Loading [MathJax]/extensions/MathZoom.js

Adam Byerly - IEEE Xplore Author Profile

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Institutional Sign In

Institutional Sign In

ADVANCED SEARCH

Author details

Adam Byerly

Publications

6

Citations

51

Publications by Year

20162024

Co-Authors:

Jeffrey P. BakkenSai Shankar ChaduvuGregory FalcoNathaniel G. GordonAndrew Grotto

Show All Co-Authors (13)

Adam Byerly

Affiliation

Applied Physics Laboratory

Johns Hopkins University

Laurel, MD

Publication Topics

Neural Network,
Satellite,
Space Exploration,
Active Defense,
Active Space,
Adam Optimizer,
Adaptive Gradient Descent,
Adaptive Method,
Allocation Framework,
Attack Surface,
Attack Vector,
Autonomous Defense

Biography

,Adam Byerly received his B.S. in Mathematics from UMBC and M.S. in Applied Mathematics from JHU. He is currently pursuing a Ph.D. in Computer Science from JHU and is a member of the Senior Professional Staff in the Space Control Applications Group at the JHU Applied Physics Laboratory. During his 8 years at APL, he has contributed software engineering and data analytics expertise across a portfolio of civil and national security space missions.(Based on document published on 13 May 2024).

Publications

6

Citations

51

Publications by Year

20162024

Co-Authors:

Jeffrey P. Bakken
Sai Shankar Chaduvu
Gregory Falco
Nathaniel G. Gordon
Andrew Grotto

Show All Co-Authors (13)

Author's Published Works

Search History

Showing 1-6 of 6 results

Conferences (5)

Journals (1)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Adam Byerly(6)
Alexander Uskov(2)
Sebastian Zanlongo(1)
Josh Siegel(1)
Jeffrey P. Bakken(1)
Department of Computer Science and Information Systems, Bradley University, Peoria, IL, USA(2)
Dept. of Computer Science and Information Systems, Bradley University, Peoria, Illinois, U.S.A(1)
Applied Physics Laboratory, Johns Hopkins University, Laurel, MD(1)
Department of Civil & Systems Engineering, Institute for Assured Autonomy Johns Hopkins University, Baltimore, MD, USA(1)
Bradley University, Peoria, IL, US(1)
2016 IEEE International Conference on Electro Information Technology (EIT)(2)
2019 IEEE Global Engineering Education Conference (EDUCON)(1)
2022 IEEE Aerospace Conference (AERO)(1)
2024 IEEE Aerospace Conference(1)
IEEE Access(1)
IEEE(6)
Big Sky, MT, USA(2)
Grand Forks, ND, USA(2)
Dubai, United Arab Emirates(1)
Adaptive Method(2)
Graphics Processing Unit(2)
Neural Network(2)
Satellite(2)
Space Exploration(2)

Select All on Page

Sort By

Results

Side-Channel Payload Attacks: Modeling, Demonstration, and Mitigation Strategies

Adam Byerly;Anthony Hennig

2024 IEEE Aerospace Conference

Year: 2024 | Conference Paper |

HTML

With the growing dependence on hosted payloads as cost-effective solutions for space missions comes an increasing urgency to understand and mitigate their vulnerabilities in the face of sophisticated cyber threats. This work investigates the specific architectural vulnerabilities of hosted payloads, emphasizing the risk of side-channel attacks. Established methodologies like the Cyber Kill Chain a...Show More

Side-Channel Payload Attacks: Modeling, Demonstration, and Mitigation Strategies

Adam Byerly;Anthony Hennig

2024 IEEE Aerospace Conference

Year: 2024 | Conference Paper |

The Space Digital Dome: Autonomous Defense of Space Vehicles from Radio Frequency Interference

Gregory Falco;Nathaniel G. Gordon;Adam Byerly;Andrew Grotto;Josh Siegel;Sebastian Zanlongo

