Optimization, Machine Learning and High Performance Computing

Group is directed by:
Professor Oliveira and  Professor Stewart

Fall 2022-Spring 2023 Talks: (Fridays)
January 27: TBD
February 10: TBD
February 24: TBD
March 10: TBD
March 24: TBD
April 7: TBD
April 21: TBD
May 5: TBD

Fall 2021- Spring 2022 Talks:
September 9th - Jamil Gafur
September 16th - Katie Elmmert
October, 7th  - Tarun Roy
October 21st - Violet Tiema
November 11th - Ibrahim Emirahmetoglu
December 9th- Cory Kromer-Edwards


We bring knowledge from Numerical Analysis and Optimization to design and improve Machine Learning algorithms.

We focus on applications with large amounts of data where new optimization or parallel algorithms are essential.

Recent projects include: Machine Learning and Genetics, Neural Networks and Educational data, Theoretical Foundations of Neural Networks, Gerrymandering

Neural Network (Variational Auto
      Enconder Illustratiion)    autoenconder figure


Gradient descent simulation           Gravity Swarm Algorithm on convex plain
We study classical optimization methods, stochastic gradient descent, and metaheuristics for machine learning and their parallelization. Above, see simulations of gradient descent and a metaheuristic algorithm (images provided by the PhD students).

Recent Collaborators include: Professor Mariana Curi, Professor Jonathan Templin, Dr. Mariana Castanheira, Dr Scott Pu, Prof. Octav Chipara, Prof. Amaury Lendasse, Prof. Palle Jorgensen

Current PhD students working on this Group

Some Recent PhD Students:

Recent Undergraduate Supervision (2015-2020)
(for Large Data Analysis Certificate with Isabel Darcy and Kate Cowles)

2015-2016 Kyumok Lee, Wyatt Bettis, Yue Bin, Kenong Su

2016-2017 Kenong Su, Jing Chen, Jingrong Li, Benjamin Jacobs

2017-2018 Yash Chauhan, Anthony Pizzimenti, Joseph Constant, Yunyi Li, Sangguan Wang

2018-2019 Mathias Sader, Chunquing Cao, Katherine Wasmer, Vanessa Chen, Kayla Gibson, Laura Weiler.


Big Summer School Participants (2015-2018)

Summer 2015 Gracé Ndovia, Mitchell Penningroth, Jacob Smith, Mathias Sader, Loius Hasley, T'shilyn Harrington, Brian Schweer

Summer 2016 Rzwan Didhu, Liam Hagan, Daniel Kelly, Dillon Kock, Lucas Zach, Nolan Dewitte, Jiahua Zhang, Anthony Pizzimenti, Austin Russ, Derek Choi, Katherine Chace

Summer 2017 Carlos Zapata, Kelvin Encarnacao, Abigail Williams-Yee, Carles Mascardo, Natasha Brown-Joel,Jacob Howard, Robert Gerritsen, Minhan Lin, Biao Liu

Summer 2018 Kevin Liu, Ethan St John, Gus Johnson, Ethan Trepka, Moly Mcdermott, Steve Garcia, Rachel Hammel, Brandon Koch, Prateek Sudhanshu Raikwar, Jeremy Feguson, Yinguy Zhou, Pranav Sateesh, Andy Hou, Drew Graves


2021 REU Mentor:

on neural networks for personality trait assessment.

 



Publications and Support : under Professors Oliveira and Stewart Pages