Vladimir Dyachkov, Ph.D
Editor-in-Chief of itinai.com
AI Product Leader
- Digital Transformation Expert
- Ph.D. in Economics
My expertise lies in transforming complex data into actionable insight, leading cross-functional teams, and ensuring every piece of content on Itinai.com meets the highest standards of quality, accuracy, and real-world applicability.
I believe that AI is only as powerful as the human insight guiding it.
At Itinai.com, I lead our editorial strategy to reflect principles:
As Chief Editor at Itinai.com — a platform at the intersection of artificial intelligence, digital healthcare, and global innovation. With over 15 years of experience in AI product development, agile transformation, and digital strategy, I bring a research-backed, user-centric approach to content leadership.
- Trustworthiness: Every article is fact-checked, and openly sourced
- Experience: Backed by 15+ years in AI, healthcare, and fintech across 10+ countries
- Expertise: Ph.D. in Economics with AI focus, hands-on ML product deployment
- Authoritativeness: Published across high-traffic platforms; built products used by millions
📘 Experience
🌍 Global AI Leadership
- Chief Product Officer, Digital Medical Products (2016–Present)
Led seven AI-driven product launches, including a WHO-based diagnostic tool structured around ICD-10. - Chief Transformation Officer, Lykke (2019–2020)
Oversaw international team restructuring, boosting agility and strategic alignment. - Senior Product Owner, goTRG (2018–2019)
Reduced time-to-market by 50% through agile adoption across eight teams, saving $120K/month in DevOps. - Product Leader, Alfa-Bank (2017–2018)
Managed the top-rated Alfa Mobile banking app, integrated Apple/Google/Samsung Pay services. - CPO, Price.ru (2014–2016)
Implemented AI-powered cataloging for over 30M products, doubling lead-based revenue. - Product Manager, RIA Novosti (2011–2014)
Oversaw content in 18 languages, serving 180M+ users monthly.
💡 Expertise & Focus
- AI/ML & Data Science: Computer vision, NLP, and predictive modeling
- Digital Product Strategy: From idea to launch across global markets
- Agile & Scalable Architecture: Cloud-native, API-first ecosystems (AWS, Azure, GCP)
- User-Centric Design: Figma prototyping, UX/UI, and personalization
- Content Trustworthiness: Ensuring medical, financial, and AI content is sourced, cited, and verified
🎓 Education
- Ph.D. in Economics, TSU – Research focus: Informational Influence in Economic Systems
- Master’s Degree, TSU – Financial Management & Information Systems
Your Success is Our Guarantee
✅ 15+ Years of Experience in AI and Digital Products
We’ve worked with businesses of all sizes—from startups to enterprises—delivering real value through intelligent, scalable solutions.
🛠 Proven Methodologies
We use only time-tested approaches that are focused on results, not buzzwords. Every tool, model, or process we implement is grounded in evidence and industry best practices.
📊 Measurable Outcomes
We define clear goals, track performance, and stay accountable for delivering success. If it can’t be measured, it can’t be improved.
🚀 Free AI Jumpstart
Discover where your business can reduce costs and grow—risk-free. Our AI audit reveals hidden opportunities with no upfront commitment.
🔍 Transparency at Every Step
From the first meeting to final delivery, you’ll understand the roadmap, the stages, and how each action contributes to your business goals.
📬 Contacts
Join the community of AI experts with Vladimir
- 🔗 LinkedIn https://www.linkedin.com/in/uxproduct
- 🔗 X: x.com/vlruso
- 📧 info@itinai.com
- 📱 Telegram: @itinai
Editor-in-Chief itinai.com Picks
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AI for Legal Document Analysis
AI for Legal Document Analysis: A Deep Dive into LegalAI Reviewer The pressure is relentless. Legal departments are being asked to do more with less, navigating an increasingly complex web of regulations while simultaneously being judged…
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Stability AI Releases Stable Code 3B: A 3 Billion Parameter Large Language Model (LLM) that Allows Accurate and Responsive Code Completion
Stable AI’s new model, Stable-Code-3B, is a cutting-edge 3 billion parameter language model designed for code completion in various programming languages. It is 60% smaller than existing models and supports long contexts, employing innovative features such…
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MIBench: A Comprehensive AI Benchmark for Model Inversion Attack and Defense
Understanding Model Inversion Attacks Model Inversion (MI) attacks are privacy threats targeting machine learning models. Attackers aim to reverse-engineer the model’s outputs to reveal sensitive training data, including private images, health information, financial details, and personal…
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Top Generative AI Use Cases for Healthcare to Enhance Patient Experience.
