Ryan Rossi

Research Scientist

San Jose

Ryan Rossi is a machine learning research scientist at Adobe Research in San Jose, CA. His research lies in the fields of machine learning; and spans theory, algorithms, and applications of large complex relational (network/graph) data from social and physical phenomena. Before joining Adobe Research, he had the opportunity to work at a number of industrial, government, and academic research labs including Palo Alto Research Center (Xerox PARC), Lawrence Livermore National Laboratory (LLNL), Naval Research Laboratory (NRL), NASA Jet Propulsion Laboratory (JPL)/California Institute of Technology, University of Massachusetts Amherst, among others. Ryan earned his Ph.D. and M.S. in Computer Science at Purdue University. He was  a recipient of the National Science Foundation Graduate Research Fellowship (NSF GRFP), National Defense Science and Engineering Graduate Fellowship (NDSEG), the Purdue Frederick N. Andrews Fellowship, and Bilsland Dissertation Fellowship awarded to Outstanding Ph.D. candidates.

His publications are available here and on his personal site.

 

My Publications

Published November 21, 2019

Linear Quadratic Regulator for Resource-Efficient Cloud Services

ACM Symposium on Cloud Computing

Youngsuk Park, Kanak Mahadik, Ryan Rossi, Gang Wu, Handong Zhao
  • AI & Machine Learning
  • Systems & Languages

Published November 3, 2019

Graph Convolutional Networks with Motif-based Attention

CIKM, 2019

John Boaz Lee, Ryan Rossi, Xiangnan Kong, Sungchul Kim, Eunyee Koh, Anup Rao
  • AI & Machine Learning

Published August 4, 2019

Latent Network Summarization: Bridging Network Embedding and Summarization

KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Di Jin, Ryan Rossi, Danai Koutra, Eunyee Koh, Sungchul Kim, Anup Rao

Published February 11, 2019

Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior

WSDM '19 Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining

Donghyun Kim, Sungchul Kim, Handong Zhao, Sheng Li, Ryan Rossi, Eunyee Koh

Published December 10, 2018

ynamic Network Embeddings: From Random Walks to Temporal Random Walks

2018 IEEE International Conference on Big Data (Big Data)

Giang Nguyen, John Boaz Lee, Ryan Rossi, Nesreen Ahmed, Eunyee Koh, Sungchul Kim

Published October 22, 2018

Predictive Analysis by Leveraging Temporal User BehaviorCharles Chen, Sungchul Kim, Hung Bui, Ryan Rossi, Branislav Kveton, Eunyee Koh and Razvan Bunescu

CIKM'18

Charles Chen, Sungchul Kim, Hung Bui, Ryan Rossi, Branislav Kveton, Eunyee Koh, Razvan Bunescu
  • AI & Machine Learning
  • Data Intelligence