I am a graduate form Imperial College London skilled in Brain Machine interfaces, Neural decoders, Data analysis, Real-time systems, and Web development.
➡️ I seek opportunities in R&D, Neural Engineering, Project Management, and Web Dev.
Email: denis.grigoryev22@alumni.imperial.ac.uk
Mobile: +44 07444 369 408
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Studying BSc Computer Science at Queen Mary University of London I became curious about how computation is carried out beyond the world of man made computers.
Human brain - the most advanced biological processor has captured my attention and so I went on conducting a final year project titled “Relating brain information processing patterns to activities and inferring user state in passive brain-machine interfaces (pBCI’s)” where I investigated how the processing of brain signals without user’s direct intervention can be used to implicitly control a brain machine interface.
To pursue my academic passion further I enrolled at an MSc Biomedical Engineering with a focus on Neurotechnology at Imperial College London, meanwhile winning a highly competitive scholarship from the Department of Bioengineering. I have completed the masters thesis “Towards collision-free movement in arbitrary environments using a Fly-Robot-Interface” in the lab of Prof. Holger Krapp where I redesigned a brain-machine interface bio-hybrid robotic intelligent system (Fly-Robotic-Interface) used by the lab to investigate insect’s sensorimotor control mechanisms. My innovative and efficient system design will reduce coding and testing time in future research projects by 50%.
In spare time I participated in a G.tec medical engineering Spring School & Hackathon and experimented with using Visual Evoked Potentials (VEP) to control a Unity 3D game character, gaining skills in API integration and game design.
I have also moderated a global hybrid hackathon in neurotechnology NeuroTechX 2023.
- Redesigned software for a research platform to reduce coding and testing time in future research projects by 50%
- Developed modular and efficient system’s control algorithms in Python
- Conducted research on sensorimotor control mechanisms supervised by Prof. Holger Krapp
- Programmed web applications using HTML5, CSS3, PHP, JS, Bootstrap
- Developed prototypes in Figma and modeled software systems in Visual Paradigm
- Preprocessed and analysed large datasets of financial transactions (NASDAQ) in Python and Scala applying an efficient data processing model MapReduce
- Title: "Relating brain information processing patterns to activities and inferring user state in passive brain-machine interfaces (pBCI’s)"
- Carried out research and performed statistical analysis on EEG brain data to relate global neuronal co-activity patterns to specific activities like resting
- Analysed data using Python, matplotlib, pandas, and Jupyter notebook
- Deliverables: two formulas describing global brain activity during rest and a blueprint of a pBCI system that infers user sate based on these formulas
- Identified pain points and gathered insights on the mentoring programme during interviews with the client, resulting in a 50% increase in mentee satisfaction
- Elicited system’s requirements, produced actionable system design specifications improving our team’s productivity by 20%
- Co-developed a web app prototype in React and JavaScript
- Applied SCRUM Agile methodology to monitor team’s progress leading to meeting 100% of deadlines
- Received a prize for the best work out of 23 competing teams (link)
- Taught Object-oriented programming (OOP) concepts to 12 first-year college students
- Performed code review and provided individualized and detailed feedback
- NeuroTechX Global Hackathon 2023:
- Moderated a global hybrid hackathon in neurotechnology NeuroTechX 2023 (link)
- Took responsibility of communicating effectively with guest speakers and keeping the audience engaged throughout the event.
- Spring School & Hackathon, G.tec medical engineering:
- Designed a graphical brain-machine interface in Unity, leveraging user generated Visual Evoked Potentials (VEP) to control an animated game character in a neuroregenerative game aimed at patients with Parkinson’s disease
- QIncubator: Participated in a college enterprise programme & practiced finding a market opportunity, starting, and running a business
- London Business School Hackathon 2021:
- Proposed a blue carbon-based solution for corporations to offset their carbon footprint
- Co-developed a business model
- Co-created a website prototype in Figma
- Collaborated in a cross-disciplinary team of four
- Currently learning: Flask, Django, AWS, APIs, Python OOP, OpenCV, CI/CD