About me
Data scientist and machine learning researcher, with previous experience as a data engineerig intern and data analyst. I have worked extensively with health, financial, and energy data. extracting business insight and publishing high quality research papers at conferences and journals like CVPR, IEEE Big Data and Journal of Urban Health, with my most recent works under review for NeurIPS, ICCV, and AAAI.
I’m experinced with programming languages and tools like Python, SQL, Google Cloud, AWS, Apache Spark, HDFS, Snowflake, ETL development, and Data Modeling.
Recent News
🟥 Jun. 2025: I will present our paper on efficent image encoding for QNNs at CVPR 2025.
Dec. 2024: I presented our paper on LLMs Empowering Phishing Attacks at IEEE Big Data.
Nov. 2024: Fordham News published an article covering my interview on our lead research.
Oct. 2024: Our paper on optimizing lead testing for children in NYC was published by The Journal of Urban Health.
Sep. 2024: I presented our paper on Imbalanced Datasets at the 28th KES conference.
April. 2024: I won the third place award at the Fordham Three Minute Thesis Competition for our research paper on Lead Testing for Childeren in New York City. [Competition Results]
May. 2023: I was featured by the U.S. Embassy Mauritania Facebook page after finishing my master’s degree as part of the Fulbright Program [Post]
Publications
Machine Learning for Public Health
M. Afane and J. Chen, “Analyzing and Optimizing the Distribution of Blood Lead Level Testing for Children in New York City”, Journal of Urban Health 2024, [Paper].
M. Afane, A. Donaire, and J. Chen, “Uncovering Correlations Between Health Coverage and Lead Vulnerability in American Cities”, Under Review. [Paper]
Quantum Machine Learning
M. Afane, G. Ebbrecht, Y. Wang, J. Chen, and J. Farooq. “ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networkss”, CVPR 2025. [Paper]
M. Afane, K. Laufer, W. Wei, Y. Mao, J. Farooq, Y. Wang, and J. Chen. “Benchmarking Large Language Models Quantum Computing Knowledge”, Submitted to NeurIPS 2025. [Paper].
M. Afane, Q. Long, H. Shen, Y. Mao, and J. Chen. “Quantum Architecture Optimization for Adversarial Robustness.”, Submitted to ICCV 2025. [Paper].
Modern Challenges in AI and Data Science
M. Afane, W. Wei, Y. Mao, and J. Chen, “Next-Generation Phishing: How LLM Agents Empower Cyber Attackers”, IEEE Big Data 2024. [Paper].
M. Afane and Y. Zhao, “Selecting Classifiers and Resampling Techniques for Imbalanced Datasets: A New Perspective”, 28th International KES 2024.[Paper].
M. Afane, J. Chen, et al. Healing or Hacking? The Risk of Backdoor Attacks in Medical AI. In Progress.