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Curriculum vitae

Research Profile

I am passionate about building trustworthy machine learning systems for healthcare: models that learn robust (multimodal) representations, provide faithful and clinically grounded explanations of their decisions, and generalize reliably across the settings in which they are deployed, including low-resource health systems, ultimately contributing to improved patient outcomes.

Research Interests

My research interests include:: medical image analysis · multimodal clinical AI · trustworthy and explainable AI · robustness and generalisation · representation learning · AI for global health.

Technical Skills

  • ML/DL: PyTorch, TensorFlow/Keras, scikit-learn, transformers, multimodal learning
  • Programming: Python, R, C/C++
  • Systems: Unix, Linux, Windows, High Performance Computing with SLURM (HPC), Grid Computing with Oracle Sun Grid Engine, Docker, GCP, GPU Computing
  • Data and Scientific Computing: SQL, NumPy, Pandas, Matplotlib, Seaborn
  • Neuroimaging Data and Tools: BIDS, FSL, FreeSurfer
  • Medical Imaging: OpenCV, SimpleITK, NiBabel, Pydicom, ANTsPy, scikit-image
  • Explainable, Fair, and Trustworthy AI: SHAP, Captum, Fairlearn, AIF360, LIME, TorchCAM, iNNvestigate

Languages

English (Bilingual Proficiency); German (B1); French (Elementary); Krio (Native); Kono (Native)

Education

Ph.D. in Cognitive Science

Universität Osnabrück, Germany (Nov 2021 – Jun 2025)

M.Sc. in Mathematical Sciences

African Institute for Mathematical Sciences (AIMS), Rwanda (Sept 2020 – Jul 2021)

  • Thesis: Deep Transfer Learning for Chest X-ray Image Analysis
  • Award: AIMS / Mastercard Foundation Scholarship

M.Sc. in Computer Science and Engineering

University of Dhaka, Bangladesh (Jul 2018 – Aug 2020)

  • Thesis: Deep Learning for Brain Tumor Detection using MRI Data in collaboration with clinicians
  • Award: Queen Elizabeth Commonwealth Scholarship

B.Sc. in Computer Science

University of Makeni, Sierra Leone

(Sept 2012 – Feb 2017)

  • Undergraduate Merit Scholarship
  • Award: Undergraduate Merit Scholarship

Professional Experience

Biomedical AI Research Fellow

Research Collaboration with Rhodes University and Global Academic Partners
Nov 2025 – Present

  • Conduct research in multimodal representation learning for biomedical data, focusing on early disease diagnosis and prognosis, with emphasis on robustness, explainability, fairness, and generalization.
  • Co-supervise students on projects in medical imaging and clinical AI, including transformer-based 3D medical image analysis and explainable/fair AI.
  • Participate in conferences, workshops, and seminars; publish research output in top-tier conferences and journals including MICCAI, npj Digital Medical, IEEE, etc.

Research Associate (PhD Researcher)

RTG Computational Cognition, Universität Osnabrück
Nov 2021 – Dec 2024

  • Conducted research in deep representation learning for artificial intelligence, with a focus on self-supervised learning methods including contrastive, generative, and joint-embedding approaches.
  • Developed joint-embedding, contrastive, and generative models for disentangled representation learning, including methods such as Barlow Twins, variational autoencoders (VAEs), and supervised contrastive learning.
  • Improved data processing efficiency by at least 20\% and increased model performance by at least 25\% across target machine learning tasks.
  • Curated and maintained the SynSpeech dataset and managed associated open-source research codebases and accessibility.
  • Presented research at international conferences and doctoral consortia, including NeurIPS (2023), German Conference on Artificial Intelligence (KI) Doctoral Consortium (2023), and ICLR (2024).
  • Supervised and mentored Master’s students in machine learning and deep learning research projects.

Research and Teaching Assistant

University of Makeni, Makeni, Sierra Leone
Feb 2017 – Jul 2018 (part-time)

  • Taught four undergraduate Computer Science courses with approximately 40 students per course.
  • Designed and developed course materials, assignments, and examination assessments.
  • Mentored and supervised student thesis.

