🎓 MS AI @ USC | 🤖 Robotics Research @ USC ISI | ⚡ ML Engineer @ Lineslip Solutions

Physics-informed ML engineer building intelligent systems for robotics, energy, and autonomous systems. I specialize in optimization algorithms, multi-physics modeling, and sensor fusion for real-world physical systems.

@ USC Information Sciences Institute - Polymorphic Robotics Lab

• 🦾 Developing distributed optimization algorithms for autonomous multi-robot coordination
• 📡 Multi-modal sensor fusion (camera + IR) achieving 96% tracking accuracy with sub-50ms latency
• 🔄 Simulation-to-hardware validation pipeline deploying control algorithms on physical robots
• 🏗️ CI/CD frameworks for real-time control system testing and validation

@ Lineslip Solutions

• 🚀 Production RAG pipelines serving 10K+ queries/day with sub-second latency
• ⚡ Achieved 40% performance improvement through algorithmic optimization and quantization
• 🔧 Automated CI/CD pipelines and monitoring systems for production ML deployment

I'm passionate about applying AI and optimization to solve challenging problems in:

• 🔋 Energy Systems - Battery optimization, thermal management, renewable energy
• 🤖 Robotics & Autonomy - Perception, control, multi-agent coordination, GNC
• ✈️ Aerospace - eVTOL, spacecraft guidance, propulsion optimization
• ⚛️ Clean Energy - Nuclear reactor modeling, digital twins, predictive maintenance

Core Competencies

• Distributed Optimization • Multi-Physics Modeling • Sensor Fusion & State Estimation
• Real-Time Control Systems • Physics-Based Simulation • Predictive Analytics

Programming & Frameworks

• Languages: Python (Expert) • C/C++ • CUDA • MATLAB • JavaScript
• ML/AI: PyTorch • TensorFlow • Computer Vision (RAFT, ViT) • LLMs (Llama, QLoRA)
• Robotics: ROS • Sensor Fusion • SLAM • Path Planning • Multi-Agent Systems
• Production: FastAPI • Docker • CI/CD • Elasticsearch • Git • Linux

Domains

• Computer Vision • Production ML Systems • Robotics • Optimization Algorithms • Deep Learning

• 📝 First-author publication at AHFE Hawaii 2024 (AI-facilitated interfaces)
• 🥇 55th Annual Senior Design Conference Session Winner - Santa Clara University
• 🤖 96% tracking accuracy on distributed multi-robot coordination (USC ISI)
• 🎬 Trained neural style transfer on 118K images with distributed GPU training
• 👁️ 77% accuracy Vision Transformer on 101 food categories (75K+ images)
• ⚡ Built production systems serving 10K+ queries/day with 40% performance gains

Production-scale video processing achieving 6.45 FPS on 1080p video

• RAFT optical flow for temporal consistency and ego-motion estimation
• Trained on 118K images using distributed PyTorch DDP with custom CUDA kernels
• 30% training speedup through CUDA optimization
• Technologies: PyTorch, CUDA, RAFT, Computer Vision

Large-scale image classification on 75K+ images achieving 77% accuracy

• Fine-tuned Vision Transformer (ViT) architecture using transfer learning
• Data augmentation and preprocessing pipeline for 100+ food categories
• Technologies: PyTorch, Vision Transformers, Transfer Learning

AI-powered motivational coaching with fine-tuned Llama 3.2 LLM

• QLoRA PEFT for culturally-aware content generation (sub-200ms latency)
• Full-stack web application with goal tracking and journaling
• Won 55th Annual Senior Design Conference Session Award
• Technologies: Python, Llama, QLoRA, Firebase, Web Development

Creative Collaborator: AI-facilitated UI for Creating Engaging and Insightful Memes
First Author | AHFE Hawaii 2024 | DOI: 10.54941/ahfe1005579

Explored AI-assisted creative interfaces using GPT-3.5 for educational content generation. Comparative user study demonstrated enhanced productivity, creativity, and satisfaction, highlighting AI's potential to augment human creativity.

• 💼 LinkedIn
• 📧 rjnickel@usc.edu
• 📍 San Francisco Bay Area, CA
• 🎯 Open to roles in: Robotics • Energy Systems • Autonomous Vehicles • Aerospace

I believe the most impactful engineering happens at the intersection of AI and physical systems: where optimization algorithms meet real hardware, where simulation validates on robots, and where intelligent systems solve tangible problems in energy, robotics, and aerospace.

🔍 Looking for: Summer 2026 opportunities in robotics, clean energy, autonomous systems, and aerospace
🌟 Specialization: Physics-informed ML engineering for real-world physical systems