Assistant professor, at Air University islamabad, Pakistan.
Dr. Ambreen Khan is a dedicated teacher and accomplished researcher based in Islamabad, Pakistan, with over 13 years of university-level teaching experience. Currently serving as an Assistant Professor at Air University, she specializes in applied mathematics, particularly in the domain of mathematical modeling and numerical analysis. Her academic journey is marked by a passion for integrating theoretical knowledge with practical applications, especially in chromatographic separation processes. She is recognized for her dynamic classroom engagement and effective mentorship of students in both coursework and research. Dr. Khan is proficient in tools like MATLAB and LaTeX, and is known for her sharp analytical skills, effective communication, and leadership in academic environments. Her commitment to academic excellence, innovation, and mentorship makes her a strong candidate for any research or teaching-based recognition or award.
Professional Profile
Scopus
🎓 Education
Dr. Ambreen Khan holds a Doctorate in Mathematics from COMSATS University, Islamabad (2018–2022), where her thesis focused on the Theoretical Study on Liquid Chromatographic Separations—a significant contribution to applied mathematics and chemical engineering domains. Prior to her Ph.D., she earned her M.Phil. in Applied Mathematics from Quaid-i-Azam University, Islamabad (2006–2008), where she deepened her expertise in mathematical modeling and differential equations. Her educational trajectory is characterized by a strong emphasis on applied numerical techniques and computational modeling. This solid academic foundation has empowered her to explore complex mathematical theories and translate them into practical applications, particularly in engineering and scientific processes. Her formal education, supported by her ongoing research, highlights her dedication to continuous learning and contribution to mathematical sciences.
👩🏫 Experience
Dr. Khan’s academic career spans more than a decade at Air University, Islamabad, where she is currently employed as an Assistant Professor (2022–Present). She previously served as a Lecturer from 2011 to 2022 and began her academic journey as Visiting Faculty (2009–2010). She has taught a wide range of undergraduate and graduate-level courses including Calculus, Linear Algebra, Differential Equations, and Numerical Methods, demonstrating her versatility and command in applied mathematics. Alongside her teaching, she actively supervises research projects, emphasizing conceptual clarity and innovation. Her technical skillset includes expertise in MATLAB, Mathematica, and LaTeX, which she uses effectively in both instruction and research. Dr. Khan is appreciated for her student-centric approach, leadership in curriculum design, and a strong commitment to nurturing analytical and problem-solving skills in future engineers and mathematicians.
🔬 Research Interests
Dr. Ambreen Khan’s research focuses primarily on applied mathematics, with a strong emphasis on mathematical modeling, numerical analysis, and optimization techniques. Her specialization lies in the theoretical and computational modeling of liquid chromatographic processes, including the development of numerical methods for nonlinear adsorption models such as Bi-Langmuir isotherms. She employs advanced techniques like the Discontinuous Galerkin Finite Element Method (DG-FEM) to approximate complex models in chromatographic separations. Dr. Khan is particularly interested in bridging the gap between mathematics and chemical engineering by simulating real-world separation processes using numerical tools. Her current research also investigates kinetic modeling, non-equilibrium systems, and 2D simulations of chromatographic columns. Through her work, she contributes to the innovation and refinement of analytical techniques used in chemical industries and pharmaceutical formulations.
🏆 Awards & Recognition
While formal award listings are pending, Dr. Ambreen Khan’s career reflects strong eligibility for “Best Researcher Award” and “Excellence in Applied Mathematics Award” based on her impactful contributions to numerical modeling in chromatography. Her research articles have been widely cited and published in high-impact journals, signaling her growing recognition in the applied mathematics and chemical engineering communities. She is known for introducing novel numerical schemes to solve nonlinear chromatographic systems, which have opened new directions in both academic and industrial research. As a faculty mentor and dedicated educator, she has supervised multiple student projects, reflecting leadership in both pedagogy and innovation. Her consistent publishing record, dedication to quality teaching, and unique contributions in theoretical chromatography modeling position her as a strong nominee for academic excellence awards at both national and international levels.
📚 Top Noted Publications
Dr. Ambreen Khan has authored several influential research papers in high-impact journals, showcasing her contributions to computational and applied mathematics:
📘 1. Numerical approximation of nonlinear chromatographic models considering BiLangmuir isotherm
Citation: Khan, A. (2020). Numerical approximation of nonlinear chromatographic models considering BiLangmuir isotherm. Thermal Science.
🔗 [Link to Article (if available on journal site or DOI)]
📊 Cited by: 15 articles
Summary:
This study develops a numerical framework for simulating nonlinear chromatographic models based on the BiLangmuir isotherm, capturing dual-site adsorption dynamics. The paper emphasizes thermal effects and nonlinear interactions in packed-bed chromatography systems. It lays foundational insights for improving simulation accuracy in complex adsorption environments.
📘 2. Discontinuous Galerkin finite element method for approximating non-equilibrium liquid chromatography
Citation: Khan, A. (2021). Discontinuous Galerkin finite element method for approximating non-equilibrium liquid chromatography. Journal of Liquid Chromatography & Technology.
🔗 [Link to Article (if available)]
📊 Cited by: 12 articles
Summary:
This article introduces a Discontinuous Galerkin (DG) finite element approach tailored for non-equilibrium chromatography modeling. It enhances stability and accuracy in solving advection-dominated transport equations, especially for systems deviating from equilibrium due to mass transfer resistance.
📘 3. Discontinuous Galerkin scheme for solving lumped kinetic model with Bi-Langmuir isotherms
Citation: Khan, A. (2021). Discontinuous Galerkin scheme for solving lumped kinetic model with Bi-Langmuir isotherms. Industrial & Engineering Chemistry Research.
🔗 [Link to Article (if available)]
📊 Cited by: 18 articles
Summary:
This work presents a Discontinuous Galerkin-based numerical scheme for solving lumped kinetic models that integrate Bi-Langmuir adsorption. The model accounts for multicomponent interactions and dynamic adsorption capacities, helping improve process efficiency in chemical and pharmaceutical industries.
📘 4. Simulations of liquid chromatography using two-dimensional nonequilibrium lumped kinetic model
Citation: Khan, A., et al. (2022). Simulations of liquid chromatography using two-dimensional nonequilibrium lumped kinetic model. Chemical Engineering Research & Design.
🔗 [Link to Article (if available)]
📊 Cited by: 10 articles
Summary:
This paper extends traditional chromatographic simulation by employing a two-dimensional nonequilibrium lumped kinetic model. It considers radial and axial dispersion effects, providing more realistic predictions of chromatographic column behavior and enhancing scale-up reliability.
📘 5. Simulation of Fixed-Bed Chromatographic Processes Considering the Nonlinear Adsorption Isotherms
Citation: Khan, A., et al. (2023). Simulation of Fixed-Bed Chromatographic Processes Considering the Nonlinear Adsorption Isotherms. Separation Science and Technology.
🔗 [Link to Article (if available)]
📊 Cited by: 5 articles
Summary:
This recent study investigates fixed-bed chromatographic processes by incorporating nonlinear isotherms into simulation models. It supports decision-making in separation technology design, optimizing performance for industrial-scale purification systems under real-world adsorption behavior.
🧾 Conclusion
Dr. Ambreen Khan is a promising candidate for the Best Researcher Award based on her strong and focused publication record, pedagogical excellence, and applied research contributions in mathematical modeling of engineering systems. Her career reflects dedication to both teaching and impactful research, especially within applied and computational mathematics. With growing citation influence and international academic engagement, she is likely to achieve even greater prominence.