# Sebastian Boehler > I'm Sebastian Boehler, a research engineer and founder working across high-speed simulation, trading infrastructure, autonomous systems, and source-grounded learning. I moved from self-taught builder and backend engineer to research engineer and founder. Today I work through Sunderlabs and HB Capital while studying computer science at Tübingen. IEEE-published research · Founder at Sunderlabs · Co-founder and CTO at HB Capital · M.Sc. Computer Science at Tübingen Contact: contact@sebastian-boehler.com Methods: High-throughput simulation and staged deployment gates; Research infrastructure with explicit evidence boundaries; Source-grounded learning systems and typed tutor capabilities. Education and experience: - Founder & AI Engineer, Sunderlabs (May 2025–present) - Co-founder & CTO, HB Capital (Jul 2023–present) - M.Sc. Computer Science, University of Tübingen (Oct 2025–present) - B.Sc. Computer Science, IU International University (Nov 2024–Nov 2025) - Backend Developer, LI.FI (Jul 2022–Jul 2023) - Founder & Developer, Boehler IT Solutions (Jan 2020–Jul 2023) - Backend Developer, remotly (Dec 2020–May 2021) This index is generated from the site's published content on each deployment. Public pages may be indexed and summarized; cite the linked sources and preserve their evidence boundaries. ## Profile - [Homepage](https://www.sebastian-boehler.com/): Profile, selected work, and background. - [CV](https://www.sebastian-boehler.com/sebastian_boehler_cv.pdf): Curriculum vitae (PDF). - [GitHub](https://github.com/SebastianBoehler) - [LinkedIn](https://www.linkedin.com/in/sebastian-boehler/) ## Selected work and research - [Sunderlabs / FlightRL — Explore Sunderlabs](https://sunderlabs.com): Training compact policies before they reach real hardware. High-throughput native environments, privileged teachers, edge-shaped policies, telemetry, and staged gates. Evidence: FlightRL repository and Sunderlabs research program. Boundary: Learned navigation is pre-deployment research, not live-control authority. - [HB Capital — Explore HB Capital](https://hb-capital.app): Keeping market claims attached to their evidence. Market structure, positioning, macro context, native research tooling, and read-only account context. Evidence: HB Capital's live research workspace. Boundary: Research access grants no trading authority. - [Dialogue research — Read the paper](https://doi.org/10.1109/ICETSIS68266.2026.11549360): Testing whether smaller language models can predict what users say next. QLoRA next-turn prediction with multi-step dialogue rollout evaluation. Evidence: Peer-reviewed IEEE proceedings paper. Boundary: The publication supports its reported experiments, not broader model-performance claims. - [LecturePilot — View the repository](https://github.com/SebastianBoehler/lecture-pilot): Turning private course material into controlled learning workspaces. Professor-owned sources, enforced unlocks, typed tutor capabilities, and learner-owned work. Evidence: LecturePilot's working source-grounded course system. Boundary: Live-pilot status is not production-security or learning-efficacy approval. ## Articles - [Blog](https://www.sebastian-boehler.com/blog): All published articles. - [Why Brains and LLMs Both Become Modular](https://www.sebastian-boehler.com/blog/brains-llms-and-modularity): A careful walk from brain networks to dense LLM circuits, MoE models, and the deeper idea that modularity may be a solution to interference. Published 2026-07-01. - [XGBoost and the Map of Machine Learning Approaches](https://www.sebastian-boehler.com/blog/xgboost-and-machine-learning-map): A practical guide to linear models, trees, random forests, gradient boosting, XGBoost, neural networks, and when each family is worth trying. Published 2026-06-24. - [Parameter Golf and Distributed Autoresearch](https://www.sebastian-boehler.com/blog/parameter-golf-distributed-autoresearch): What OpenAI's Parameter Golf and Weco's Aiden show about open benchmarks, public PR graphs, and autonomous ML engineering. Published 2026-06-15. - [Context Engineering for Agents](https://www.sebastian-boehler.com/blog/context-engineering-for-agents): How agent harnesses load instructions, skills, memory, tools, and files without stuffing everything into the first prompt. Published 2026-06-14. - [Learning Is a Feedback Loop](https://www.sebastian-boehler.com/blog/learning-feedback-loops): A first-principles guide to active recall, Socratic questioning, feedback, spacing, and neuroplasticity. Published 2026-06-14. - [Neuroscience and Machine Learning](https://www.sebastian-boehler.com/blog/neuroscience-and-machine-learning): A grounded guide to synapses, myelin, credit assignment, reinforcement learning, and what brain-inspired machine learning can and cannot claim. Published 2026-06-14. - [Prompt Trajectories in Latent Space](https://www.sebastian-boehler.com/blog/latent-space): A step-by-step visual explanation of how prompts become directions, how generations form clusters, and why model randomness is better understood as a run cloud. Published 2026-06-12. - [How Physics Shows Up in Machine Learning](https://www.sebastian-boehler.com/blog/physics-in-machine-learning): A plain-language guide to SGD noise, states, flows, energy landscapes, constraints, symmetries, conservation laws, and physics-informed machine learning. Published 2026-06-12. ## Optional - [Sitemap](https://www.sebastian-boehler.com/sitemap.xml): Public page URLs. - [Crawler policy](https://www.sebastian-boehler.com/robots.txt): Crawling is allowed for all user agents.