Mr. Jeffrey Chavis

Information Systems Engineering

Current Courses

Personal Bio

Jeffrey Chavis is a member of the principal professional staff at the Johns Hopkins University Applied Physics Laboratory (APL) and currently serves as the chief engineer for the applied data science branch at APL. He leads the development and application of advanced data science analytical techniques to provide data driven insights to solve problems in various domains including, but not limited to, cyber security, disease prediction, and artificial intelligence.

 Chavis currently teaches in Johns Hopkins University’s Engineering for Professionals programs, in both the software engineering and the information systems engineering programs. He is a senior member of IEEE and was recognized with the Black Engineer of the Year Award (BEYA) for Professional Achievement at the BEYA STEM Global Competitiveness Conference in 2016.

 Chavis earned a BS in Electrical Engineering from Howard University and an MS in Electrical Engineering from the University of Maryland, College Park. He is currently working on his doctoral degree at Johns Hopkins University researching novel methods to secure the Internet of Things through application of Machine Learning.

 

Education History

  • BSEE Electrical Engineering, Howard University
  • MSEE Electrical Engineering, University of Maryland

Work Experience

Principal Professional Staff, JHU Applied Physics Laboratory

Publications

Chavis JS, Kunz A, Watkins LA, Rubin A, Buczak AL. A Capability for Autonomous IoT System Security : Pushing IoT Assurance to the Edge. In: 2nd Annual Workshop on Assured Autonomous Systems (IEEE WAAS 2020). San Francisco, CA, United states

J. S. Chavis, A. Buczak, A. Rubin and L. A. Watkins, "Connected Home Automated Security Monitor (CHASM): Protecting IoT Through Application of Machine Learning," 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0684-0690.

A survey of deep learning methods for cyber security
DS Berman, AL Buczak, JS Chavis, CL Corbett
Information 2019

Using sequential pattern mining for common event format (CEF) cyber data
AL Buczak, DS Berman, SW Yen, LA Watkins, LT Duong, JS Chavis; Proceedings of the 12th annual conference on cyber and information security 2017

Detection of tunnels in PCAP data by random forests
AL Buczak, PA Hanke, GJ Cancro, MK Toma, LA Watkins, JS Chavis; Proceedings of the 11th Annual Cyber and Information Security Research 2016

Unsupervised Machine Learning by Graph Analytics on Heterogeneous Network Device Data; JS Lin, E Guven, LT Duong, JS Chavis, MD Dinmore, PA Hanke, BG Magen; Procedia Computer Science 140, 144-151 2016

Sensor-Based Adaptive Methods for Wearable Devices
T Gao, AM Alm, SM Babin, JS Chavis; US Patent App. 12/632,890 2010

Sensor-based adaptive wearable devices and methods
T Gao, J Chavis, WE Bishop, RR Juang, AM Alm, DM White, DA Crawford; US Patent 7,629,881 2009

Honors and Awards

  • Black Engineer of the Year - Professional Achievement in Industry (2016)

Professional Organizations

IEEE
NSBE