Sebastian Raschka
Summary: Staff Research Engineer at Lightning AI. Author of "Python Machine Learning," "Machine Learning with PyTorch and Scikit-Learn," "Build a Large Language Model (from Scratch)." PhD from Michigan State University. Writes exceptional technical deep-dives (blog, Substack). Published detailed explainer on DeepSeek DSA. Strong educator + practitioner — potential PhD advisor or industry mentor.
Profile
| Field | Details |
|---|---|
| Current Role | Staff Research Engineer, Lightning AI |
| PhD | Michigan State University (Computer Science / ML) |
| Key Books | "Python Machine Learning" (3rd ed), "Machine Learning with PyTorch and Scikit-Learn", "Build a Large Language Model (from Scratch)" |
| Blog/Substack | sebastianraschka.com, magazine.sebastianraschka.com |
| Twitter/X | @rasbt |
| GitHub | rasbt |
| Research Interests | LLM training, efficient attention, ML education, PyTorch, Lightning |
Significance for You
Multiple connection points:
| Connection | Relevance |
|---|---|
| DSA explainer author | Your DSA-ViT project directly builds on DSA; his blog is a reference |
| Lightning AI | Industry lab with PhD-style research; potential internship/collab |
| Educator + practitioner | Rare combo — great for learning how to communicate research |
| Book author (LLM from Scratch) | Your BSAI background matches his teaching style |
| PhD from MSU | Academic track → industry research; good perspective on both paths |
Target tier: Tier 2-3 (industry research, not traditional PhD advisor, but excellent mentor/network node)
Key Technical Content (from DSA blog)
His DeepSeek DSA blog covers:
- Indexer — Lightning indexer:
I_{t,s} = sum w^I_{t,j} · ReLU(q^I_{t,j} · k^I_s) - Token Selector — Top-k on index scores:
S_t = {c_s mid I_{t,s} ∈ Top-k} - Core Attention — MQA on selected tokens
- MLA Integration — DSA instantiated under MLA MQA mode (shared latent KV)
- Training Stages — Dense warmup (KL on indexer) → Sparse training (KL on selected + LM loss)
Your DSA-ViT project can cite this as accessible reference.
Contact Strategy
When: Anytime (active on X, responds to thoughtful replies) How: X reply / DM / email (listed on website) Angle:
- Reference his DSA blog in your project
- Ask specific technical question about DSA→ViT adaptation
- Share your DSA-ViT project page
- Lightning AI internship inquiry (Summer 2025)
Not for: Direct PhD supervision (industry role), but excellent for:
- Industry mentorship
- Internship referral
- Technical feedback
- Networking to academic collaborators
Related Wiki Pages
- dsa-attention — Concept page (his blog is a source)
- paper-deepseek-v3-2 — Original DSA paper
- vision-transformer-dsa-integration — Your project applying DSA to ViT
- lightning-ai — His employer (create if needed)
- target-labs — Your PhD target list
Sources
- web-sebastianraschka-dsa: Blog post "DeepSeek Sparse Attention (DSA) Explained"