Scholarships

NSF Graduate Research Fellowship Workshops

The National Science Foundation (NSF) Graduate Research Fellowship requires US Citizenship or Permanent Residency, and applicants must be either graduating undergraduates or first or second-year graduate students who have not applied previously as a grad student.

Why attend NSF Fellowship Workshops?

  • The NSF Fellowship provides three years of funding for Graduate School
  • Cultivate your grant writing skills to help you later apply for postdoc positions and other awards for your early career
  • Receive tips and strategies for submitting a competitive application for the NSF fellowship by attending these workshops!

Summer and Fall NSF Workshops

Strategies and Resources for Getting Started
July 22nd |10:00 – 11:30 am |YONG B64, Registration
August 6th |10:00 – 11:30 am |YONG B64, Registration
August 28th |7:00 – 8:30 pm |WALC 3138, Registration
September 3rd | 12:00 – 1:30 pm |BRWN 1154, Registration

Personal Statement Workshops
July 23rd |10:00 – 11:30 am |YONG B64, Registration
August 7th |10:00 – 11:30 am |YONG B64, Registration
September 10th | 12:00 – 1:30 pm | WTHR 320, Registration
September 12th |7:00 – 8:30 pm |WALC 3138, Registration

Research Statement Workshops
July 24th |2:00 – 3:30 pm |YONG B64, Registration
August 8th |10:00 – 11:30 am |YONG B64, Registration
September 24th |12:00 – 1:30 pm | BRWN 1154, Registration
September 26th | 7:00 – 8:30 pm |WALC 3138, Registration

Panel of Current NSF Fellows: Q&A Session
September 17th |7:00 – 8:30 pm | WALC 3090, Registration
This panel of previous NSF Fellowship winners from across various academic areas will answer questions from the audience regarding best practices for preparing your NSF Fellowship application.

Panel of Faculty with NSF Experience: Q&A Session
September 4th |9:30 – 11:00 am | WALC 3090, Registration
September 6th | 1:30 – 3:00 pm | WALC 3138, Registration
This panel of faculty have extensive experience helping their students prepare for the NSF Fellowship and they are happy to share their best practices for making your writings shine. Come ask the experts questions and hear their advice!

Additional fellowship and professional development workshops are posted here: https://gspd.gosignmeup.com/public/course/browse

Classes

IE 590: Robotics and Machine Vision (Technical Elective Credit)

NEW CLASS IE 590, FALL 2019:
DEEP LEARNING AND MACHINE VISION*
Dr. Juan P. Wachs (jpwachs@purdue.edu)

This course combines practically relevant methods, tools and applications related to deep learning in computer vision. Specifically, we will look at how data science principles are applied to computer vision through: (1) teaching neural networks including deep configurations with recent advances such as Generative Adversarial Networks (GANs), Long short-term memory (LSTMs), Style Transfer, and Autoencoders.

Program Overview (in a nutshell):
1.         Introduction to computer vision and deep learning.
2.         Linear Classification, Loss Functions, Neural Networks and Backpropagation
3.        CNNs and Recurrent Neural Networks
4.        Feature Representation and Adversarial Networks.
5.        Deep Reinforcement Learning.
6.        Style Transfer, GANs, RNNs, LSTM and Network Visualization.

Course Assignments:
Individual Assignments: Three homeworks will be assigned during the semester.
Project Assignments: Students will form a small team and build an application (or model) of a computer vision deep learning based system.
Midterm:  An in class midterm will be given to the students in class.

Course Requirements: Calculus, linear algebra, probability, Python programming experience (C/C++ is also a plus).