Ahmed Fakhry
Data scientist and AI researcher with over four years of experience in leading machine learning and deep learning projects, creating generative and predictive models, and building high-performing teams. Demonstrated proficiency in problem-solving, business process optimization, and developing automated AI agents. Capable of working with stakeholders and cross-functional teams to improve data integrity and model performance in both academic and commercial contexts using data-driven insights.
- M.SC in computing and information systems
Liverpool John Moores University
Feb 2023 ‐ Now - B.SC in electronics and communication engineering
Alexandria University, Faculty of Engineering
Sep 2015 ‐ Aug 2020
Education
Learn more about my:
SKILLS
Below are some of my skills, and I'm always looking to learn more.
Programming Languages
Python, C/C++, Java
Deep Learning Frameworks
Tensorflow, Keras, Pytorch, Scikit-learn, Pandas, NumPy, Matplotlib, SciPy
Databases
SQL database, MongoDB
Others
Linux, Git, OOP Fundamentals, Matlab
Personal Projects
Here you can see some of the projects I've done on my own time.
To see more of my projects...
Papers
Virufy: Global Applicability of Crowdsourced and Clinical Datasets for AI Detection of COVID‐19 from Cough Audio Samples
Nov 2020, Awaiting AE Recommendation from IEEE TAI.
Download
Virufy: A Multi‐Branch Deep Learning Network for Automated Detection of COVID‐19
March 2021, Interspeech Conference 2021
Download
Enhancing Few-Shot Video Anomaly Detection with Key-Frame Selection and Relational Cross Transformers
June 2024, AVSS Conference 2024
Download
Timeline
A short summary of my work experience..
Sep 2023 ‐ Now
AI Research Scientist
Kyungpook National UniversityDaegu, South Korea
- Reduce potential security threats by researching and implementing few-shot and meta-learning techniques to train an anomaly detection system for surveillance aimed at identifying illegal actions.
- Collaborate on multiple surveillance projects with Korean research institutes and private companies to develop innovative technologies and optimize existing surveillance systems.
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Nov 2022 ‐ Sep 2023
Machine Learning Developer
OpenAIUS - Remote
- Ensured high-quality outputs and results by working closely with approx. 10 AI trainers and 5 LLM prompt engineers to improve the model resilience against hallucinations and factual inaccuracies.
- Worked on the Reinforcement Learning Human Feedback models.
Feb 2023 ‐ Now
M.SC in computing and information systems
Liverpool John Moores UniversityLiverpool - Remote
• Topics: Computer Systems, Software Development.
Jan 2022 ‐ Jan 2023
Lead Data Scientist
P.E.R PARTNERSUK ‐ Remote
- Lead a team of four data scientists where I was responsible for developing the company’s flagship product, Digital Eye, alongside other products such as Drug Interaction Checker.
- Digital Eye is based on a deep learning model for digitizing handwritten documents
- Carried out research and built the core understanding of the company performance metrics to qualitatively inform and interpret models
- Was responsible for supporting the growth and professional development of the team.
July 2021 ‐ Jan 2022
Senior Data Scientist
P.E.R PARTNERSUK ‐ Remote
Worked on designing machine learning models for a variety of products in the healthcare sector. For example, SKU demand forecasting for drug‐distributing companies.
Dec 2020 ‐ July 2021
Machine Learning Research Assistant
UNiVERSiTY OF BERGENBergen, Norway ‐ Remote
- Worked on a research project to create a deep learning model to detect gene‐gene interactions from gene expression data.
- Used findr tool to preprocess yeast gene expressions.
- Responsible for designing, training, and evaluating the performance of the deep learning model.
March 2021 ‐ June 2021
Machine Learning Team Lead
ViRUFYSan Francisco, US ‐ Remote
- Was responsible for all phases of deploying machine learning models in production, deciding on performance, fine‐tuning the model on clinical datasets, Testing APIs, etc.
- Involved in making deals with hospitals to gather, clean, and standardize clinical datasets.
- Helped the machine learning team to achieve their potential and meet up the organization standards and follow deadlines and guidelines.
Oct 2020 ‐ Feb 2021
Machine Learning Engineer
ViRUFYSan Francisco, US ‐ Remote
- Pre‐process and extract audio features from coughing audio files from large clinical and crowdsourced datasets.
- Worked on the design and the implementation of machine learning models for automated detection of respiratory diseases from speech and cough audio files.
- Thorough and comparative analysis of SOTA deep learning models for audio classification and automated detection of respiratory diseases.
- Contributed to design the state of the art deep learning model in detecting COVID‐19 from coughing audio files from COUGHVID crowdsourced dataset.the deep learning model.
Sep 2015 ‐ Aug 2020
B.SC in electronics and communication engineering
Faculty of EngineeringAlexandria
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Nov 2022 ‐ Now
Machine Learning Developer
OpenAIUS - Remote
- Working on the tether project.
- Helping reinforcement learning models to fine‐tune and enhance chatgpt performance.
Feb 2023 ‐ Now
M.SC in computing and information systems
Liverpool John Moores UniversityLiverpool - Remote
- Topics: Computer Systems, Software Development
Jan 2022 ‐ Jan 2023
Lead Data Scientist
P.E.R PARTNERSUK ‐ Remote
- Lead a team of four data scientists where I was responsible for developing the company’s flagship product, Digital Eye, alongside other products such as Drug Interaction Checker.
- Digital Eye is based on a deep learning model for digitizing handwritten documents
- Carried out research and built the core understanding of the company performance metrics to qualitatively inform and interpret models
- Was responsible for supporting the growth and professional development of the team.
July 2021 ‐ Jan 2022
Senior Data Scientist
P.E.R PARTNERSUK ‐ Remote
Worked on designing machine learning models for a variety of products in the healthcare sector. For example, SKU demand forecasting for drug‐distributing companies.
Dec 2020 ‐ July 2021
Machine Learning Research Assistant
UNiVERSiTY OF BERGENBergen, Norway ‐ Remote
- Worked on a research project to create a deep learning model to detect gene‐gene interactions from gene expression data.
- Used findr tool to preprocess yeast gene expressions.
- Responsible for designing, training, and evaluating the performance of the deep learning model.
March 2021 ‐ June 2021
Machine Learning Team Lead
ViRUFYSan Francisco, US ‐ Remote
- Was responsible for all phases of deploying machine learning models in production, deciding on performance, fine‐tuning the model on clinical datasets, Testing APIs, etc.
- Involved in making deals with hospitals to gather, clean, and standardize clinical datasets.
- Helped the machine learning team to achieve their potential and meet up the organization standards and follow deadlines and guidelines.
Oct 2020 ‐ Feb 2021
Machine Learning Engineer
ViRUFYSan Francisco, US ‐ Remote
- Pre‐process and extract audio features from coughing audio files from large clinical and crowdsourced datasets.
- Worked on the design and the implementation of machine learning models for automated detection of respiratory diseases from speech and cough audio files.
- Thorough and comparative analysis of SOTA deep learning models for audio classification and automated detection of respiratory diseases.
- Contributed to design the state of the art deep learning model in detecting COVID‐19 from coughing audio files from COUGHVID crowdsourced dataset.the deep learning model.
Sep 2015 ‐ Aug 2020
B.SC in electronics and communication engineering
Faculty of EngineeringAlexandria
- Cumulative Grade: 72.8% (Good)