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Computer vision Robotics

Budapest, Hungary
December 21, 2020

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Oluwatosin Olatunde Alabi

Floor */**, **-** Ulloi ut: H-1091 Budapest. Tel: +447*********

Email: GitHub: Nationality: Nigerian EDUCATION

2020 – 2022 Pázmány Péter Catholic University Budapest (Current), Universidad Autónoma de Madrid, and University of Bordeaux (Coordinating University)

Image Processing and Computer Vision (IPCV) Erasmus Mundus Joint Masters Degree Relevant Coursework done in Image Processing, Data Mining and Machine learning, Design Patterns, Multimodal Sensor Fusion and Navigation, Parallel Computer Programming, and Numerical Analysis. Other courses to be taken before summer break 2021 include: Vision for multiple and moving cameras, Video Sequence Analysis, People detection and Biometrics, Tomography and 3D Imaging, Acquisition Reconstruction and Inverse Problems, Deep learning in Computer Vision. 2019 – 2020 University College London, U.K

MSc Robotics and Computation (Ongoing)

Relevant coursework in Robot Navigation, Multi-Agent Artificial Intelligence, 3D Geometry Acquisition and Processing, Machine Vision, and Numerical Optimization.

Dissertation on Deep Learning Optical Flow Method for Fetoscopic Mosaicking. Submitted as Paper at IEEE ISBI 2020. Awaiting Acceptance.

2012 – 2017 University of Ilorin, Ilorin, Kwara State Result: First Class Honours B.Eng. Electrical and Electronics Engineering CGPA: 4.59/5.00 Relevant coursework in Engineering Mathematics, Applied Computer Programming, Digital Electronics and Microprocessors, Networking and Communication, Graphics, and Signal Processing. Dissertation on Affordable Home Automation Systems; Specialized degree in Computers and Control. WORK EXPERIENCE:

Software Developer at Techspecialist Consulting Limited, F.C.T Abuja Dec 2017 – Jun 2019 Utilized various web technologies to develop custom applications to ease organizational processes. Completed applications on in-house procurement, employee appraisal, and bus transport ticketing and payment. Taught students JavaScript during bootcamps organized by my employers.


Instructor at AI Saturdays Abuja Nigeria Jan 2019 – Sept 2019 Taught classes on Python, GIT, and select topics in math. Organized and graded assignments. Developed a demo for the students on a document classification system using Tesseract-OCR and OpenCV to extract data from certificates and classify them based on text-content.


• Programming languages: C++ (Intermediate), Python (Intermediate), Java (Intermediate),

• Deep learning frameworks: Tensorflow (Intermediate) and PyTorch (Intermediate)

• Web technologies: HTML (Proficient), CSS (Proficient), JavaScript (Proficient), Vue JS(Intermediate), Node JS(Intermediate), SQL(Intermediate).

• Robotic Tools, Frameworks and other skills: Robotic Operating System (Intermediate), MoveIT (Intermediate) and MATLAB (Intermediate)

• Microcontrollers: Arduino (Intermediate), Raspberry Pi (Basic) RELATED COURSEWORKS:

Implement Support Vector Machines Spring 2020

Implemented SVM from scratch for multi-classes classification problem using various optimization techniques such as penalty method, primal dual interior point method. Non-linear classifications also explored with various kernel functions. Forest Cover Type Prediction Winter 2020

2-layer stacked model is trained to predict cover types using with first layer containing KNN, multi-class SVM and random forest classifiers. A decision tree is used as the 2nd layer. The stacked model is trained using cross-validation-like scheme. Counterfactual Cover Type Prediction Spring 2020

Implementation of the Counterfactual Multi-Agent Policy gradient paper by Jakob N. Foerstar et al. It is a multi-agent actor critic method which utilized a centralized critic and decentralized actors. It utilized a counterfactual baseline to addess the multi-agent credit assignment problem.

Image Stitching Algorithms Summer 2020

Implemented Feature-based Stitching by estimating Affine transformation using the Levenberg-Marquardt Optimization and RANSAC. Implemented dense stitching using Pyramidal Lucas-Kanade Method. These were used as comparison for the method used in my dissertation; I used the FlowNet-2 optical flow deep learning architecture to estimate flow-fields on fetoscopic images and perform Image stitching with estimated flow-fields. AWARDS:

Erasmus Mundus Scholarship for the IPCV program, Petroleum Development Technology Fund MSc Scholarship (2019–2020), University Scholar for Electrical and Electronics Engineering Department (2013–2017), Agbami Medical and Engineering Professional Scholarship Award (2014–2017), Best (1st) chemistry student in Nigeria Secondary School competition organized by Chemical Society of Nigeria (CSN) (2011), Best Mathematics Student, Kwara State Mathematics Association of Nigeria Competition

(2011), Bronze medal in Biology (National) Nigerian Mathematics and Science Olympiad (2011). ADDITIONAL SKILLS, CERTIFICATIONS AND PROFESSIONAL MEMBERSHIPS: Languages: English (native), Yoruba (fluent), French (basic) Professional Memberships and Certifications: Member of the Nigerian society of Engineers, Microsoft Certified Programmer in Front-End Technologies, Member National Anti-Corruption Corps Nigeria.

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