Bryse Flowers

About Bryse Flowers

Bryse Flowers, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at University of California, San Diego, specializes in the field of Machine Learning, Wireless Communications.

His recent articles reflect a diverse array of research interests and contributions to the field:

Utilizing Reinforcement Learning for Adaptive Sensor Data Sharing over C-V2X Communications

Utilizing Unsupervised Learning for Improving ML Channel State Feedback in Cellular Networks

Adaptive c-v2x sidelink communications for vehicular applications beyond safety messages

Multi-source feature fusion for object detection association in connected vehicle environments

Countering physical eavesdropper evasion with adversarial training

An rfml ecosystem: Considerations for the application of deep learning to spectrum situational awareness

Low Overhead Codebook Design for mmWave Roadside Units Placed at Smart Intersections

A UCSD view on replication and reproducibility for CPS & IoT

Bryse Flowers Information

University

Position

___

Citations(all)

315

Citations(since 2020)

315

Cited By

94

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

6

i10Index(since 2020)

6

Email

University Profile Page

Google Scholar

Bryse Flowers Skills & Research Interests

Machine Learning

Wireless Communications

Top articles of Bryse Flowers

Title

Journal

Author(s)

Publication Date

Utilizing Reinforcement Learning for Adaptive Sensor Data Sharing over C-V2X Communications

IEEE Transactions on Vehicular Technology

Bryse Flowers

Yu-Jen Ku

Sabur Baidya

Sujit Dey

2023/10/4

Utilizing Unsupervised Learning for Improving ML Channel State Feedback in Cellular Networks

Bryse Flowers

Adarsh Sawant

Runxin Wang

Dustin Zhang

2023/6/20

Adaptive c-v2x sidelink communications for vehicular applications beyond safety messages

Yu-Jen Ku

Bryse Flowers

Samuel Thornton

Sabur Baidya

Sujit Dey

2022/6/19

Multi-source feature fusion for object detection association in connected vehicle environments

IEEE Access

Samuel Thornton

Bryse Flowers

Sujit Dey

2022/12/12

Countering physical eavesdropper evasion with adversarial training

IEEE Open Journal of the Communications Society

Kyle W McClintick

Jacob Harer

Bryse Flowers

William C Headley

Alexander M Wyglinski

2022/10/12

An rfml ecosystem: Considerations for the application of deep learning to spectrum situational awareness

IEEE Open Journal of the Communications Society

Lauren J Wong

William H Clark

Bryse Flowers

R Michael Buehrer

William C Headley

...

2021/9/20

Low Overhead Codebook Design for mmWave Roadside Units Placed at Smart Intersections

Bryse Flowers

Xinyu Zhang

Sujit Dey

2021/9/13

A UCSD view on replication and reproducibility for CPS & IoT

Alex Yen

Bryse Flowers

Wenshan Luo

Nitish Nagesh

Peter Tueller

...

2021/5/18

Effects of forward error correction on communications aware evasion attacks

Matthew DelVecchio

Bryse Flowers

William C Headley

2020/8/31

When wireless security meets machine learning: Motivation, challenges, and research directions

Yalin E Sagduyu

Yi Shi

Tugba Erpek

William Headley

Bryse Flowers

...

2020/1/24

See List of Professors in Bryse Flowers University(University of California, San Diego)

Co-Authors

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