Curriculum Vitae

Education

• Ph.D. in Cognitive Science, Universität Osnabrück, 2024
• MSc. in Mathematical Sciences, African Institute of Mathematical Sciences, 2021
• MSc. in Computer Science and Engineering, University of Dhaka, 2020
• BSc. in Computer Science, University of Makeni, 2017

Work experience

• 2021-Present Research Associate
  • Research Training Group (RTG) in Computational Cognition, Universität Osnabrück
  • Duties included: Conduct basic research at the interface of Cognitive Science and Deep Learning with particular emphasis on building computational models of Individual Recognition – a ubiquitous phenomenon in social species like humans.
• 2017-2018 : Research Teaching Assistant
  • University of Makeni
  • Duties included: Teaching undergraduate Computer Science courses in Principles of Programming Languages, Introducion to Computing, Web Programming, Relational Database Systems theory and practice
  • Supervisor: Lakshamana Namamula Rao
• 2018: Research Assistant
  • Limkokwing University of Creative Technology
  • Duties included: Teaching undergraduate Computer Science courses in Principles of Programming Languages and Introducion to Computing
  • Supervisor: Aiah James
• 2017-2018 : College Registrar
  • African Accents International Institute of Computer Technology
  • Duties included: Oversight of Enrollment, coodination of outreach activities
  • Supervisor: Mustapha Jalloh

Conferences, Workshops & Seminars

• 05/2018 – 07/2018 – UNESCO-ICHEI, China
  • Seminar on ICT in Higher Education Innovation for African Countries. Attained knowledge in the role of informatization of higher education to improve learning outcomes. The seminar entailed hands-on training in Big Data management with Apache Spark and predictive analytics with Machine Learning techniques to improve learning outcomes.
• 31/07/2022 – 06/08/2022 – German Primate Center in Göttingen, Germany
  • Bridging the technological gap – spreading technological innovations in the study of the human and non-human mind. A workshop that brought early-stage researchers to share ideas on cutting-edge technologies to facilitate animal behavior and cognition research. Link: here
• 6/08/2022 – 07/08/2022 – Insitute of Cognitive Science in Osnabrück University, Germany
  • Bridging the Gap between Biological and Artificial Neural Networks” at the (Research Training Group (RTG) in Computational Cognition). Co-organized the workshop that brings together experts from diverse but intersecting fields pursuing research in understanding the mechanisms that give rise to intelligence in biological and artificial systems. Link here

Summer Schools

• 11/09/2022 – 16/09/2022 - Mediterranean Machine Learning school,Università Milano Bicocca, Milan, Italy
  • The Mediterranean Machine Learning (M2L) summer school comprised 5 days of keynotes, lectures, and practical sessions covering the breadth and depth of deep learning from cutting-edge research to practice. Link here
• 11/07/2022 – 29/07/2022 - Neuromatch Academy: Deep Learning, Virtual
  • The Deep Learning (DL) course covers team-based hands-on training in the theoretical underpinnings and practical approaches of current DL algorithms. The three weeks of intensive training involve the complete DL workflow from data curation to exploratory data analysis to model design, implementation, evaluation, and reporting. These algorithms range from Logitic Regressors to Transformers and everything in between.Link here
• 07/2021 – 07/2021 - Eastern European Machine Learning Summer School, Virtual
  • Covered the breadth and depth of deep learning from basic principles like backpropagation, to attention mechanisms and reinforcement learning. Link here
• 07/2020 – 08/2020 - Oxford Machine Learning Summer School, UK
  • Bayesian ML, Computer Vision, Natural Language Processing, Reinforcement Learning, Causal ML, Topological ML, and Transfer Learning. Link here
• 07/2020 – 08/2020 - Machine Learning Summer School-INDO, Indonesia
  • Machine Learning Fundamentals, TensorFlow, Convolutional Neural Network, Advanced Topics in Equivariance and Inductive Biases, Bayesian Machine Learning, Information Theoretic Objectives, and Robust Generalization, Computational Morphology, Reinforcement Learning, Probabilistic Generative Models, VAEs and Flows, Deep Learning for NLP, Graph Neural Nets, Transfer Learning for NLP, Multilingual NLP, Super-resolution and its Application to Computer Vision Tasks. Link here

Additional Certifications

• 08/2023 - 09/2023 - IBM AI Engineering Professional Certificate, Virtual
  • Introduction to Deep Learning & Neural Networks with Keras. Link here
• 02/2023 - 08/2023 - IBM Data Science Professional Certificate, Virtual
  • Specialization Certificate. Link here
• 03/2023 - 04/2023 - University of Michigan, Virtual
  • Python Data Structures. Link here
• 08/2020 – 09/2020 - MathWorks Training Service, MOOC
  • Deep Learning for Image Recognition. Using Pre-trained Networks, Managing Collections of Data, and Performing Transfer Learning.
• 08/2019 – 06/2020 - Imperial College London, Virtual
  • Mathematics for Machine Learning Specialization: Linear Algebra, Multivariate Calculus, and Principal Component Analysis. Link here
• 09/2016 – 10/2016 - On-Campus Internship Programme (OCIP), University of Makeni, Sierra Leone
  • Installation and configuration of software, computer networking, troubleshooting, and maintenance.

