Hi, I'm

Kobby Panford-Quainoo

Research Engineer, Machine Learning|

Passionate about machine learning, deep learning, and AI for social good. Building scalable ML systems and contributing to open-source projects.

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About Me

Get to know more about who I am and what I do

A Little About Myself

I'm a Research Engineer in Machine Learning at InstaDeep Ltd, where I work on optimizing and scaling ML platforms, developing data annotation tools, and contributing to AI for Social Good initiatives. My work includes leading open-sourcing efforts and scaling Google's SKAI to GCP.

With a Master's in Mathematical Sciences (Machine Intelligence) from AMMI and experience teaching foundational ML courses, I'm passionate about both advancing the field and sharing knowledge. I've worked on projects ranging from graph neural networks for trade modeling to generative models for drug discovery.

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Passion

Driven by a passion for creating exceptional digital experiences and solving complex problems.

Experience

Years of experience building scalable applications and working with cutting-edge technologies.

Interests

Love for design, photography, and exploring new technologies in my free time.

Skills & Technologies

Technologies and tools I work with

Programming Languages

Python
C++

Deep Learning Libraries

PyTorch
TensorFlow
JAX

Cloud Computing & Tools

Google Cloud Platform
AWS
LaTeX
Unix
Windows
Arduino IDE

Featured Projects

A collection of projects I've worked on

B

Bilateral Trade Modelling with Graph Neural Networks

Created a new framework that uses graph neural networks to predict the income level of countries and potential trade partners up to 68% and 98% accuracy respectively. Master's project at AMMI.

PyTorch
Graph Neural Networks
Python
D

Drug Discovery with Generative Models

Built and trained Adversarial and Variational Autoencoders for both representation learning and generation of discrete-structured molecular data, particularly the SMILES dataset for drug repurposing.

PyTorch
VAE
GAN
Python
C

Calibration of Ensemble Models

Investigated how calibrated deep ensemble models are compared to non-ensemble deep neural network models.

PyTorch
TensorFlow
Python
S

SKAI Data Annotation Tool

Developed and maintain an easy to deploy data annotation tool for SKAI at InstaDeep, optimizing workflows for machine learning data preparation.

Python
GCP
MLOps
D

Desert Locust Early Warning System

Contributed to InstaDeep's AI for Social Good initiative, developing and enhancing an early warning system for desert locusts using machine learning for agriculture sustainability.

Machine Learning
AI for Social Good
Python
C

Causal Graphs from Medical Literature

Built causal graphs from Medical literature (e.g., PubMed) and Electronic Health Records, pruning causal edges with a language model that understands causal relationships from medical text.

NLP
Causal Inference
Python

Experience & Education

My professional journey and educational background

Research Engineer, ML

InstaDeep Ltd

Jan 2023 - Present
Remote
  • Working with a team to optimize and scale Deepchain platform with modern tools and technologies
  • Developed and maintain an easy to deploy data annotation tool for SKAI
  • Led the open-sourcing and scaling efforts of Google's SKAI to GCP, optimizing performance by leveraging GPUs and TPUs
  • Contributed to AI for Social Good initiatives, including InstaDeep's early warning system for desert locusts

Tutor

African Masters of Machine Intelligence (AMMI)

Feb 2020 - Sep 2023
Remote
  • Taught foundational courses: Mathematics, Programming, Foundations of Machine Learning and Deep Learning
  • Assisted professors teach advanced courses: Kernel Methods, Computer Vision, Reinforcement Learning

Teaching Assistant

Neuromatch Academy

July 2022
Remote
  • Tutored students in the annual virtual Deep Learning School
  • Assisted groups of participating students complete their final projects

Visiting Student & Research Intern

University of Toronto & Vector Institute

Sep 2019 - Jan 2020
Toronto, Canada
  • Advised by Marzyeh Ghassemi (ML for Healthcare group)
  • Built causal graphs from Medical literature and Electronic Health Records
  • Pruned causal edges with a language model that understands causal relationships from medical text

Teaching and Research Assistant

KNUST

Sep 2017 - Aug 2018
Kumasi, Ghana
  • Assisted professor teach Programming with C++ (I&II) and Introductory Electronics

MSc. Mathematical Sciences (Machine Intelligence)

African Institute for Mathematical Sciences - AMMI

Sep 2018 - Sep 2019
Rwanda
  • Google-Facebook Scholarship (full) - acceptance rate 6%
  • Most (Technical) Supportive student - Certificate of Excellence

BSc. Physics (Major: Electronics)

Kwame Nkrumah University of Science and Technology (KNUST)

Aug 2013 - Jul 2017
Kumasi, Ghana
  • DAAD Student Travel Award and Research Grant (Germany)

Get In Touch

Have a project in mind or want to collaborate? Let's talk!