Generative AI has revolutionized the healthcare industry, particularly in enhancing patient experience. It offers several use cases, such as personalized treatment plans based on patient data, generating synthetic data for research, enhancing medical imaging quality, creating…
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Google DeepMind Researchers Propose GenRM: Training Verifiers with Next-Token Prediction to Leverage the Text Generation Capabilities of LLMs
Practical Solutions and Value of Generative AI Challenges in Generative AI Models Generative AI models are crucial in various applications, but they often need help with the accuracy and reliability of their outputs. This is particularly…
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How Faithful are RAG Models? This AI Paper from Stanford Evaluates the Faithfulness of RAG Models and the Impact of Data Accuracy on RAG Systems in LLMs
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From ONNX to Static Embeddings: What Makes Sentence Transformers v3.2.0 a Game-Changer?
Growing Need for Efficient AI Models There is an increasing demand for AI models that provide a good balance of accuracy, efficiency, and versatility. Many existing models face challenges in meeting these needs, especially in both…
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If the World Ends, What’s the Likelihood You Witnessed It?
The article discusses using data science to calculate the probability of being alive at the end of the world, based on historical human birth rates and population data. By leveraging the SciPy library, the project fills…
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Kolmogorov-Arnold Networks (KANs): A New Era of Interpretability and Accuracy in Deep Learning
Discover Kolmogorov-Arnold Networks (KANs) Enhancing Interpretability and Accuracy in Deep Learning Explore how KANs offer a compelling alternative to MLPs, leveraging mathematical concepts to enhance interpretability and accuracy in deep learning. With ongoing research aiming to…
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Decoupling Tokenization: How Over-Tokenized Transformers Redefine Vocabulary Scaling in Language Models
Understanding Tokenization in Language Models What is Tokenization? Tokenization is essential for improving the performance and scalability of Large Language Models (LLMs). It helps models process and understand text but hasn’t been fully explored for its…
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DeepMind’s CEO draws comparison between AI risks and the climate crisis
Google DeepMind CEO, Demis Hassabis, has called for AI risks to be treated as seriously as the climate crisis. He emphasized the need for an immediate response to the challenges posed by AI and suggested the…
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OpenResearcher: An Open-Source Project that Harnesses AI to Accelerate Scientific Research
The Role of AI in Scientific Research Addressing Challenges with AI Solutions The exponential growth of scientific publications presents a challenge for researchers to stay updated. AI tools such as Scientific Question Answering, Text Summarization, and…
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This company is building AI for African languages
Lelapa AI, a collaboration between Jade Abbott and Pelonomi Moiloa, is working to create AI tools specifically designed for African languages. Their latest tool, Vulavula, can convert voice to text and detect names of people and…
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Meta Releases Aria Everyday Activities (AEA) Dataset: An Egocentric Multimodal Open Dataset Recorded Using Project Aria Glasses
The introduction of AR and wearable AI gadgets is advancing human-computer interaction, allowing for highly contextualized AI assistants. Current multimodal AI assistants lack comprehensive contextual data, requiring a new approach. Meta’s Aria Everyday Activities (AEA) dataset,…
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This AI Paper by Scale AI Introduces GSM1k for Measuring Reasoning Accuracy in Large Language Models LLMs
Machine Learning in Artificial Intelligence Machine learning focuses on creating algorithms that enable computers to learn from data and improve performance over time. It has revolutionized domains such as image recognition, natural language processing, and personalized…
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This AI Research from Stability AI and Tripo AI Introduces TripoSR Model for Fast FeedForward 3D Generation from a Single Image
Research in 3D generative AI has led to a fusion of 3D generation and reconstruction, notably through innovative methods like DreamFusion and the TripoSR model. TripoSR, developed by Stability AI and Tripo AI, uses a transformer…