Co-founder & CTO · Adaptly
Ilya Emelianov
Building the next-generation infrastructure for adaptive learning
Entrepreneurship with deep ML & platform execution
Architecture · Production systems · Market-grade delivery
Verified researcher
We engineer the machine learning layer and platform that make Adaptly’s closed-loop adaptive engine ship in production — not slide-ware: measurable learner signal, disciplined scope, architecture that scales.
Adaptly is a closed-loop AI learning ecosystem for programming and data science: adaptive paths, code-native lessons, and a mentor surface built as one coherent product system. The focus is product value and infrastructure readiness for international scale, including the European market.
Responsibility sits at the intersection of founder judgement and technical depth: ML stack, platform architecture, and production systems that turn adaptation into measurable outcomes.
The Thesis
The problem. Much of EdTech — classic MOOCs included — still runs a one-size-fits-all syllabus. That ignores cognitive diversity and drives high drop-out: passive consumption instead of an active, high-retention loop.
Our solution. Adaptly is a closed-loop system built around cognitive load optimisation and neural personalisation: we map progress and psychological feedback in near real time, adapt delivery and difficulty, and keep the learner inside one coherent path — engineering-first, market-serious.
What We Build
We design and ship the ML layer, data paths, and platform boundaries that make that thesis operational — real-time knowledge modelling, progress intelligence, and systems integration into a scalable product. Not research for its own sake: production architecture.
ML Systems
Adaptive modelling, knowledge tracing, and recommendation logic — engineered for production latency, not just notebooks.
Platform Architecture
Backend systems, data pipelines, and API design that keep the product coherent as it scales across markets.
Product Engineering
Translating ambiguous learning outcomes into measurable, testable, shippable software — with clear ownership of product and technical decisions.
Execution Speed
From whiteboard to working demo in days. Full-stack when needed, ML-first by default, always product-aware.
Adaptly
Psychology-aware adaptive learning for programming and data science:
personalised onboarding, code-native lessons, real-time progress intelligence, and a mentor surface —
engineered as one product system, not a feature list.
Unlike fixed MOOCs (Coursera, edX, Udacity) that ship the same syllabus on a fixed schedule, we run a closed-loop stack: the system reads cognitive signal, closes knowledge gaps with targeted delivery, and keeps the learner in a single coherent path — cognitive load optimisation and tutoring-at-scale mechanics, backed by production ML and platform discipline.
Public materials on GitHub describe scope and UI direction; backend, agents, and data architecture stay in private development. No over-promising in the open repo.
ML & Platform layer
Product · thought leadership
High-level ML systems manual — practitioner reference that reads as intellectual property, not a blog draft. Pairing a clean cover with the public repo signals depth and authoring discipline for diligence and visas alike.
GitHub →Stack & Tools
Core depth first, peripheral surface second. Everything listed has shipped in a real system.
Execution & proof
Shipped systems, nationally competitive algorithms, and long-form ML depth — framed for diligence on technical execution, not optics.
Focus & Trajectory
Primary focus: scaling Adaptly’s product and infrastructure — a global AI-native learning platform with EU-ready architecture and disciplined ML execution.
Concentration stays on the adaptive engine, platform boundaries, and evidence-backed delivery. Open to partnerships with investors, advisors, and collaborators who align on product depth and international scale — introduced on merit, not noise.