Spacecraft autonomy
Physics-conditioned learning and optimization for reliable on-orbit operation, from VLEO through deep space.
Aerospace engineer · Tucson, Arizona
Adam
Nekolny
Ph.D. student and mission systems engineer building autonomous spacecraft, guidance and control systems, and physics-aware neural optimization.
32.2226° N110.9747° W
Currently researchingSpacecraft-native learning
Research
Focus areas
Learning and control methods shaped by the spacecraft itself: its structure, actuators, power, thermal state, communications, and orbital environment.
Guidance, navigation & control
Attitude dynamics, optimal estimation, embedded control, and flight-software architectures for small spacecraft.
Neural systems
Compact policy networks, reinforcement learning, and custom update rules shaped by spacecraft subsystems and environments.
Flight programs
Missions
Student-led spacecraft programs where the research is carried into real architectures, embedded hardware, and operations.
MembraneSat · Earth Cup RACE 1
SolarCat
Mission Systems Architect · ADCS, ECE & Flight Software Lead
A hexagonal sailcraft demonstrating autonomous drag-modulated lifetime extension in VLEO. Third place in RACE 1 and advanced to flight-hardware development.
6U CubeSat · University of Arizona
CatSat
Systems & Automation Engineer
Ground-segment infrastructure, mission-data automation, and on-orbit validation of ARLAMX against spacecraft orbital-decay and quaternion telemetry.
Academic
Education
Mathematics, aerospace engineering, controls, and autonomous systems, all at the University of Arizona.
University
of Arizona
Ph.D. · Aerospace Engineering
University of Arizona
Dynamics and Control · Advisor: Prof. Christopher K. Walker
Spacecraft-native neural optimization for autonomous operation.M.S. · Aerospace Engineering
University of Arizona
Dynamics and Control
Thesis: Multi-Objective Deep Reinforcement Learning for Aerodynamic Attitude Scheduling in Very Low Earth Orbit.B.S. · Aerospace Engineering & B.S. · Mathematics
University of Arizona Honors College
Cum Laude · GPA 3.64
Aerospace capstone: AIAA Design/Build/Fly. Mathematics capstone: match-filtering and sensitivity analysis for LIGO gravitational-wave detection.
Connect
Profiles and projects
Capabilities
PythonMATLABC / C++PyTorchPPO / SAC / TD3Kalman filteringQuaternion controlBasiliskSTKFreeRTOSSTM32KiCadLinuxDockerFlight software architecture
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