Lecturer

Limkokwing University of Creative Technology, Freetown, Sierra Leone Jan 2018 – Jul 2018 (part-time)

  • Taught Principles of Programming Logic and Design to more than 120 undergraduate students per semester.
  • Delivered lectures, prepared teaching materials, and supported student assessment and academic evaluation.
  • Facilitated practical programming exercises and supported students in foundational software development concepts.

Selected Publications

See the publications page for the full, up-to-date list.

Competitive Scholarships and Awards

  • Lambda AI Research Grant (2026)
  • Google Cloud Academic Research Grant (2026)
  • CIFAR Deep Learning and Reinforcement Learning (DLRL) Summer School Inclusive AI Scholarship, Canada, 2024
  • Deep Learning Indaba Scholarship, 2023
  • Cambridge Ellis Machine Learning Summer School Fully-funded Scholarship, 2022

Further Training and Certifications

  • DeepLearning.AI AI for Medicine Specialization (Coursera, online, 2026) — (3 months)
    Focus: diagnostic, prognostic, and treatment-effect AI models in healthcare.
    Certificate Link

  • Stanford University AI for Healthcare Specialization (Coursera, online, 2025) — (8 weeks)
    Focus: clinical data, healthcare systems, and evaluation of AI in medicine.
    Certificate Link

  • MUST Deep Learning Bootcamp (North-West University, South Africa, 2025) — (2 weeks intensive)
    Focus: CNNs, optimization, gradient descent, regularization, supervised learning.

  • IBM AI Engineering Professional Certificate (Coursera, online, 2023) — (5 months)
    Focus: deep learning, TensorFlow, Keras, neural networks, hyperparameter tuning.
    Certificate Link

  • IBM Data Science Professional Certificate (Coursera, online, 2023) — (6 months)
    Focus: Python, SQL, machine learning, data visualization, cloud computing.
    Certificate Link

  • Python Programming and Data Structures (University of Michigan, Coursera, online, 2023) — (8 weeks)
    Focus: Python, algorithms, recursion, object-oriented programming.
    Certificate Link

  • Mediterranean Machine Learning School (Università Milano Bicocca, Italy, 2022) — (5-day intensive)
    Focus: advanced deep learning lectures and hands-on sessions.

  • Deep Learning Program (Neuromatch Academy, online, 2022) — (3-week intensive program)
    Focus: end-to-end deep learning from theory to implementation. Certificate Link

  • Machine Learning Summer School (Bandung, Indonesia, 2020) — (2-week intensive)
    Focus: CNNs, VAEs, NLP, TensorFlow, transfer learning.

  • Machine Learning Summer School (University of Oxford, UK, 2020) — (2-week intensive)
    Focus: Bayesian ML, computer vision, NLP, reinforcement learning, causal inference.

  • Mathematics for Machine Learning (Imperial College London, Coursera, online, 2020) — (3 months)
    Focus: linear algebra, multivariate calculus, optimization, PCA.
    Certificate Link

Data Access, Governance, and Compliance

  • Approved access to Demographic and Health Surveys (DHS) data for research on trustworthy disease diagnosis.
  • Credentialed access and training for controlled biomedical datasets and platforms, including UK Biobank/MRC, PhysioNet, LONI IDA, and the German FDPG framework.
  • Training in research ethics, data privacy, and responsible data use (CITI Program); experienced with IRB-compliant workflows and secure handling of sensitive health data.

Talks

See the talks page.

Teaching

See the teaching page.

Academic Service

  • Scholarship Selection Committee Member: Masters in Mathematical Sciences in Mathematical Epidemiology (MathEpi), Africa Health Collaborative (AHC) African Institute for Mathematical Sciences (AIMS), 2026.

  • Award Committee Member: Deep Learning Indaba Kambule Doctoral Award Committee, 2025.

  • Conference and seminar organization: Co-organized the “Bridging Biological and Artificial Neural Networks” workshop (Osnabrück University, 2022) and the Deep Representation Learning Seminar (Winter 2023/24).

  • Peer review since 2023: Scientific Reports; BMC Medical Informatics and Decision Making; Healthcare Technology Letters; npj journals; ICLR; ICML MusIML Workshop; Deep Learning Indaba.

  • Memberships: MICCAI Society (2023–present); Black in AI (2022–present); Deep Learning Indaba (2022–present); IEEE (2019–present); AIMS Alumni Network (2021–present).

Professional Memberships