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General Information

Full Name Tanya Akumu
Languages English, Swahili

Education

  • 2024 – 2027 (expected)
    Ph.D., Computer Science
    Universitat de Barcelona, Barcelona, Spain
    • {"Advisor"=>"Karim Lekadir."}
    • {"Proposed thesis"=>"Deep Learning for Obstetric Ultrasound in Low Resource Settings."}
  • 2019 – 2021
    M.Sc., Electrical and Computer Engineering
    Carnegie Mellon University Africa, Kigali, Rwanda
    • {"GPA"=>"3.9/4.0."}
  • 2012 – 2016
    B.Sc., Electrical and Electronic Engineering
    Jomo Kenyatta University of Agriculture & Technology, Nairobi, Kenya
    • Second Class Honors, Upper Division.

Experience

  • Oct 2021 – Apr 2024
    AI Research Engineer
    IBM Research – Africa (Nairobi, Kenya)
    • Implemented a neural network optimization technique (US Patent filed; IJCAI 2024) achieving ~30% memory reduction and 4× faster execution.
    • Built toolkit for analyzing LLM embedding spaces and model alignment; contributed to papers on hallucination detection and internal state analysis.
    • Led healthcare AI research with MADIVA hub on explainable ML models for predicting hypertension and diabetes in African populations.
  • Jun 2020 – Sep 2021
    Software Engineer
    Plentify, South Africa (Remote)
    • Built and maintained client-facing dashboard integrated with ML models via AWS for real-time remote device monitoring.
    • Developed backend to ingest data from new IoT products and integrate into existing company databases.
  • Oct 2016 – Jul 2019
    Embedded Engineer
    M-Kopa, Nairobi, Kenya
    • Designed embedded hardware for IoT solar home systems; contributed to release of two products (M-Kopa 6, M-Kopa 600).
    • Performed IoT data analysis for remote monitoring and predictive maintenance, reducing customer callbacks on faulty devices.

Honors and Awards

  • 2024
    • 3rd place, ACOUSLIC-AI Challenge (MICCAI)
  • 2023
    • Outstanding Technical Award, IBM Research
  • 2022
    • Growth Award, IBM Research
  • 2021
    • Eta Kappa Nu (HKN) – ECE Honor Society, Carnegie Mellon University
  • 2019
    • Mastercard Foundation Scholarship (Full scholarship for graduate studies at CMU-Africa)

Academic Interests

  • Inclusive AI
    • Methods and tools that broaden accessibility and equity.
  • Medical Imaging
    • AI for obstetric ultrasound and low-resource settings.
  • Deep Learning
    • Representation learning and optimization for vision.
  • Trustworthy AI
    • Explainability, bias detection, and robustness.
  • Computer Vision
    • Video analysis and automated measurements.

Other Interests

  • Hobbies: Travelling and Videography.