing his undergrad and graduate degree from Stanford in CS, Abhishek went on to work at large technology companies in the Bay Area: Facebook and Apple. More recently, he started working for startups. He is now a full-stack engineer at an early stage startup.

Talk Brief

We must be aware of the dangers of AI, but we should also recognize how it can be used for good. This talk is about applying AI for animal welfare. We will go over two case studies: helping find lost dogs and preventing the poaching of African elephants.

We will discuss

- Finding and tracking lost dogs 
- Facial recognition
- Challenges:
- Having a big enough data set of quality images 
- Lack of funding
- Preventing the poaching of African wild elephants. 
- Analyze visualizations of sonograms using AI
- Identify the quantity of elephants in a given area
- Detect signs of poaching

AI for
Social Good

Friday, Feb 18th 4pm EST

Jorge Nam Song

Stanford University

Management Science & Engineering

Personal Background

Jorge has a background in Finance and Data Science. Since the beginning of the COVID-19 pandemic, he has been using data science and machine learning to advise on policy recommendations and combat corruption in Paraguay, creating a more transparent business ecosystem in Paraguay.

Talk Brief

AI is a technology that fascinates the entire world. We see AI in development of artificial robots or virtual assistants such as Siri and Amazon, and even self-driving autonomous vehicles and google translate. However, AI is more than that and can do more. AI is the next generation tool that will help the world solve some its biggest societal issues and create a more sustainable world.

We will discuss

- Common AI technologies
- United Nations’ 17 Sustainable Development Goals
- AI for Social Good
- Examples of AI for social good

AI for Disease Diagnosis

Sunday, Feb 27th 4pm EST

Nishit Srivastava

Cambridge University

Bioengineering / Mechanobiology

Personal Background

Nishit has a background in Engineering and biology and did his PhD from university of Cambridge. Currently, he’s a scientist in Paris, France where he is using deep learning and AI for studying behavior of cells and predicting outcome of diseases. 

Talk Brief

There are so many diseases, particularly Cancer, where an early detection can improve the survival manifolds. AI and deep learning have transformed biology and disease studies tremendously and are now being used routinely to predict diseases and cellular behavior. In this talk, we’ll see how deep learning and AI are being utilized in biology and for diagnosing and preventing diseases.

We will discuss

- Various deep learning and AI modules for detection of cells
- How AI and deep learning are being used for prediction of diseases
- Future development of state-of-art techniques for diagnosis and treatment of diseases

Introduction to Explainable AI (XAI)

Friday, Mar 4th 4pm EST

Wilfried Bounsi

Oxford University

Computer Science and Applied Mathematics

Personal Background

Wilfried implemented a Knowledge Graph construction pipeline from educational materials and improved document classification quality by 95% through the usage of state of the art heterogeneous Graph Neural Networks. He co-founded two startups: Quidely and Skylon.

Talk Brief

For Artificial Neural Networks (ANNs) to be safely used in critical applications such as recruiting tools, judiciary decision support systems, and clinical decision support systems, explainability is not only a desirable property, but it is also - or in some cases will soon become - a legal requirement. As a result, a resurgence of scientific interest in the field of eXplainable Artificial Intelligence (XAI) has been observed in recent years. This talk aims to provide a succint introduction to XAI.

We will discuss

- Interpretable ML
- Taxonomy of Explanatory methods
- Post-hoc Explanatory Methods
- Self-Explanatory Methods
- Open source XAI librairies
- Challenges in XAI
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Learn from the best

Access a network of AI experts, researchers, industry leaders, and top university alumni. The seminar has talks exclusively by PhDs, Alumni and Students from MIT, Stanford, Oxford, Cambridge and Harvard.

Meet like-minded peers

Join a network of exceptionally passionate peers who are preparing for college too (these are people who will be your classmates in college or who you'll work with in personal projects).

Adava University around the world

students & instructors

Classes designed around you

We’ve had students
from 11 to 19 years old
Our students are usually
6th to 12th graders
  • No programming skills
  • ​Basic programming skills
  • ​Advanced programming skills
Talks will be interactive, allowing students to ask questions and adapting the talk to their pace

Check out another related program:

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