Scholarships

Class of 1937 Scholarship & the Charles O. McGaughey Leadership Award

The Division of Student Life is pleased to announce that applications are now available for the Class of 1937 Scholarship and the Charles O. McGaughey Leadership Award. The application may be found at https://www.purdue.edu/vpsl/leadership/

Both are awarded on a competitive basis in recognition of leadership accomplishments and leadership potential.

The Class of 1937 Scholarship

A limited number of scholarships are available for the 2020-2021 school year from funds donated by members of the Purdue Class of 1937 in support of current students.  Criteria for determining recipients of this scholarship include: Leadership, Character, and Scholarship.

To be Eligible for a Purdue Class of 1937 Scholarship, an applicant must:

  1. Be enrolled at the Purdue University West Lafayette campus;
  2. Be registered for 12 or more credit hours;
  3. Be classified as a sophomore, junior, or senior during the 2020-2021 academic school year;
  4. Have a cumulative grade point index of 2.0 or higher on a 4.0 scale;
  5. Be in good academic and social standing with the University;
  6. Show evidence of leadership potential and ability

To complete the application students must provide the following:

  • A list of their of their significant leadership activities since enrolling at Purdue
  • An essay reflecting on their leadership experiences and abilities
  • Name and email addresses for two (2) references familiar with their leadership abilities

The number of scholarships and the amount awarded for 2020-2021 will be determined by the interest earned on the Class of 1937 endowment during the past year.  An average of 15 scholarships have been awarded each year since 1987-88, with individual scholarship amounts ranging from $500 to $4000.  

The application is to be completed on line and submitted by January 13, 2020 @ 5:00 pm (EST). The references will be due January 22, 2020 @ 5:00 pm (EST).

Students should refer to the application for complete details.

Charles O. McGaughey Leadership Award

Charles O. McGaughey (pronounced Mackgoy) Leadership Awards will be presented in the Spring Semester of 2020. 

A limited number of awards will be available in the amount of at least $2000 each.

These awards are made possible by an endowment established by the late Mr. Charles O. McGaughey, a 1939 graduate of Purdue University. Mr. McGaughey designated the award to honor Purdue undergraduates who show leadership abilities and “appreciation for basic American values.”

Applicants must:

1. Be an undergraduate student currently registered at the West Lafayette campus of Purdue University who will have completed at least two years of undergraduate studies as a full-fee student (i.e., full-time student) by the end of the spring semester 2020;
2. Have at least a 3.0 overall GPA;
3. Have demonstrated leadership abilities and appreciation of basic American values as evidenced by a record of achievement through community service and service to the university;
4. Demonstrate an appreciation for the values of liberty and the democratic form of government and an appreciation of the importance of respect for others and for the diversity of the United States of America;
5. Have no evidence of addiction to drugs or alcohol;
5. Have no criminal record;  

APPLICATION DEADLINE

Submit the application on line no later than January 15, 2020 by 5:00 pm (Late applications will not be considered. Incomplete applications will not be considered)

Previous McGaughey Leadership Award recipients are not eligible.

Please note: Preference will be given to applicants whose majors are in the College of Liberal Arts, College of Science, and School of Management. However, applicants from all colleges will be considered.

To complete the application student must submit:

  • A list of their significant leadership activities, including a brief description of what was achieved as a result of their leadership
  • An essay reflecting on their college experience providing information about their development as a leader

Students should refer to the application for full details about what is required.

Contact Harry Brown hebrown@purdue.edu if you have any questions about the Class of 1937 Scholarship or the Charles O. McGaughey Leadership Award.

Classes

ABE 591: Machine Learning & High-Performance Computing for Digital Ag & Biological Engineering; Part 1: Algorithms, resilient data lakes, & analytics at the edge

Dr. Somali Chaterji (Assistant Professor, Department of Ag and Biological Engineering, Purdue University) will be offering a one-credit data science & data engineering course for non-computer science majors titled: ABE 591: “Machine Learning & High-Performance Computing for Digital Ag & Biological Engineering; Part 1: Algorithms, resilient data lakes, & analytics at the edge”.

This course is about data stories, data lakes, and algorithms that will provide the conceptual and foundational bases for machine learning (ML) applied to genomics, digital agriculture, and IoT, to name a few domains. These are some of the domains that are generating terabytes of data, both diverse and available in large volumes. These data sets can be used for “deciphering the rules of life” or to extract actionable information from the ubiquitous IoT sensors. Overall, this course is meant for both advanced undergraduate or graduate students and does not assume any prior knowledge of ML algorithms. This course is part of a Purdue initiative that aims to deliver stackable one-credit courses to create a custom data-science curriculum.

Course webpage: schaterji.io/teaching.html;
Flyer: http://bit.ly/chaterji-data-science;
Tweet: https://twitter.com/SomaliChaterji/status/1190377382265475073?s=20

Offering: Spring 2020 [starting week of Mar 9th, 2020]; 1 lecture/week for 2 hours (Wed evenings). Prerequisite: STAT 30100 OR ABE 20500 OR CHE 32000 OR Graduate Standing; a more advanced statistics course is also acceptable as long as the student has taken the course for credit.

Keywords: High-performance computing (HPC), resilient data lakes, noSQL databases, edge computing, deep learning, reward learning, distributed computing, supercomputers, graphics processing units (GPU).