Portrait of Alexander Lebedev, MD PhD

Alexander Lebedev, MD PhD

MD PhD • Medical AI Engineer • Clinical and Technical Expert

Deep expertise in medicine & AI engineering for high-stakes systems

Lebedev Labs | Medicine × AI Engineering × Clinical Safety |    GitHub GitHub

About

Dr. Alexander Lebedev is an MD/PhD medical AI engineer with deep expertise in both medicine and advanced machine learning. He designs AI systems for real clinical environments where safety, reliability, and traceability are non-negotiable.

With 16+ years in advanced analytics and clinical research, he leads core technical decisions across architecture, risk controls, and model evaluation in high-stakes healthcare workflows.

He works with executive and product teams to reduce technical risk, strengthen model quality, and deploy trustworthy medical AI at scale.

Highlights

Core Expertise

Medical AI Architecture

Design production-grade AI/ML architectures for healthtech products, from data and model interfaces to safe inference patterns.

LLM Guardrails for Healthcare

Define and implement guardrails that reduce harmful outputs, improve reliability, and align model behavior with clinical risk constraints.

Clinical Evaluation & Safety Evals

Build evaluation frameworks for quality, safety, and failure-mode analysis to support responsible launch decisions.

AI Governance & Monitoring

Establish governance and monitoring practices for post-deployment performance, drift, and risk management in regulated environments.

Clinical-Grade Data/ML Pipelines

Build robust data and model pipelines with reproducibility, traceability, and operational controls required for healthcare contexts.

Technical Due Diligence for AI Health Products

Provide technical assessment for executive teams and investors on AI readiness, risk, and implementation quality across product, model, and infrastructure layers.

Selected Works

Function Health

Senior Medical AI Engineer leading medical AI R&D across architecture, guardrails, and evaluation design. Focused on building safer, production-ready AI systems and deployment governance for preventive health workflows.

AlphaROC

Developed seasonality analysis of financial transactions; created ML-based price forecasts and valuations for futures and stocks; performed alternative data analytics and automated financial report scraping.

Open Dialogue Space

Science Director. Leading R&D of the digital mental health platform, launched interactive data-informed dashboards for mental health monitoring, semantic pipelines for crisis detection.

Dreamseer

Co-founder. Leveraged cutting-edge NLP and AI to develop an innovative dream analysis platform, advancing mental health insights through technology.

Safehaven Hedge Fund

On-chain analytics, macro-market analysis, quantitative trading and hedging strategies, communications with clients.

OhCleo

Built LLM-powered chatbots, thematic content tagging, and speech-to-text workflows to enhance user engagement and platform personalization.

Katharsis Journeys Ltd

Co-founder. Strategic wellness partnerships with academia, NLP solutions driving 40% revenue growth, recognized as "Best Psilocybin Retreats in Europe" by Healing Maps.

Karolinska Institutet

Leveraged big-data analytics to inform public health policies on substance use and global societal dynamics. Spearheaded large-scale mental health and well-being initiatives. Led a clinical trial investigating psilocybin-based treatment for depression.

Stavanger University Hospital

Developed ML tools for clinical data analysis and secured NOK 1.5M in research funding, established international collaborations.

Aging Research Center

Coordinated the €1M project funded by the European Research Council, investigating cognitive and neurobiological plasticity. Oversaw the full lifecycle of a clinical trial—from protocol development and coordination to data analysis and final reporting.

Data Insights & Visualizations

BTC On-Chain Insights – price vs unspent miner supply with daily Δ.
BTC On-Chain Insights
BTC price vs. unspent miner supply change.
Workflow pipeline from Lebedev et al. (2014) – FreeSurfer & R analysis
Diagnostic Classification for Medical Data
From Lebedev et al. (2014) : Medical image data processing → high-dimensional feature extraction → ML classification & visualization.

Testimonials

Alexander is one of the most inspirational and brilliant minds I’ve encountered. A compassionate thinker who improves lives through innovation.

— Jonathan Dekle

A brilliant physician, scientist, and leader. His ability to listen, analyse, and guide with wisdom is rare.

— Tatiana Santini

Alexander brings together neuroscience, finance, behavioural economics and data to create inspiring, high-performing environments.

— Luigi Espasiano, MD

His expertise in big data analytics and statistical methods has been crucial in multiple high-impact research projects.

— Christoph Abé, PhD

He combines deep technical insight with creativity and rapid execution — nothing is impossible.

— Ivan Dimoski

A fantastic researcher and developer, warm and empathetic, with outstanding productivity and intelligence.

— Pierre de Boer

Vision & Mission

My mission is to turn rigorous clinical reasoning and strong engineering practice into medical AI systems that are reliable, measurable, and safe in real-world use.

Contact

For medical AI architecture, safety evaluation, or high-stakes product decisions, send a brief project note below.