Skills

• Computing
  • Knowledge of algorithm discovery and representation
  • Agile and defensive programming
  • Mathematical Modelling and Optimization
  • Software Engineering processes
• Leadership Skills

Publications

Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification

Yusuf Brima, Mossadek Hossain Kamal, Upama Kabir, and Tariqul Islam (2019). "Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification." IEEE/ACM Transactions on Computational Biology and Bioinformatics. 1(1).

Transfer Learning for the Detection and Diagnosis of Types of Pneumonia including Pneumonia Induced by COVID-19 from Chest X-ray Images

Yusuf Brima. (2021). "Deep Transfer Learning for the Detection and Diagnosis of Types of Pneumonia including Pneumonia Induced by COVID-19 from Chest X-ray Images." MDPI Special Issue on Machine Learning Applications for COVID-19 and Its Complications: Screening, Diagnosis, Treatment, and Prognosis. 1(1).

A Mathematical Framework for Understanding Recognition Systems

Brima, Yusuf. "A Mathematical Framework for Understanding Recognition Systems" biorxiv preprint biorxiv:2023.06.08.544240 (2023).

Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images

Brima, Yusuf and Marcellin Atemkeng. “Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images.” (2022).

Understanding Self-Supervised Learning of Speech Representation via Invariance and Redundancy Reduction

Brima, Yusuf, et al. "Understanding Self-Supervised Learning of Speech Representation via Invariance and Redundancy Reduction." arXiv preprint arXiv:2309.03619 (2023).

Self-Supervised Learning of Speech Representation via Redundancy Reduction

Brima, Yusuf (2023): Self-Supervised Learning of Speech Representation via Redundancy Reduction. DC@KI2023: Proceedings of Doctoral Consortium at KI 2023. DOI: 10.18420/ki2023-dc-02. Gesellschaft für Informatik e.V.. pp. 11-19. Doctoral Consortium at KI 2023. Berlin. 45195

Talks

Introduction to the Internet

June 12, 2017

Talk at University of Makeni, Department of Computer Science, Sylvanus Koroma Campus Yoni, Makeni

Detecting malaria using a deep convolutional neural network

May 15, 2019

Talk at University of Dhaka, Department of Computer Science and Engineering, Department of Computer Science and Engineering, Dhaka

Big Data for Healthcare Analytics

July 16, 2019

Talk at University of Dhaka, Department of Computer Science and Engineering, Bangabandhu International Conference Center, Dhaka

African Accents International (AAI-SL): Engaging youths, transforming lives

February 09, 2021

Talk at African Institute of Mathematical Sciences (AIMS), Rwanda, AIMS Centre Remera, Kigali

Big Data for Healthcare Analytics

May 05, 2021

Talk at African Institute of Mathematical Sciences (AIMS), Rwanda, AIMS Centre Remera, Kigali

Transfer Learning for the Detection and Classification of traditional pneumonia and pneumonia induced by the COVID-19 from Chest X-ray Images

June 27, 2021

Talk at African Institute of Mathematical Sciences (AIMS), Rwanda, AIMS Centre Remera, Kigali

Supervised Contrastive Deep Learning for Individual Recognition in Chimpanzees in the Wild

July 31, 2022

Talk at Language and Communication colloquium, Institute of Cognitive Science, Osnabrueck University, Germany, Building 50, Room 50/E07, Wachsbleiche 27, Osnabrueck, Germany

Supervised Contrastive Deep Learning for Individual Recognition in Chimpanzees in the Wild

August 08, 2022

Talk at Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Germany, Virtual

Supervised Contrastive Representation Learning for Individual Recognition in the Wild

November 16, 2022

Talk at Language and Communication colloquium, Institute of Cognitive Science, Osnabrueck University, Germany, Building 50, Room 50/E07, Wachsbleiche 27, Osnabrueck, Germany

Teaching

Principles of Programming Languages

Data Mining and Warehousing

Server-side programming with PHP

Relational Database Management Systems

PRINCIPLES OF PROGRAMMING LOGIC AND DESIGN