MD MEHEDI·HASSAN
Ph.D. Researcher · Texas Tech University · Lubbock, TX

Md. Mehedi
Hassan

Ph.D. researcher working on World Models and AI-driven cardiovascular intelligence with the Causal Dynamics Lab — causal reasoning, dynamic system modelling, and predictive AI for cardiovascular health, bridging advanced research with real-time, industry-oriented applications.

2,440+Citations
27h-index
109Publications
8Books Edited
Md. Mehedi Hassan in a Texas Tech University College of Human Sciences lab coat
Texas Tech University · College of Human Sciences
SLICE 01 · About & Research Focus

Md. Mehedi Hassan is a Ph.D. researcher at Texas Tech University, working on World Models and AI-driven cardiovascular intelligence with the Causal Dynamics Lab — exploring causal reasoning, dynamic system modelling, and predictive AI for cardiovascular health.

His work bridges advanced AI research with real-time, industry-oriented applications: modelling cardiovascular dynamics, understanding how disease progresses, and supporting clinical decision-making.

He holds M.Sc. and B.Sc. degrees in Computer Science and Engineering and has authored peer-reviewed scientific publications (2,440+ citations, h-index 27), edited 8 scholarly books with premier publishers, and holds two granted patents. He serves as Associate Editor and Academic Editor across leading Q1/Q2 journals.

His Field-Weighted Citation Impact (SciVal) stands at 2.09 — within Scopus's top 1% of global impact — across 47 papers as first, lead, or corresponding author.

Current RolePh.D. Researcher, Texas Tech University
FocusWorld models, causal reasoning, cardiovascular AI
LocationLubbock, Texas, USA
ORCID0000-0002-9890-0968
MembershipIEEE Professional Member (2020–present)
SLICE 01b · Recognition

World’s Top 2% Scientists

Top 2% Scientists 2026 certificate, verified from Elsevier and Stanford University data

Listed in the 2026 Stanford University & Elsevier ranking

The single-year citation-impact list covering roughly the top two per cent of researchers worldwide, across every scientific field. The listing places the work in Artificial Intelligence & Image Processing.

2026 · single-year data AI & Image Processing Global rank 184,513 8,326 in sub-field
Read the announcement →
SLICE 08b · Opinion & Commentary

Writing for the Public

Op-eds in Bangladeshi national media, written in Bengali.

14 Oct 2026 · Nagorik Online

From vaccines to mosquito control: how far has Bangladesh progressed in dengue research?

What the research on vaccines, insecticide resistance, serotypes and rapid tests can and cannot carry on its own.

17 Aug 2026 · Nagorik Online & Dhaka Today

Is the social media comment box changing the course of politics in Bangladesh?

Why high online visibility should not be mistaken for national public opinion.

All commentary →
SLICE 08 · News & Media

Latest Updates

October 2026 · Conference

IEEE HealthCom 2026, New York

Presented the first Ph.D. work — lightweight 3D liver segmentation — an industry-linked collaboration with Stanford University and Emory University.

August 2026 · Media coverage

DermaViGNet featured by Adelaide University and EurekAlert!

Explainable AI for skin disease diagnosis, reaching 98% accuracy across five conditions including Stevens-Johnson Syndrome.

All news & coverage →
SLICE 10 · Contact

Let's Connect

Open to research collaborations, editorial invitations, speaking engagements, and doctoral/postdoctoral opportunities in biomedical AI and medical imaging.

Based in Lubbock, Texas

Currently a Ph.D. researcher at Texas Tech University. Reach out by email for the fastest response — happy to discuss manuscripts, collaborations, or teaching/speaking invitations.

Send an Email →
Collaboration & Affiliation

Where the Work Happens

Doctoral research, the industry lab the applied work runs with, and the supervisory and industry panel guiding it — the academic and applied halves of one programme of work.

Texas Tech University

Ph.D. research

Doctoral research in the College of Health & Human Sciences, Lubbock, Texas.

Causal Dynamics Lab

Industry research

World models and AI-driven cardiovascular intelligence — causal reasoning and dynamic system modelling for real-time applications.

Stanford University

Industry & supervisory panel

On the supervisory and industry panel for the applied research strand.

Emory University

Industry & supervisory panel

On the same supervisory and industry panel, and research partner to the Causal Dynamics Lab.

Institutional and company marks are the property of their respective owners, shown here to indicate affiliation and collaboration. No endorsement is implied.