Vahideh Vakil

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PhD Candidate
WINLAB (Wireless Information Network Laboratory)
Department of Electrical and Computer Engineering
Rutgers, The State University of New Jersey

671 Route 1 South
North Brunswick, N.J. 08902-3390
Phone: +1 (848) 932-0942
Fax: +1 (732) 932-6882
Email: vavakil [@] winlab [DOT] rutgers [DOT] edu

Short Bio

Vahideh Vakil received her first PhD degree from Amirkabir University of Technology, Tehran Polytechnic, in Iran. She is currently working toward the PhD degree at the Department of Electrical and Computer Engineering, Rutgers University, working with Professor Wade Trappe in WINLAB since 2018. Her current research interests include the area of mathematical modeling and networking techniques in systems pharmacology and systems biology, with a goal of developing quantitative techniques to improve medical treatments for human diseases. Prior to joining Rutgers, her main research focus was in the area of technologies in mobile communications and networks. She worked as a faculty member of Electrical Engineering till 2013.

General Research Interests

Current Research Projects

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Optimal Drug Combination

Treatments consisting of mixtures of pharmacological agents have been shown to have superior effects to treatments involving single compounds. Given the vast amount of possible combinations involving multiple drugs and the restrictions in time and resources required to test all such combinations in vitro, mathematical methods are essential to model the interactive behavior of the drug mixture and the target, ultimately allowing one to better predict the outcome of the combination. The determination of drug dosages is important for obtaining optimum therapeutic results and for clinical tests in the drug development process. Dosage algorithms aim to optimize the onset, intensity and duration of the therapeutic effects of the drugs by determining the appropriate dosages, frequency, and route of administration, while also minimizing any adverse effects.

Check out our paper published in Pharmaceutics [Link] [PDF] for more on mathematical modeling of drug combinations.

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Combating Drug Resistance in Cancer Treatment

In the case of cancer therapy, drug resistance is a frequent problem that, when it arises, often leads to refractory tumor progression and can lead to failure in therapeutic efforts. Evolutionary modeling has been shown to help in identifying the cell of origin, and in predicting the likely trends in tumor growth and drug resistance. Developing treatment strategies that lead to successful therapies requires a correct understanding of the evolutionary dynamics. This research presents a method for determining a dosage strategy to combat drug resistance in tumor progression based on a dynamic model for the clonal evolution of cancerous cells.

For more information about designing optimum treatment strategies to combat drug resistance in cancer, check our IEEE/ACM TCBB paper [Link].
More on how to postpone drug resistance, in our FEBS Open Bio paper [Link] [PDF].

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Dynamics of Viral Infection Diseases

The emergence of COVID-19 pandemic as a new disease with many unanswered questions about its underlying mechanisms in different levels and effective therapeutic methods, is the core subject of this research. In this project, a mathematical framework is proposed for exploring the dynamics of corona virus transmission in the population level and investigating the epidemiological aspects of vaccination, as well as exploring the dynamics of viral diseases in cellular level through modeling the immune system’s response to the viral infection caused by the corona virus.

Check out our IJERPH paper for more information on COVID-19 Transmission Dynamics [Link] [PDF].

Selected Publications

  1. V. Vakil and W. Trappe, “Projecting the Pandemic Trajectory through Modeling the Transmission Dynamics of COVID-19,” International Journal of Environmental Research and Public Health, Apr. 2022. [Link] [PDF]

  2. V. Vakil and W. Trappe, “Dosage Strategies for Delaying Resistance Emergence in Heterogeneous Tumors,” FEBS Open Bio, Feb. 2021. [Link] [PDF]

  3. V. Vakil and W. Trappe, “Drug-resistant Cancer Treatment Strategies Based on the Dynamics of Clonal Evolution and PKPD Modeling of Drug Combinations,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, Dec. 2020. [Link]

  4. V. Vakil and W. Trappe, “Drug Combinations: Mathematical Modeling and Networking Methods,” Pharmaceutics, vol. 11, no. 5, pp. 208, May 2019. [Link] [PDF]

Full list of publications.

Poster Presentations



  1. Instructor: Probability and Random Processes, Rutgers University, Summer 2019 and Summer 2020.

  2. Teaching Assistant: Linear Systems and Signals, Rutgers University, Fall 2019 and Fall 2020.

  3. Teaching Assistant: Professionalism and Ethics, Rutgers University, Spring 2020.

  4. Teaching Assistant: Probability and Random Processes, Rutgers University, Spring 2019 and Spring 2021.

  5. Assistant Professor: Communications I, Communications II, Signals and Systems Processing, Computer Networks I, Computer Networks II, Digital Communications, Data Network, System Processing, Electrical Circuit, Circuit I, Circuit II, Principles and Circuits of Communications, Communication Technology, Applied Mathematics, Electricity and Magnetism Physics, Bahar Institute of Higher Education, Mashhad, Iran, 2008–2013.