We are PhD students from Harvard University here to answer questions about artificial intelligence and cognition. Ask us anything!

EDIT 3

Thank you everyone for making this so exciting! I think we are going to call it a day here. Thanks again!!

EDIT 2:

Thanks everyone for the discussion! Keep the discussion going! We will try to respond to some more questions as they trickle in! A few resources for anyone interested.

Coding:

Introduction to Programming with CodeAcademy.

More advanced Python programming language (one of the most popular coding languages).

Intro to Computer Science (CS50)

Machine learning:

Introduction to Probability (Stat110)

Introduction to Machine Learning

Kaggle Competitions – Not sure where to start with data to predict? Would you like to compete with other on your machine learning chops? Kaggle is the place to go!

Machine Learning: A Probabilistic Perspective – One of the best textbooks on machine learning.

Code Libraries:

Sklearn – Really great machine learning algorithms that work right out of the box

Tensorflow (with Tutorials) – Advanced machine learning toolkit so you can build your own algorithms.




Hello Redditors! We are Harvard PhD students studying artificial intelligence (AI) and cognition representing Science in the News (SITN), a Harvard Graduate Student organization committed to scientific outreach. SITN posts articles on their blog, hosts seminars, creates podcasts, and meet and greets with scientists and the public.

Things we are interested in:

AI in general: In what ways does artificial intelligence relate to human cognition? What are the future applications of AI in our daily lives? How will AI change how we do science? What types of things can AI predict? Will AI ever outpace human intelligence?

Graduate school and science communication: As a science outreach organization, how can we effectively engage the public in science? What is graduate school like? What is graduate school culture like and how was the road to getting here?

Participants include:

Rockwell Anyoha is a graduate student in the department of molecular biology with a background in physics and genetics. He has published work on genetic regulation but is currently using machine learning to model animal behavior.

Dana Boebinger is a PhD candidate in the Harvard-MIT program in Speech and Hearing Bioscience and Technology. She uses fMRI to understand the neural mechanisms that underlie human perception of complex sounds, like speech and music. She is currently working with both Josh McDermott and Nancy Kanwisher in the Department of Brain and Cognitive Sciences at MIT.

Adam Riesselman is a PhD candidate in Debora Marks’ lab at Harvard Medical School. He is using machine learning to understand the effects of mutations by modeling genomes from plants, animals, and microbes from the wild.

Kevin Sitek is a PhD candidate in the Harvard Program in Speech and Hearing Bioscience and Technology working with Satra Ghosh and John Gabrieli. He’s interested in how the brain processes sounds, particularly the sound of our own voices while we're speaking. How do we use expectations about what our voice will sound like, as well as feedback of what our voice actually sounds like, to plan what to say next and how to say it?

William Yuan is a graduate student in Prof. Isaac Kohane's lab in at Harvard Medical School working on developing image recognition models for pathology.

We will be here from 1-3 pm EST to answer questions!

Proof: Website, Twitter, Facebook

EDIT:

Proof 2: Us by the Harvard Mark I!

Submitted July 29, 2017 at 11:31AM by SITNHarvard
via reddit https://www.reddit.com/r/IAmA/comments/6qbw5f/we_are_phd_students_from_harvard_university_here/?utm_source=ifttt

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