Ms. Nitasha Naheed is a dedicated Lecturer in the Department of Artificial Intelligence at Shifa Tameer-e-Millat University (STMU), Islamabad, and a Ph.D. scholar in Mathematics at COMSATS University Islamabad. She completed her M.S. in Mathematics from COMSATS University with the highest CGPA in her cohort, specializing in analytical and computational fluid mechanics, electroosmotic-modulated peristaltic transport, variable fluid properties, microchannel flows, and drug delivery systems. Her research integrates mathematical modeling with AI-based computational techniques, including Artificial Neural Networks and data-driven approaches, to enhance predictive accuracy. She has authored 10 research articles in reputable international journals and represented her work internationally at the 12th Heidelberg Laureate Forum (HLF) 2025 in Germany. At STMU, she actively contributes to teaching, curriculum development, student mentorship, and coordinates student sports and co-curricular activities.

EDUCATIONAL QUALIFICATIONS

TEACHING EXPERIENCE

PROFESSIONAL & RESEARCH EXPERIENCE

MANAGEMENT EXPERIENCE

HONORS & AWARDS

• First Position in M.S. Mathematics: Graduated with the highest CGPA in cohort (3.94/4.0), COMSATS University Islamabad.
• Academic Distinction in B.S. Mathematics: Graduated with CGPA 3.87/4.0, International Islamic University Islamabad.
• Heidelberg Laureate Forum (HLF) 2025 Scholarship: Awarded a fully funded scholarship to attend HLF 2025 in Germany; selected for one of 30 international poster flash presentation spots on electroosmotic-modulated peristaltic transport.
• Intercultural Science Art Project Selection: Selected among 28 international participants at the 12th Heidelberg Laureate Forum, Germany, recognizing interdisciplinary contributions integrating science, mathematics, and art.
• Nobel Laureate & Turing Award Poster Session: Presented and discussed research with internationally distinguished scientists during the 12th Heidelberg Laureate Forum.
• Undergraduate Merit-Based Scholarship: Awarded throughout B.S. studies, securing a 4.00/4.00 GPA in 6 out of 8 semesters.
• Prime Minister’s Laptop Scheme: Selected in recognition of consistent academic excellence.

RESEARCH AREAS & INTERESTS

• Analytical & Computational Fluid Mechanics
• Electroosmotic-Modulated Peristaltic Transport
• Artificial Neural Networks (ANNs) & Data-Driven Modeling
• Heat & Mass Transfer in Porous Media
• Mathematical Modeling & Numerical Simulations
• Computational Fluid Dynamics (CFD)
• Non-Newtonian Fluid Mechanics & Nanofluid Dynamics
• Magnetohydrodynamics, Transport Phenomena & Biomedical Flow Modeling

RESEARCH SUPERVISION (MS LEVEL)

1. Forced convection analysis of Williamson-based magnetized hybrid nanofluid flow through a porous medium: Non-similar Modeling.
2. Numerical Study of Non-Similar Bioconvective Flow near a Stretching Surface with Viscous Dissipation and Radiation Effects.
3. Non-similar bioconvective analysis of ternary-hybrid nanofluid over a heated surface.
4. Computational and AI-Based Analysis of Mixed Convective Maxwell Hybrid Nanofluid Flow with Cross-Diffusion Effects in Porous Media.
5. Analysis of Magnetohydrodynamic Boundary Layer Nanofluid Flow under Joule Heating and Viscous Dissipation Effects.
6. Comparative Study of Supervised Machine Learning Models for Anti-Money Laundering Applications.
7. Machine Learning-Based Analysis of Eye Disease Images for Early Diagnosis.

JOURNAL PUBLICATIONS

1. Naheed, N., Noreen, S., & Afridi, M. I. (2025). Investigation on variable properties in thermo-electroosmotic peristaltic flow. Case Studies in Thermal Engineering, 70, 106049.
2. Naheed, N., Zia, F., & Riaz, M. B. (2025). Coupled Magneto-Bioconvective Dynamics of Eyring–Powell Ternary Hybrid Nanofluids through Porous Media: A Neural Network-Based Predictive Approach. International Journal of Thermo-fluids, 101406.
3. Riaz, S., Naheed, N., Farooq, U., Lu, D., & Hussain, M. (2023). Non-similar investigation of magnetized boundary layer flow of nanofluid with the effects of Joule heating, viscous dissipation and heat source/sink. Journal of Magnetism and Magnetic Materials, 574, 170707.
4. Cui, J., Naheed, N., Farooq, U., Hussain, M., & Sheremet, M. (2022). Non-similar analysis of nanofluids flows under the consequences of mixed convection with Lorentz forces over stretching/shrinking surface. Journal of Engineering Thermo-physics, 31(4), 704-719.
5. Zia, F., Iqbal, J., Naheed, N., & Alam, M. M. (2025). AI-powered analysis of thermally magnetized EMHD Casson hybrid nanofluid. Case Studies in Thermal Engineering, 106812.
6. Farooq, U., Fatima, A., Naheed, N., & Hussain, M. (2025). Non-similar analysis of bioconvective stagnation-point flow toward a stretching surface in the presence of buoyancy force, viscous dissipation, and thermal radiation. Numerical Heat Transfer, Part B: Fundamentals, 86(4), 1035-1053.
7. Cui, J., Zia, F., Farooq, U., Hussain, M., & Naheed, N. (2025). Non‐similar bioconvective analysis of ternary‐hybrid nanofluid over a heated surface. ZAMM‐Journal of Applied Mathematics and Mechanics, 105(11), e70263.
8. Farooq, U., Safeer, M., Cui, J., Hussain, M., & Naheed, N. (2025). Forced convection analysis of Williamson-based magnetized hybrid nano fluid flow through a porous medium: non-similar modeling. Numerical Heat Transfer, Part B: Fundamentals, 86(4), 1018-1034.
9. Naheed, N., Zia, F., & Riaz, M. B. (2026). AI-Assisted Modeling of Heat and Mass transfer in Mixed Convective Maxwell Hybrid Nanofluids with Cross-Diffusion Effects in Porous Media. Results in Engineering, 109563.
10. Naheed, N., & Noreen, S. (2026). Non-Linear Electroosmotic Peristaltic Flow of Bingham-Papanastasiou Fluids with Variable Characteristics: A Neural Network Coupled Heat and Mass. AI Thermal Fluids, 100038.