Training & Consulting
I offer three training and consulting tracks, each adapted to your team's level and objectives, from academic labs to enterprise R&D units and startups. Available online or on-site.
Generative AI Integration
From prompt engineering fundamentals to fine-tuning small language models (SLMs) and building RAG pipelines over your documents. The depth and tooling depend entirely on your audience: executives get a strategic overview, engineers get hands-on with model deployment, and research teams learn to build specialized pipelines. The CoGenAI serves as a reference implementation for labs and enterprises wanting their own secure, tailored AI environment.
- Prompt engineering fundamentals
- Fine-tuning and deploying SLMs
- Building RAG pipelines over your documents
- Evaluating and ranking model outputs
- Strategic overview for decision-makers
- Hands-on deployment for engineering teams
Signal Processing & Wearable Systems
Bridges research methodology with engineering execution. Beyond the hands-on technical stack, this track teaches teams how to formulate investigable R&D questions, design rigorous experiments, conduct literature-driven gap analysis, and structure hypothesis-driven development cycles. Covers the full chain from research question formulation and sensor selection through embedded firmware, DSP pipelines, and validation protocols. Built for research labs transitioning from concept to prototype, and industry teams needing to level up their in-house biosignal R&D expertise. Includes live demonstrations and direct work on your team's current problems.
- Formulating R&D questions and hypothesis-driven development
- Literature gap analysis and state-of-the-art positioning
- Experiment design, data collection protocols, and bias control
- Sensor selection and signal acquisition
- DSP pipelines: filtering, feature extraction
- Algorithm design and benchmarking
- Embedded firmware and edge deployment
- Validation protocols and documentation
- Live demonstrations and team problem-solving
AI Tools & Workflow Integration
Practical consulting for startups, enterprises, and research labs that want to meaningfully integrate AI tools into their daily workflows, not just experiment. I help teams cut through the noise and adopt the right tools for their context with concrete, immediately applicable examples. This includes AI-assisted coding (vibe coding), automated documentation, literature synthesis, meeting summarization, email drafting, data analysis copilots, and custom internal tooling via no-code/low-code AI platforms. The goal is productivity, not hype.
- AI-assisted coding: vibe coding, Copilot, Cursor, Claude Code
- Automated literature review and research synthesis
- Meeting summarization and knowledge base building
- Custom internal AI tools with no-code/low-code platforms
- Data analysis copilots: natural language queries on your data
- Workflow audit: identify where AI actually saves time vs adds overhead