Dr. Sarah Thomas

Professor
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Biography

Sarah Thomas is a Professor of Computer Science at Stanford University. She received her PhD in Computer Science from MIT in 2004. Her research interests include machine learning, artificial intelligence, computer vision, robotics, and natural language processing. She has published over 100 papers in top academic conferences and journals. She has also received several awards for his research, including the ACM SIGKDD Innovation Award, the NSF CAREER Award, and the Google Faculty Research Award. Professor Thomas is a passionate teacher and has won numerous teaching awards. She is also an active member of the computer science community and has served on several program committees and editorial boards. She is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and the Institute of Electrical and Electronics Engineers (IEEE).

Education
Computer science
  • Stage Ph.D
  • Location United States of America
  • Date 2004-01-01
  • University Massachusetts Institute of Technology
Computer science
  • Stage Master of Science
  • Location United States of America
  • Date 2001-06-14
  • University Stanford University
Electrical engineering
  • Stage Bachelor of Science
  • Location United States of America
  • Date 1997-01-01
  • University University of California, Berkeley
Research interests
  • Machine learning
  • Natural language pro
  • Robotics
  • Computer vision
  • ML
Research Areas
  • Deep learning
  • Reinforcement learn
  • Computer graphics
Work Experience
Research Scientist

Developed new algorithms for machine learning and natural language processing.

  • Company Google
  • Location Mountain View, CA
  • Start 2005-05-01
  • End 2008-01-03
Software Engineer

Designed and developed software for the iPhone and iPad.

  • Company Apple Inc.
  • Location Cupertino, CA
  • Start 2008-05-15
  • End 2010-05-31
Professor

Currently teaching undergraduate and graduate courses in computer science. Conducting research on computer vision and robotics.

  • Company Stanford University
  • Location Stanford, CA
  • Start 2010-06-01
  • End -
Courses
  • Computer Vision
  • Robotics
  • AI
  • Introduction to CS
Patents
Method and System for Context-Aware

  • Date 2024-05-14
  • Number US 17,123,456 B1
Collaborative Learning Framework for

  • Date 2022-02-12
  • Number US 16,876,543 B2
Augmented Reality System for Real-Time Sign

  • Date 2024-05-18
  • Number US 18,456,123 B1
Awards
rank-3 3
ACM SIGKDD Innovation Award

Awarded for the development of a new algorithm for mining large datasets.

Date 2011-02-01
rank-1 1
NSF CAREER Award

Awarded for the development of a new approach to robot learning.

Date 2018-01-18
rank-2 2
Inc. Magazine 30 Under 30

: Awarded for his entrepreneurial success as the co-founder of MyStartup Inc.

Date 2024-05-06
Professor positions
  • Deadline : Dec 12, 2024
  • Start : 2 Months later
  • Duration : 48 month
  • English
  • Fund : 35000 USD
  • Fee : 125 USD
Ph.D Computer Science - Artificial Intelligence ,
?

The field of Artificial Intelligence (AI) has witnessed tremendous growth, with AI models achieving remarkable performance in diverse tasks. However, the opaque nature of these models raises concerns about explainability and interpretability. This research project delves into Explainable AI

    • Deadline : Dec 12, 2024
    • Start : 2 Months later
    • Duration : 48 month
    • English
    • Fund : 48000 USD
    • Fee : 100 USD
    • No Exam

    Natural Language Processing (NLP) has emerged as a powerful tool with the potential to address various societal challenges. This research project focuses on leveraging NLP techniques for social good applications. The successful candidate will explore various NLP tasks with a focus on real-w

    • Deadline : Dec 12, 2024
    • Start : 2 Months later
    • Duration : 36 month
    • English
    • Fund : 0
    • Fee : 0

    The development of safe and reliable autonomous vehicles (AVs) hinges on robust computer vision (CV) systems. This research project explores novel CV techniques for enabling AVs to perceive their surroundings and make informed decisions. The successful candidate will delve into various aspe