A

Alex Showalter-Bucher

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SVP of Technology / Founder
United States

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Résumé

Jobs verified_user 0% verified
  • Code Metal
    SVP of Technology / Founder
    Code Metal
    Sep 2023 - Current (3 years)
  • Orange Comet Inc
    Director of Engineering
    Orange Comet Inc
    Dec 2022 - Apr 2024 (1 year 5 months)
  • Mint State Labs acquired by Orange Comet
    Chief Technology Officer
    Mint State Labs acquired by Orange Comet
    Feb 2022 - Dec 2022 (11 months)
  • MIT Lincoln Laboratory
    Associate Technical Staff
    MIT Lincoln Laboratory
    Apr 2014 - Apr 2021 (7 years 1 month)
    • Research and development of machine learning/A.I. techniques for multiple sensor modalities • Software engineering from design and development to delivery • System and element level analysis of complex systems • Concept development, proposal formulation, and leading programs
  • Lawrence Livermore National Laboratory
    Research Intern
    Lawrence Livermore National Laboratory
    Jun 2012 - Aug 2012 (3 months)
    • Explored the potential of underground target characterization using singular value decomposition (SVD) for a car-mounted multistatic underground imaging radar system • Determined that the behavior of singular values have a direct correlation to the polarization characteristics of the underground target
  • Northeastern University
    DHS Career Development Fellow
    Northeastern University
    Jan 2012 - Aug 2013 (1 year 8 months)
    • Developed algorithms for tunnel localization and soil property estimations using a borehole Ground Penetrating Radar system (GPR) • Simulated full-wave electromagnetic field propagation using both finite difference frequency domain (FDFD) and finite difference time domain (FDTD) codes developed in Matlab • Processed and compared simulation and experimental data for algorithm verification • Coordinated international collaboration for field tests
  • Gettysburg College
    Physics Research Intern (Summers)
    Gettysburg College
    Jan 2008 - Dec 2009 (2 years)
    Independently learned Geant4 and constructed a simulation of the low energy particle behavior of a reactor (YAGUAR, located in Russia) to determine the potential of hydrogen desorption • Constructed a simulation which properly modeled the geometries and materials of the YAGUAR reactor • Simulated and compared the attenuation of low-energy particles for selection of appropriate physical models • Compared and verified simulation results to known experimental data • Performed initial simulated tests of the behavior of low energy electrons produced by the reactor
Education verified_user 0% verified
  • Northeastern University
    Master of Science - MS, Computer Science
    Northeastern University
    Jan 2015 - Dec 2020 (6 years)
    Concentration: Artificial Intelligence
  • Northeastern University
    Certificate, Engineering Leadership
    Northeastern University
    Jan 2012 - Dec 2013 (2 years)
  • Northeastern University
    Master of Science - MS, Electrical Engineering
    Northeastern University
    Jan 2011 - Dec 2013 (3 years)
    Concentration: Computational Electromagnetics
  • Lancaster University
    Study Abroad Program, Study Abroad Program
    Lancaster University
    Jan 2009 - Dec 2009 (1 year)
  • Gettysburg College
    BA, Physics
    Gettysburg College
    Jan 2006 - Dec 2010 (5 years)
    Minors: Computer Science and Classical Studies
  • Massachusetts Institute of Technology
    Advanced Studies Program
    Massachusetts Institute of Technology
    Coursework: 6.869 - Advances in Computer Vision (graduate-level - Fall 2018) 6.865 - Advanced Computational Photography (graduate-level - Fall 2017) 6.867 - Machine Learning (graduate-level - Fall 2016)
Projects (professional or personal) verified_user 0% verified
  • S
    Spatial-temporal Frame Decomposition for Optically Multiplexed Cameras via 3D ConvNets
    Apr 2020
    Project for Graduate Course: Imaging and Deep Learning Description: Individual project that researched the utility of using 3D ConvNets to spatial-temporally decompose frames from an optically multiplexed imager. Project required reimplementing a significant portion of existing architectures in Pytorch. Concluded that technique showed promise but should be revisited with less constrained configurations and training resources. Contribution: All parts of project
  • A
    Augmented Annotation
    Oct 2019
    MIT Lincoln Laboratory Description: Five-person team—developed complete augmented annotation tool to label video sequences for training and evaluating visual object detectors. Key augmentations included integration of a visual object detector for bootstrapping labeling and a visual tracker to identify additional annotations from validated annotation seeds. Preliminary results showed a 66x increase in throughput over a non-augmented annotation framework. Contribution: Visual track fusion implementation, visual object detector integration, containerization of software
  • U
    Utilizing Optically Multiplexed Cameras for Simultaneous Localization and Mapping (SLAM)
    Dec 2018
    Graduate Course Project: Advanced in Computer Vision (at MIT) Description: Three-person team—explored the feasibility of extending a simultaneous localization and mapping (SLAM) algorithm, ORB-SLAM, to work with optically multiplexed cameras. Outcomes found that spectral filters or stereo epipolar constraints were viable approaches for enabling SLAM on optically multiplexed cameras. Contribution: Conception, project lead, data generation, SLAM integration, and execution of two monocular approaches
  • V
    Virtual Reality Integration Into Open Source Games
    Apr 2017
    Graduate Course Project: Building Game Engines Description: Two-person team—integrated OpenVR head-mounted display (HMD) and tracking support into three open source games: Free Space 2 (C++), Super Mario 64 HD (Unity), and Quake (C). Contribution: Complete OpenVR integration into Free Space 2 and Quake, and aided integration into Super Mario 64 HD
  • P
    Pose Estimation via Machine Learning Techniques
    Dec 2016
    Graduate Course Project: Machine Learning (at MIT) Description: Two-person team—implemented two pose estimation methods via machine learning. First implementation was a convolutional neural network to estimate an object pose directly from images. Second implementation was a feed-forward neural network to estimate an object pose from 2D projections measurements of reference points on an object.
Awards verified_user 0% verified
  • MIT Lincoln Laboratory
    Fake News Hackathon Winning Team
    MIT Lincoln Laboratory
    Jul 2017
    Co-led winning team in machine learning hackathon on classification of unreliable news.
  • S
    Sponsor Commendation for Development of Simulation Software
    May 2017
    Received commendation from government sponsor for key contributions to the development of a missile defense simulation software.
  • N
    Outstanding Teaching Assistant Award
    Northeastern University College of Engineering
    May 2012
    Recognition for outstanding contributions as a teaching assistant in the Gordon Engineering Leadership Program.
Publications verified_user 0% verified
  • I
    Eigenmode-based method to determine the complex permittivities of layered soil via a borehole ground penetrating radar
    IEEE Antennas and Propagation Society International Symposium APSURSI
    Jul 2014
  • Northeastern University
    Model-Based Inversion Algorithms for Tunnel Localization via Borehole Ground Penetrating Radar
    Northeastern University
    Aug 2013
    Thesis/Challenge Project
  • N
    Experiment on Direct NN Scattering — the Radiation-Induced Outgassing Complication
    Nuclear Physics A
    Dec 2012
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