Dr.Tariq Mahmood

Designation(s): Assistant Professor

Education(s): PhD

Department(s): Physics

Email: tariq.mahmood@gcwus.edu.pk

Professional History:

Dr. Tariq Mahmood is PhD in Computational Materials Physics from School of Materials Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China and has over 17 years of teaching, research, and administration experience. Dr. Tariq is presented papers in many national and international conferences. He won three research grants and now he is conducting one research project. Currently, Dr. Tariq Mahmood is working as an Assistant Professor of Physics at Department of Physics, GC Women University Sialkot. Moreover, he established and running the Central Research Laboratory at GC Women University Sialkot. He is also working as a chairperson or member in different committees and statuary bodies at department and University level.

He has around 50+ International publications, Impact Factor= 100+, Citations=600+, hindex=12, i10-index=15 while his major research areas have been Computational Materials Physics, Synthesis of Tungstate based Photo catalytic nanomaterials, Metal Oxide, Graphene Like nano materials. He has also been involved in teaching both at undergraduate and post-graduate

level and has supervised up to 50 BS/M.Sc final year projects as well as 20 MS/M.Phil research thesis and supervising Two PhD students.

Courses I Teach:

  • BS: Quantum Mechanics; Mathematical Methods in Physics, Particle Physics, Introduction of Programming in Physics, General Physics, Mechanics, Introduction to Computer Science.
  • MS: Advanced mathematical Methods in Physics, Computational & Theoretical Physics/DFT • PhD: Optical Properties of Solids, Advanced Condensed Matter Physics
    Research Projects:
  • Synthesis of Tungstate based Nanomaterials using Uniform Strategy for Efficient and LowCost Photocatalytic Degradation of Toxic Materials (2.3 Million) • Lab Scale Membrane Bioreactor for Treatment of Wastewater (0.5 Million) • Enhancing Performance in HPC Parallel Computing Systems under Power Consumption Limitations (0.5 Million)
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