Machine Learning takes over the EECS Atrium

Students in EECS 545: Machine Learning, taught by Prof. AL Hero, presented their final projects in a poster session sponsored by KLA.
Students in front of their poster Enlarge

Students in EECS 545: Machine Learning presented posters on their class projects in the EECS Atrium on Friday, December 13th. The course is a graduate-level introduction of machine learning and provides foundations of mathematical derivation and implementation of the algorithms and their applications. It was taught by Al Hero, the John H. Holland Distinguished University Professor of EECS and R. Jamison and Betty Williams Professor of Engineering.

The students’ projects fell into one of three tracks:

  1. Application
  2. Implementation
  3. Open-Ended

KLA, a global capital equipment company that is currently building a second headquarters in Ann Arbor, sponsored the event. They awarded a $100 gift card to each member of a 1st place team, a $50 gift card to each member of a 2nd place team, and a $25 gift card for honorable mentions. Below are the winners:


1st Place

“A Machine Learning Approach to Predicting Liver Transplant Candidate Outcomes.”
Luke DeRoos, Sajjad Seyedsalehi, Dipak Narayan, and Akshit Kumar

2nd Place

“Auto-regressive model with exogenous input (ARX) based Traffic Flow Prediction.”
Bowei Li, Jun Ying, Xin Dong, and Zihan Tian


1st Place

“An Investigation of Rectified Adam.”
Cameron Husted, Aaron Tumulak, Michael Sander, and Bryan Rabotnick

2nd Place

“Reinforcement Learning in Continuous Action Spaces.”
Joseph Lowman, Michael Maring, Jonathan Schwartz, and Aishwarya Unnikrishnan


1st Place

“Triplet loss for regularizing deep neural networks.”
Junghwan Kim, Drake Svoboda, Anshul Aggarwal, and Youngwoo Woo

2nd Place

“Detail-Preserving Image-based Virtual Try-On Network with Patch GAN.”
Chia-Ming Wang, Rongcong Xu, Shangquan Sun, and Hanwen Miao

Honorable Mentions

“Bayesian LSTM for Anomaly Detection in Time Series.”
Jeremiah Hauth, Loubna Baroudi, Han Yang, and Wenyi Zhao

“Electrocorticography from the Orbitofrontal Cortex Predicts Gambling Tasks and Suggests a Focal Network Architecture.”
Matthew Willsey, Lap Sum Chan, Ali Rafei, Ibrahim Ajlan I Alajlan

“Implementation and Analysis of Capsule Networks.”
Fengyi Gao, Yihao Yang, and Bolaji Eniwaye

“Investigation on GAN, WGAN and WGAN-GP.”
Xiaozhu Fang, Mingjie Gao, Jiaren Zou, and Shuyang Huang

“Show Me the Money: Professional Basketball Betting via Neural Networks.”
Christopher Wentland, Maximilan Huppertz, David Mayers, and Matthew Schirmann

“Statistical Arbitrage by Pair Trading using Clustering and Machine Learning.”
Israel Diego, Yingcong Jiang (None), Kaiqi Wang, and Wuren Wang

For more photos, check out our flickr.