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Marc Chalé

Data Scientist

USA

marc@marcchale.com

(937) 255-2549


Skills

Machine Learning

90%

Leading and Growing Human Capital

80%

Decision Analysis

75%

Front End Web Development

50%



Programming Languages



AI Secures Freedom

Techlogy is integrated brilliantly into our lives. Only when our devices malfunction, do we realize how dependent we've become on cyber systems and the internet of things. These systems were not built on intrinsically secure infrastructures and they need auxilliary defenses. My work seeks to empower people with AI driven threat detection technology.
    For several years I recognized the transformation artificial intelligence has made in various fields of engineering, but I saw untapped potential in cybersecurity. Scholars of operations research have invented and improved countless analysis algorithms, but few research groups seemed to ask "how can our models become robust to cyber crimials who seek to corrupt them?" By characterizing the distribution of normal and malicious cyber data, we start to understand how attackers can evade intrusion detection systems within their various threat models. I believe this insight will be key to designing an intrusion detection system robust against evasion attacks. I hope you stay in touch as I publish my research for the community.

Work Experience

Ph.D. Candidate, Air Force Scholar - Air Force Institute of Technology
Aug 2018 - Current
    Research Associate at Army Cyber Institute Intelligent Cyber-Systems and Analytics Research Lab

    Conference Presentations
  • "A Holistic Approach to the Algorithm Selection Problem" at the Military Operations Research Symposium 2020
  • "A Structured Approach for Selection of Machine Learning Techniques" at INFORMS Annual Meeting 2019
  • "Generative Machine Learning and Meta-learning to Defend from Adversarial Attack in the Cyber Domain" at Army Research Lab-US Military Academy Technical Symposium 2021

  • Published Research
  • Challenges and Opportunities for Generative Machine Learning in the Cyber Domain" (Accepted) Proceedings of the 2021 Winter Simulation Conference
  • "Algorithm Selection Framework for Cyber Attack Detection"
  • Thesis "Algorithm Selection Framework: A Holistic Approach to the Algorithm Selection Problem"

Operational Test Analyst - AFOTEC
Aug 2014 - Aug 2018
    Leadership Impact
  • Lead Test Engineer/Analyst for $8.4 Million test program to drive acquisition decision for $7.73 Billion fleet upgrade.
  • Led team of 5 engineers during 9 months of test events and analysis resulting in on time delivery of test report to 2 Star General.
  • Re-engineered data analysis process resulting in 700% increase in efficiency and saving over 600 engineer man hours.
  • Hand picked by 1 Star General to revitalize retiree outreach program, led 75 airmen providing medical, financial, and legal benifits to thousands of California veterans. "Best year ever" claimed general officer.

Consulting Test Engineer Internship - LiquidPiston
May 2014 - Aug 2014
    Technical Impact
  • Designed chemical treatment and heat treatments to harden and strenthen various metal contact surfaces in low-friction rotory engine
  • Improved mechanical seal design reducing friction, and locking in combustion gasses, improving power, reducing vibration.
  • Executed dynamometer test, pre-processed millions of data points, and produced reports, facilitating analysis of alternatives for 3 engine models.

Education

Air Force Institute of Technology
2018 - 2022
  • Ph.D. Candidate in Operations Research (Expected graduation 2022)
  • M.S. in Operations Research

New Mexico State University
2016 - 2018

M.S. in Industrial Engineering


University of Connecticut
2010 - 2014

B.S. in Materials Science & Engineering