Splash Spring 2019 is May 4-5, 2019!

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ESP Biography

NIKHIL BHATTASALI, M.S. Computer Science (AI + Bio-Robotics)

Major: Computer Science

College/Employer: Stanford

Year of Graduation: 2019

Picture of Nikhil Bhattasali

Brief Biographical Sketch:

I'm a masters student studying Artificial Intelligence and Bio-Robotics under Computer Science. For undergrad at Stanford, I studied Artificial Intelligence under Symbolic Systems!

Hailing from the D.C.-area (yay, East Coast!), I attended Thomas Jefferson High School for Science and Technology, where I did research in the Automation and Robotics Lab.

At Stanford, you'll likely spot me at entrepreneurship events or at one of the many beautiful outdoor study spots having an intense discussion with my friends.

I'm excited for SPLASH this year, especially because I'll be sharing a topic near and dear to my heart with a group of interested, bright young minds!

Past Classes

  (Clicking a class title will bring you to the course's section of the corresponding course catalog)

B7306: Neuroscience and Artificial Intelligence in Splash Spring 2019 (May. 04 - 05, 2019)
Neuroscience aims to understand the mind, while artificial intelligence aims to recreate it. This course seeks to integrate knowledge from each field and shed light on their relationship. We’ll survey three topics: (1) vision and convolutional neural networks, (2) locomotion and reinforcement learning, and (3) hippocampal episodic memory and deep memory networks.

M5891: From Code to Consciousness: The Quest for Artificial General Intelligence in Splash Spring 2017 (Apr. 22 - 23, 2017)
In a time when buzzwords like “artificial intelligence” and “machine learning” are tossed around frequently, why don’t intelligent agents like Siri and Amazon Alexa seem very … well, intelligent? Sci-fi media has long promised worlds with true AI beings, like JARVIS in "Iron Man" and HAL in "2001: A Space Odyssey". But our current reality is much tamer, and it seems like such technologies are a long way off. Artificial general intelligence, or AGI, is the study of how computers can be made to be truly as intelligent as (or more intelligent than) a human being. What is the state of AGI today? Why is it such a hard problem? What does the future hold? And is AGI really something we should strive for, anyways? In this interdisciplinary overview, we traverse neuroscience, computer science, and philosophy to explore the fascinating topic of AGI. We start from the inception of “thinking machines” and watch how the field has progressed to the current state-of-the-art. We take a look at the human brain, how it works, and what amazing feats it can perform. Finally, we ponder what current and future AI technologies mean for us and, indeed, for our species.