I'm a Computational linguist and Data Scientist with machine learning, AI development, and big data consulting. With advanced studies from Stanford and WorldQuant University, I specialize in Biomedical Data science, Quantum NLP, and Fintech. Proficient in Python, SQL, statistical analysis, and computational linguistics, I design scalable models and data-driven solutions to deliver actionable insights and drive innovation across diverse challenges. Multilingual and globally focused, I excel at merging technical expertise with impactful results.

Bassam Mejlaoui Profile Photo

Academic Background

Between 2016 and 2021, I followed a polymathic path—studying Computer Science, Data Science, Mathematics, and Bioinformatics through the Open Source Society University while grappling with impostor syndrome. In 2019, I formally pursued a Bachelor's degree in Linguistics at Ibn Tofail University, where I conducted thesis research on the role of Computational Linguistics in developing Artificial Intelligence—before the AI wave truly hit. In 2024, I began a Master's in Financial Engineering with a minor in Machine Learning at WorldQuant University (not yet graduated), completing labs in Applied Artificial Intelligence and Applied Data Science. I'm also enrolled in a fully online, self-paced Master's in Data Science from the University of Colorado Boulder. Beyond academia, I completed leadership training with Aspire Institute and Harvard Business School, earned certification in AI in Healthcare from Stanford School of Medicine, and joined Stanford's Code in Place under Professors Mehran Sahami and Chris Piech.

Research

I'm broadly interested in leveraging AI and computational techniques for decision-making and human-machine interaction. My research spans Neuroinformatics, Brain-Machine Interfaces, Digital Twin Technology, Quantum NLP, Ethical AI, Algorithmic Governance, Biomedical Data Science, Applied AI, Computational Linguistics, Corpus Linguistics, and Cryptologic Language Analytics. Papers (and preprints) are ordered by recency. I completed my Bachelor's thesis on the role of Computational Linguistics in the development of Artificial Intelligence at Ibn Tofail University.

Title / Role

Independent AI Researcher / Scholar
Self-directed learning while building and scaling my AI startup

Summary / Core Expertise

Conducting self-directed research in AI, Cognitive Science, and HCI, applying findings directly to startup solutions.
Bridging business, law, design, and cognitive science to develop innovative, scalable AI products.
Contributing to open-source AI projects with Meta, DeepMind, Microsoft, Google, and Hugging Face.

Developing expertise in:
  • Human-Computer Interaction (HCI)
  • Machine Learning & Predictive Analytics
  • Cognitive Modeling & Neuroscience-inspired AI
  • AI System Design & Scalable Infrastructure

Researching and prototyping AI applications in NLP, recommendation systems, and intelligent user interfaces.

Audited Advanced Coursework (Self-Directed from Top Universities)

I'm auditing courses, classes, and seminars across top universities in majors and degrees relevant to my research and startup vision. Key areas include:

  1. BSc in Cognitive Science – MIT
  2. MBA – Stanford GSB
  3. MSt in Entrepreneurship – Cambridge Judge
  4. MPP in Business & Technology Policy – Harvard Kennedy School
  5. MDes – Stanford d.school
  6. MSc in Statistics – Oxford
  7. MSc in Operations Research – Stanford
  8. JD – Stanford Law
  9. PhD in Computer Science (AI/HCI) – Stanford
  10. PhD in Neuroscience – Harvard
  11. PhD in Economics (Behavioral Economics) – MIT
  12. PhD in Philosophy (Ethics & Epistemology of AI) – Cambridge
  13. PhD in Learning Sciences – Stanford GSE
  14. ScD in Applied Data Science / Computational Science – Harvard

Approach

Learning like a founder-researcher, not just a student: acquiring frameworks from the world’s top universities and immediately applying them to product building, research, and startup execution.
Pursuing knowledge for practical impact and innovation, not for traditional credentialing.
Combining entrepreneurship + AI research to bridge the gap between theory, product, and real-world adoption.