Ivan Stepanov
Robotics & Automation Engineer and PhD Candidate in Mechanical Engineering at the University of Washington
About
I'm Ivan Stepanov, a Robotics & Automation Engineer and PhD Candidate at the University of Washington. My work focuses on the intersection of hardware and software, specifically designing vision-guided robotic platforms for automated microtissue handling in personalized oncology. My career has taken me from developing financial data systems to building ML pipelines for Boeing, and now to FolchLab, where I recently co-authored research in Science Advances on robotic drug testing. I am passionate about the reliability that automation brings to complex medical and industrial tasks. I’m currently looking to connect with professionals in the R&D space as I prepare for a transition to the European engineering market in 2027. I offer a unique blend of machine learning, computer vision, and physical hardware integration expertise.
Networking
What I can offer
- ›Bridge between high-level software (ML/CV) and physical hardware integration
- ›Expertise in medical and industrial R&D automation
- ›Experience with large-scale industrial data systems
Looking for
- ›Robotics, Automation, or R&D Engineering roles in Europe starting in 2027
- ›Collaborations with researchers in oncology and mechanical engineering
Best fit for
Current Interests
Background
Career
Transitioned from software engineering in finance to machine learning for aerospace manufacturing, currently specializing in vision-guided robotics for medical research.
Education
PhD Candidate in Mechanical Engineering at University of Washington; Master’s Degree in Mechanical Engineering from University of Washington (2021–2023); Bachelor of Science in Engineering Physics/Applied Physics from Bauman Moscow State Technical University (2016–2020).
Achievements
- ›Co-first author of a paper published in Science Advances (May 2024)
- ›Designed a unified automation system for microtissue handling and user-facing GUI
- ›Developed a defect prediction strategy for Boeing using large industrial datasets
Opinions
- Robotic integration leads to higher reliability in complex tasks like fluid and microtumor manipulation
- Research should be disseminated through open-access publishing