About Me
I'm an undergraduate at the University of Minnesota, studying Robotics, Computer Science, and Mathematics. I value these five pillars in life: Family, Finance, Philosophy, Fitness, and Decision Making. I love my Family. I'm looking for a Job where I can add value and gain it back too. I'm an avid Stoic. I currently Bench 185lbs, Squat 315lbs, and play pick-up Soccer. And decisions have made me who I'm today.
Contact:
Projects
Genentic Learning for Self Driving Cars | Python, Numpy, and Pygame
Created a 2D automobile physics simulation, and a procedural track to mimic real-world driving conditions. Implemented genetic learning to train a shallow neural network to drive autonomously within the simulation. Designed a fitness function that rewarded efficient and safe driving behavior, resulting in improved performance.
Object Detection with Faster R-CNNs | Python and Pytorch
Implemented a Faster R-CNN network for object detection, and trained it on PROPS achieving a 20\% mAP score. Utilized transfer learning by using RegNetX-400MF to speed up training time to only 3 hours. Calculated and implemented all forward and backwards steps for back-propagation by hand.
Eigen Faces | Python, Scikit-Learn, and Numpy
Applied Principal Component Analysis and a linear layer on a facial data set, achieving an 85% f1 test accuracy. Optimized the forward pass for efficient use with a Faster R-CNN network after facial regions are found. Presented results to class and wrote a paper on it.
Genentic Learning for Self Driving Cars | Python, Numpy, and Pygame
Created a 2D automobile physics simulation, and a procedural track to mimic real-world driving conditions. Implemented genetic learning to train a shallow neural network to drive autonomously within the simulation. Designed a fitness function that rewarded efficient and safe driving behavior, resulting in improved performance.
Object Detection with Faster R-CNNs | Python and Pytorch
Implemented a Faster R-CNN network for object detection, and trained it on PROPS achieving a 20\% mAP score. Utilized transfer learning by using RegNetX-400MF to speed up training time to only 3 hours. Calculated and implemented all forward and backwards steps for back-propagation by hand.
Github Contributions
Education
University of Minnesota - Twin Cities
September 2022 - May 2025
Bachelor of Science in Computer Science, Minor in Mathematics
Minneapolis, MN
Selected Coursework: Deep Learning For Robotics, Computer Vision, Real Time Embedded Systems, Computer Graphics, Optimal Filtering/Control, Algorithms and Data Structures, Real Analysis, and Differential Equations.
GPA: 4.0 | Transcript: Unofficial
Work Experience
Software Engineering Intern
May 2024 - August 2024
RTX, Collins Aerospace, Mission Systems, Embedded Low-Level Systems and Software
Cedar Rapids, IA
Accomplishments: Implemented fixes for 4 major and 6 minor bugs and developed 9 new features on a production team, 3x the expected total of 6 tickets.
Presented the Q3 Plan for the RCU Team to the Mission Systems Directorate, addressing over 200 people, and became the first intern to achieve this.
Skills Gained: Embedded Systems Development, Working in Secret Labs, Agile Development, and Computer Networking.
Development Platforms: The half-sized and full-sized Domestic Radio Control Unit for the ARC-210 Radio and the half-sized International Radio Control Unit for the AR-1500 Radio.
These platforms serviced many aircraft including the F/A-18 Hornet, F-15 Eagle, Air Force One, A-10 Warthog, C-17 Globemaster III, C-130 Hercules, V-22 Osprey, MQ-25, E-3 Sentry AWACS, HH-60 Pave Hawk, and many more.
Academic Experience
Teaching Assistant, Computer Vision
August 2024 - Present
University of Minnesota, College of Science and Engineering, Prof. Volkan Isler
Minneapolis, MN
Accomplishments: Designed homework, teaching students back-projection, homographys, RANSAC, stereo depth estimation, feature engineering, image filtering, SVM classifiers, and convolutional neural networks.
Developed an auto-grading system, improving efficiency by 7x.
Skills Gained: Technical Communication and a Deep Understanding of Core Computer Vision Concepts.
Undergraduate Robotics Researcher
September 2023 - Present
Robotics Perception and Manipulation Lab, Prof. Karthik Desingh
Minneapolis, MN
Accomplishments: Trained vision encoders using self-supervised learning for efficient imitation learning, applied to robotic arm policies in both simulation and on real hardware - UR5e Robotic Arm.
Currently evaluating pre-training methods with different image modalities to advance the field of pretraining.
Skills Gained: Self-Supervised Learning, Dataset Creation, Benchmarking, and Imitation Learning for Robotics.
Awards
Undergraduate Research Opportunity Scholarship
August 2024 - Present
Placed #1 at HackUIowa 2023: GitConnect Devpost
September 2023