2022 IEEE Aerospace Conference (AERO)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

HTML

While awareness of active threats is critical to space vehicles, action is required to avoid harm. Physical hazard avoidance requires orbital manipulation using propulsion, whereas options for avoiding or nullifying radio frequency interference (RFI) are less straightforward. Because these actions need to occur on the space vehicle in real-time despite limited computing capacity and power on the e...Show More

The Space Digital Dome: Autonomous Defense of Space Vehicles from Radio Frequency Interference

Gregory Falco;Nathaniel G. Gordon;Adam Byerly;Andrew Grotto;Josh Siegel;Sebastian Zanlongo

2022 IEEE Aerospace Conference (AERO)

Year: 2022 | Conference Paper |

Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks

Adam Byerly;Tatiana Kalganova

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (9)

HTML

Neural networks traditionally produce a scalar value for an activated neuron. Capsules, on the other hand, produce a vector of values, which has been shown to correspond to a single, composite feature wherein the values of the components of the vectors indicate properties of the feature such as transformation or contrast. We present a new way of parameterizing and training capsules that we refer t...Show More

Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks

Adam Byerly;Tatiana Kalganova

Year: 2021 | Volume: 9 | Journal Article |

Machine Learning-based Predictive Analytics of Student Academic Performance in STEM Education

Vladimir L. Uskov;Jeffrey P. Bakken;Adam Byerly;Ashok Shah

2019 IEEE Global Engineering Education Conference (EDUCON)

Year: 2019 | Conference Paper |

Cited by: Papers (37)

HTML

Machine Learning (ML) is expected, in the near future, to provide various venues and effective tools to improve education in general, and Science-Technology-Engineering- Mathematics (STEM) education in particular. The Gartner Analytics Ascendancy Model requires the use of four types of data analytics to be considered comprehensive: descriptive, diagnostic, predictive and prescriptive data analytic...Show More

Machine Learning-based Predictive Analytics of Student Academic Performance in STEM Education

Vladimir L. Uskov;Jeffrey P. Bakken;Adam Byerly;Ashok Shah

2019 IEEE Global Engineering Education Conference (EDUCON)

Year: 2019 | Conference Paper |

OpenCL and CUDA software implementations of encryption/decryption algorithms for IPsec VPNs

Colleen Heinemann;Sai Shankar Chaduvu;Adam Byerly;Alexander Uskov

2016 IEEE International Conference on Electro Information Technology (EIT)

Year: 2016 | Conference Paper |

Cited by: Papers (2)

HTML

Graphics Processing Unit accelerated-computing technology is the innovative use of graphics processing units together with a CPU to significantly accelerate scientific, engineering, and enterprise applications. This paper presents the outcomes of a research project focused on the development and performance analysis of encryption/decryption algorithms in various modes of operation using OpenCL and...Show More

OpenCL and CUDA software implementations of encryption/decryption algorithms for IPsec VPNs

Colleen Heinemann;Sai Shankar Chaduvu;Adam Byerly;Alexander Uskov

2016 IEEE International Conference on Electro Information Technology (EIT)

Year: 2016 | Conference Paper |

A new parameter adaptation method for Genetic Algorithms and Ant Colony Optimization algorithms

Adam Byerly;Alexander Uskov

2016 IEEE International Conference on Electro Information Technology (EIT)

Year: 2016 | Conference Paper |

Cited by: Papers (1)

HTML

This Ant Colony Optimization algorithms and Genetic Algorithms are actively used in controller design, robotic path planning, design automation, biomedical imaging, data mining, and distribution network planning. This paper introduces a genetic algorithm implementation, an ant colony optimization algorithm implementation, and a method of adapting the parameters for the algorithms during the course...Show More

A new parameter adaptation method for Genetic Algorithms and Ant Colony Optimization algorithms

Adam Byerly;Alexander Uskov

2016 IEEE International Conference on Electro Information Technology (EIT)

Year: 2016 | Conference Paper |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.