Evgeny Poliakov — Biomedical AI Engineer

I am an Associate Professor at Department №12 “Computer Systems and Technologies”, National Research Nuclear University “MEPhI” (Moscow). My work bridges artificial intelligence, medical imaging, and clinical oncology to build intelligent diagnostic tools for blood cancer and minimal residual disease monitoring.

🔬 Research & Engineering Focus

• AI-powered analysis of blood and bone marrow cells in acute leukemia
• Clinical Decision Support Systems (CDSS) for oncohematology
• Integration of medical data standards: DICOM, FCS, HL7 FHIR
• GPU-accelerated image processing pipelines (PyTorch, OpenCV, CUDA)
• End-to-end development of biomedical web platforms (Django, REST, Angular)

📚 Academic & Teaching

• PhD in Engineering Sciences (Candidate of Technical Sciences)
  “Methods and Models for Chromatin Structure Analysis in Bone Marrow Cell Nuclei for Automated Acute Leukemia Diagnostic Systems”
• MSc in “Electronics and Automation of Physical Installations”, MEPhI (2012)
• Teaching: AI in Healthcare, Neural Networks in Medical Imaging, NLP for Biomedicine, C++/Python
• Supervised: 2 PhD students, 2 MSc, 3 BSc (all successfully defended)

💻 Technical Stack

• Languages: C++, Python
• AI/ML: PyTorch, scikit-learn, OpenCV
• Web: Django, REST API, Angular
• Infra: Debian/Ubuntu, Nginx, Supermicro servers, QEMU/KVM, NVIDIA RTX 4060 + CUDA
• Standards: DICOM, HL7 FHIR, FCS

🏆 Grants & Collaborations

• RFBR #17-07-01496, #18-07-01456, #18-29-09115
• RSF #19-11-00176 (“AI for melanoma diagnosis”)
• Ongoing collaboration with N.N. Blokhin National Medical Research Center of Oncology

📄 Output

• 179 scientific and educational works
• 2 textbooks: “Digital Processing of Medical Images”, “Optical Microscopy Systems”
• 100+ peer-reviewed articles (Scopus / Web of Science)
• 10 patents + 20+ software registrations

🚀 Current Project (2025–2026)

“Next-Gen Clinical Decision Support System for Oncohematology” — integrating multimodal AI, FHIR/DICOM interoperability, and clinician-in-the-loop validation into a deployable diagnostic platform.