Dr. Sujit Roy has an experience of 7 years in Research and Development in the field of Computer Science. A ceaseless aspirant for knowledge, he’s a developer, a programmer and have overseen SRInnoxy Corporation as Director, R&D, Computer Science Head, MRIIC and guided multiple projects with IIT Madras and IIT Patna.
Salient features of his experience include the areas of Deep Learning, Biomedical Research, Fluid Interface, Brain-Computer Interfacing, Image Processing, and Holography among others.
He has experience in the formulation and implementation of ML/DL frameworks into healthcare, IOT and Robotics domains. He is also considered a strategist for business development and hence has completed several business plans, customized market segment and industrial collaborations. He has also received funding for multiple projects from both Governments and private sectors. He has 5 filed patents and 2 copyrights to his name. He has also accomplished 30 research projects, the majority of which have fetched numerous awards, and few have also made it to the market.
He completed his Ph.D. in Computational Neuroscience at Ulster University and IIT Kanpur under UKIERI Fellowship. He has a keen interest and a proven track record for translating complex ideas into slick.
Key areas of experience include:
* Machine Learning/ Deep learning
* Biomedical signal processing
* Fluid interfaces
July '22 - Present Computer Scientist Level IV Step IV
NASA MSFC IMPACT
April '21 - June '22 Machine Learning Researcher
The University Of Manchester
Nov '17 - June '21 PhD in Computer Science
Ulster University, UK; IIT Kanpur, India
1. Improving the performance of BCI by channel selection in MEG and identifying Brain regions responsible for Motor movements, language, and arithmetic.
2. Designed a novel Deep learning architecture for transfer learning
3. Novel Generative network architecture to generate artificial EEG signals.
4. First MEG-compatible exoskeleton for stroke rehabilitation
Nov '17 - present Visiting Research Fellow
Indian Institute of Technology, Kanpur
Robotic Exoskeleton, Machine Learning, Position Tracking & Feedback
July '17 - Sept'17 SDE I
Venture7 Technology Private Limited, India
MVC architecture application development on C#
Jan '17 - Jun '17 Software Engineer Internship
SS Innovations China Co. Ltd., China
Software & Robotics Development on QTCreator platform
Aug '13 - Dec '16 Researcher & Innovator
Manav Rachna Innovation & Incubation Center (MRIIC), India
Software & Electronics Development, Image Processing, BCI & Project Management
Selected Work & Research
There have been quite a few interesting and life-learning experiences like being selected as the youngest researcher from The Manav Rachna Innovation and Incubation Center (MRIIC) or like being the gold medalist for the research paper presented at IACDE (2016), or say publishing and carrying out multiple research papers in the field of Neural Networking and bio-medical engineering as well.
Here are some of the key research and work experiences out of the many so far.
Brain Signal Mapping
As part of my research work, I am designing prediction-based model of motor movements for controlling robotic exoskeleton by stroke patients using MEG/EEG signals .
Working closely with the Professors and research team of the Indian Institute of Technology, Madras on Bio-Medical Projects and Hologram technologies.
Dentist posture belt
The solution provided is a novel posture correction apparatus based on an IMU capable of tracking tilt in three dimensions and an electromyography based sensor to measure and monitor the stress on the lower back specially desigend for dentists.
In my short career in research and product development (since 2015), I have delivered over 30 projects in the areas of Biomedical, machine learning, IOT and misceleneous. Many of the projects were the problem statements of an industry such as Medanta – The Medicity, MREI, okhla industrial area, technoplanets, techChefs, etc.
My current area of research is BCI for stroke reahabilitation using Magnetoencephalography, which includes algorithm developments for improving classification in real time BCI systems. Thus, my work is based on deep elarning models, ML models, feature selection and extraction.