Professional Experience

Indiana University Intelligent Systems Engineering

Systems Engineer (2021-02-22 – present)

  • Led a small team researching deep learning for embedded system security
  • Ran customized open-source SaaS container infrastructure serving hundreds of concurrent users
  • Built and maintained multi-user, high performance compute and accelerator cluster hardware
  • Developed on-premises datacenter infrastructure including power delivery and monitoring
  • Compiled data and reports for ABET accreditation to establish a new engineering program
  • Taught engineering courses (Computer Architecture, C, Python, Operating Systems, Networks)

Senior Electronics Engineer (2016-07-01 – 2021-02-22)

  • Built and maintained datacenter cluster, server, power, and switch hardware
  • Built 64-node FPGA cluster for high performance networks and graph analytics
  • Merged 8-GPU cluster with 16-node CPU/FPGA cluster for hardware accelerated networking
  • Developed hardware-accelerated distributed edge computing prototypes and publications

Indiana University Psychological and Brain Sciences

Electronics Engineer (2014-03-03 – 2016-06-30)

  • Specified and implemented custom hardware and software for embedded devices for researchers
  • Developed MRI-safe touch screen technology (result: US Patent 10820839B2)
  • Created novel sensors for research including skin response, eye tracking systems, and brain-computer interfaces
  • Developed combined electronics, carpentry, and machine shop containing CNC mills, lathes, saws, and PCB fabrication services

Education

Ph.D. in Intelligent Systems Engineering

Indiana University (2018-08-20 – 2023-12-15). Computer Engineering concentration, Computer Science minor. Dissertation: Deep Learning for Obfuscated Code Analysis.

Bachelor of Science in Electrical Engineering

Indiana University Purdue University Indianapolis (2010-05-11 – 2013-12-16).

Skills

  • focus: deep learning, software engineering, open-source project management, data analytics, Natural Language Processing (NLP), Computer Vision, compilers
  • tools: Python, C, C++, JavaScript, J, Bash, Linux, Git Docker, PyTorch, Tensorflow, Matplotlib, Seaborn, Vivado, Cadence Innovus, PostgreSQL
  • dabble in: K, Racket, Elm, emacs lisp, assembly, MATLAB, LaTeX

Publications

  • Shroyer, Alexander, Paventhan Vivekanandan, and D. Martin Swany. "Function Classification for Obfuscated Binary Code". Submitted to IEEE Transactions on Information Forensics and Security, December 2023.
  • Shroyer, Alexander, and D. Martin Swany. "Detecting Standard Library Functions in Obfuscated Code." IntelliSys, September 2023. Best presentation award (video).
  • Shroyer, Alexander, and D. Martin Swany. "Data Augmentation for Code Analysis." 2022 International Conference on Intelligent Data Science Technologies and Applications (IDSTA). IEEE, 2022.
  • Brasilino, Lucas RB, Naveen Marri, Alexander Shroyer, Catherine Pilachowski, Ezra Kissel, and Martin Swany. "In-network processing for edge computing with InLocus." International Journal of Cloud Computing 9, no. 1 (2020): 55-74.
  • Brasilino, Lucas RB, Alexander Shroyer, Naveen Marri, Saurabh Agrawal, Catherine Pilachowski, Ezra Kissel, and Martin Swany. "Data Distillation at the Network's Edge: Exposing Programmable Logic with InLocus." In 2018 IEEE International Conference on Edge Computing (EDGE), pp. 25-32. IEEE, 2018.
  • Arap, Omer, Lucas RB Brasilino, Ezra Kissel, Alexander Shroyer, and Martin Swany. "Offloading collective operations to programmable logic." IEEE Micro 37, no. 5 (2017): 52-60.
  • "Thinking in Array Languages" on Software Unscripted. Interviewed by Richard Feldman, July 8 2023.

Open Source Contributions

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