Benjamin Conte

Aspiring Software Developer

Computer Science student 👨‍💻 studying at the University of California - Santa Barbara

Academic History

University of California - Santa Barbara, Computer Science

GPA: 3.70

Expected Graduation: June 2025

Relevant Coursework

  • Differential Equations
  • Classical Mechanics
  • Vector Calculus
  • Intro to Computation
  • Data Structures and Algorithms
  • Computer Architecture
  • Automata and Formal Languages
  • Software Systems (IoT)

University of California - San Diego, Computer Science

GPA: 4.0

Summer 2021

Relevant Coursework

Introduction to Programming and Computational Problem Solving (JAVA)

Tools

Programming Languages / Tools

C++, Python, JAVA, C#, RobotC, Linux, React JS, Mips, PyRTL(HDL), .NET, NodeJS, TensorFlow

Concepts

Object-Oriented Programming, Recursion, Data Structures, Memory Optimization, Algorithms

Applications

Git, Visual Studio, Arduino IDE, Word, Powerpoint, Excel, Adobe Acrobat, Photoshop, MS Word, Azure

Work Experience

Software Engineer Intern at Giesecke+Devrient (June 2023-Present)

  • Surpassed performance target by optimizing existing code, achieving a 125% improvement in runtime
  • Modified C# UI with .NET Framework to incorporate testing features, saving 10 hours of manual work weekly
  • Researched emerging technologies and implemented a 90% accurate image-to-text feature for clients
  • Created a Python script using OpenCV for image variations, bolstering code accuracy tests
  • Packaged the application into a library using .NET Framework, streamlining distribution and integration
  • Implemented unit tests to ensure code accuracy and functionality, leading to a 30% reduction in failed cases

Projects

Facial and Smile Recognition Program

  • Created a real-time application that can detect a smiling face within the camera frame
  • Utilized the simplicity of Python and the capability of the OpenCV Library
  • Optimized resource consumption to increase efficiency and detection speed
  • Reduced image file sizes by 66%, resulting in a 30% improvement in processing runtime
PYTHONMLCV2
Data Optimization Program
  • Developed a binary search tree using a linked-list data structure
  • Optimized insertion and deletion of elements from the tree
  • Utilizing recursion to decrease redundancy and improve efficiency
C++Linked List