Adrian Lozada

M.S. Computational Science & Engineering @ Georgia Tech

I build high-performance computing systems, parallel algorithms, and intelligent software. My work spans HPC, distributed systems, robotics, and machine learning.

Experience

Software Engineer Intern

May 2025 - Aug 2025

Orion Defense Solutions L.L.C. (Remote)

  • Built and deployed a Python/FastAPI automation platform integrating LangChain and SQL-backed internal systems, reducing project cycle time by ~8 hours.
  • Containerized platform microservices using Docker and Kubernetes, enabling rolling updates and eliminating ~7 hours of manual setup per week.

Undergraduate Researcher

Jan 2024 - May 2025

Reality, Autonomy, Robot Experience (RARE) Lab, USF — Tampa, FL

  • Published two first-author papers at ACM/IEEE HRI 2025 (25% acceptance rate) on autonomous fog-screen communication systems.
  • Developed ROS nodes in C++ to synchronize Fetch robot behavior, achieving reliable distributed actuation.

Projects

HPC

High-Performance Parallel Computing

  • Parallelized dense matrix kernels using OpenMP in C++, achieving near-linear 16x speedup at 16 threads on GT's PACE/ICE cluster.
  • Accelerated a heat equation PDE solver on an NVIDIA H100 via CUDA shared memory tiling, achieving up to 83.9x speedup.
  • Implemented MPI-parallel Monte Carlo simulation scaling to 64 processes with 99.7% parallel efficiency.
  • Applied Roofline performance modeling to classify SpMV, stencil, and 3D-FFT kernels on Intel and AMD architectures.
C++OpenMPCUDAMPI
Robotics

Autonomous Ground Vehicle

  • Led a team of 7 to design and build an autonomous vehicle on Raspberry Pi, mentoring peers in Linux development and conducting code reviews.
  • Designed and deployed a Flask backend with SQLAlchemy to expose REST endpoints for robot status, logs, and commands.
PythonFlaskSQLAlchemyRaspberry Pi
ML

GNN-Based Fraud Detection

  • Developed a Graph Neural Network in PyTorch to classify fraudulent financial transactions, achieving 91% accuracy on real-world datasets.
  • Preprocessed graph data with NetworkX, extracting structural features (centrality, clustering coefficients) to improve model performance.
PyTorchNetworkXPython

Education

Georgia Institute of Technology

M.S. Computational Science and Engineering

Expected Dec 2026 • GPA: 3.33/4.0

Coursework: High Performance Parallel Computing, Numerical Linear Algebra, Modeling and Simulation

University of South Florida

B.S. Computer Engineering, summa cum laude

Aug 2021 - May 2025 • GPA: 3.9/4.0

Honors: FLIT-GAP Scholar, Bright Futures Scholar

Coursework: Analysis and Design of Algorithms, Data Structures, Social Networks, Computer Architecture

Skills

Languages

PythonC/C++SQLBash/ZshJavaScript

Parallel / HPC

MPIOpenMPCUDA

Tools

GitDockerKubernetesROS

Systems / Areas

Data Structures & AlgorithmsDistributed SystemsHPCUnix/Linux

Libraries

PyTorchNumPyPandasFastAPIFlaskSQLAlchemyLangChainNetworkX

Awards

UR2PhD Technical Conference Travel Award

Computing Research Association (CRA)

$2,000 Mar 2025

Tampa Conference Presentation Grant Program

CPGP

$700 Mar 2025

NSF Distributed Research Experiences for Undergraduates

DREU

$7,000 May 2024 - Aug 2024

Florida Bright Futures Scholarship

100% of Tuition

Full Tuition Aug 2021 - May 2025