OLATUNJI MUMINI OMISORE

Research achievements and citations are available on Google Scholar.

As an emerging academic and researcher working on robot-assisted surgical interventions with over a decade R&D experience on intelligent robotics, control automation, and human-robot interactions, I have unique training underpinning development of medical devices (e.g. surgical robotics) and artificial intelligence for safe flexible-access interventions. My PhD at University of Chinese Academy of Sciences (CAS) aimed to reduce the global mortalities associated with top-killing diseases such as cardiovascular diseases, cancer, and diabetes. Thus, I designed and developed intelligent surgical robotic systems with learning-based strategies for intraluminal navigation. The dissertation included the first published study on predictive modeling for kinematics resolution in flexible surgical robotics. My expertise was strengthened with two-year post-doctoral research at Shenzhen Institutes of Advanced Technology. These largely expanded my skills on developing intelligent systems for robot-assisted surgical interventions, surgical skill assessment, surgical image processing and data analytics, and wide knowledge on leading and participating in-silico, in-vitro, and in-vivo studies.

I received the Lillian Gilbreth Research Fellowship at Purdue (2023), President's International Fellowship Initiative at CAS (2019), CAS-TWAS doctoral fellowship (2015); and awards like the Heidelberg Laureate award for outstanding young computer scientist (2020), the world robotics competition (Beijing, 2019), and travel award for IEEE ICIT (Canada, 2017).

Research Motivation and Aim

Operational hazards e.g. radiation exposure and orthopedic injuries faced by surgeons, and potential vessel damage are major issues now faced during endovascular interventions (EVI). Robotic systems are being embraced to reduce the operational challenges, but total control dependence relies on interventionists. Thus, robot-assisted EVIs are only done in a few hospitals, globally. My research aims to develop new methods and systems to improve outcomes of EVIs, surgical skill training/assessment, and surgeon-robot collaborative procedures. These could enhance patients' access to vascular healthcare, while also fostering perioperative safety of both patients and surgeons.

Main research interests

Robot-assisted intraluminal interventions with physics-based and AI-based navigation and vision systems (cases of gastrointestinal and intravascular treatments have been successfully investigated);
Real-time automated coronary artery analytics for robot-assisted cardiovascular interventions.
Multimodal sensor fusion and machine learning development for surgeon-robot collaboration and surgical skill assessment/training.
Surgical scene analytics through development of tool segmentation and registration, tracking methods for intelligent surgical systems;
Advanced wearable systems for operative data sensing, feedback, and skill monitoring in the field of robot-assisted interventions;

Major Achievements

Development of isomorphic robotic system for surgeon-robot collaborative catheterization during cardiovascular interventions;
Development of intelligent wearable glove interface for surgical skill evaluation and training during endovascular interventions.
Development of tool segmentation and tracking method in robot- assisted endovascular interventions;
Development of mutlimodal data warping and fusion for hand motion recognition in robot-assisted endovascular intervention;

Research Funding

1. Intelligent surgical skill learning during robot-assisted endovascular interventions

Role: Principal Investigator, 2022.01 ─ 2023.12;

Details: Ministry of Science & Technology, China. RMB 300,000 ($41,950 USD) .

1. Africentric Learning Design: Socio-culturally Sensitive & AI-driven E-Learning Platform for African Canadians

Role: External Collaborator, 2023.06 ─ 2025.05;

Details: Mitacs Accelerate Project, Canada. CAD 240,000 ($174,750 USD) .

1. COVID-19 automated contact tracing with privacy-preserving in Nigeria.

Role: Co-Investigator, 2021.01 ─ 2022.12

Details: Nigerian Tertiary Education Trust Fund. NGN 29 Million ($49,830 USD) .

1. Data-guided robotic catheterization for intelligent intravascular cardiac interventions

Role: Principal Investigator, 2020.06 ─ 2023.05;

Details: Shenzhen Natural Science Foundation. RMB 300,000 ($41,950 USD) .

1. Multimodal Data Fusion for Intelligent Robotic Intravascular Catheterization

Role: Principal Investigator, 2020.01 ─ 2021.12

Details: Natural National Science Foundation of China. RMB 310,000 ($43,340 USD) .

Selected Research Articles

O. M. Omisore, T. Akinyemi, A. Nguyen, and L. Wang, “Weakly-supervised Learning via Multi-lateral Decoder Branching for Guidewire Segmentation in Robot-assisted Cardiovascular Catheterization”, IEEE International Conference on Robotics and Automation, May 2025.
W. Du, G. Yi, O. M. Omisore, W. Duan, T. Akinyemi, X. Chen, J. Liu, B. Lee, and L. Wang#, “Analyzing Surgeon-Robot Cooperative Performance in Robot-assisted Intravascular Catheterization”, IEEE Transactions on Human-Machine Systems, Accepted: August 2024, IF = 3.5. Link.
O. M. Omisore, T. O. Akinyemi, W. Duan, W. Du, and L. Wang, “Multi-lateral Branched Network for Endovascular Tool Segmentation during Robot-assisted Catheterization”, IEEE Transactions in Medical Robotics and Bionics, 6(2):1-15, Jan. 2024. IF = 3.7. [Link].
O. M. Omisore, et al., “Weighting-based Deep Ensemble Learning for Recognition of Interventionists’ Hand Motions during Robot-assisted Intravascular Catheterization, IEEE Transactions on Human-Machine Systems, 53(1):215-227, IF= 4.124, January 2023. [Link]
O. M. Omisore, S. Han, X. Jing, H. Li, Z. Li, and L. Wang, “A Review on Flexible Robotic Systems for Minimally Invasive Surgery”, IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(1):631-644, IF=9.309, January 2022 IF=9.309, JCR Q1. [Link] [ESI Paper]
W. Du, O. M. Omisore, W. Duan, et al., "Exploring Operators’ Natural Behaviors to Predict Catheterization Trial Outcomes in Robot-assisted Intravascular Interventions", IEEE Transactions on Medical Robotics and Bionics, 4(3):682-95, August 2022. [Link]
O. M. Omisore, W. Duan, W. Du, and L. Wang, "A Deep Multimodal Network for Classification and Identification of Interventionists' Hand Motions during Cyborg Intravascular Catheterization", 17th IEEE CASE, August 2021, France. [Link]
O. M. Omisore, et al., “Towards Characterization and Adaptive Compensation of Backlash in a Novel Robotic Catheter System for Cardiovascular Intervention”, IEEE Transactions on Biomedical Circuits and Systems, 12(4):824-838, April 2018. IF=3.50, JCR Q1. [Link]
O. M. Omisore, S. Han, L Ren, A. Elazab, N. Azeez, T. Talaat, H. Li, and L. Wang, “Deeply-Learnt Damped Least-Squares Method for Inverse Kinematics of Snake-Like Robots”, Neural Networks, Elsevier, 107 (2018): 34-47, August 2018, IF=7.17, JCR Q1. [Link]
O. M. Omisore, B. Ojokoh, A. Babalola, T. Igbe, Z. Nie, Y. Folajimi, and L. Wang, “An Affective Learning-based System for Diagnosis and Personalized Management of Diabetes Mellitus”, Future Generation Computer System, 117, April 2021. IF= 6.125, JCR Q1. [Link]

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