Bio

Mahnaz is a PhD Candidate in Stanford EE working in Prof. Eric Pop's lab on insulator-metal-transition oxides for applications in memory selectors and brain-like computing. She also holds a Masters in EE (2021) from Stanford and completed her Bachelors in EEE (2017) from Bangladesh University of Engineering and Technology (BUET), where she worked as a Lecturer prior to joining Stanford in 2019. She is the recipient of Thomas and Sarah Kailath Stanford Graduate Fellowship in Science and Technology and enjoys dancing, hiking, and taking care of her plants in her free time.

Honors & Awards

  • Thomas and Sarah Kailath Fellow, Stanford Graduate Fellowships Program in Science and Engineering (2019 - 2022)

Professional Affiliations and Activities

  • Student Member, IEEE (2015 - 2022)
  • Student Member, IEEE Women in Engineering (2016 - Present)
  • Student Member, IEEE Electron Device Society (2016 - Present)

Education & Certifications

  • M.Sc., Stanford University, Electrical Engineering (2021)
  • M.Sc., Bangladesh University of Engineering and Technology, Electrical and Electronic Engineering, Electrical and Electronics Engineering (2019)
  • B.Sc., Bangladesh University of Engineering and Technology, Electrical and Electronic Engineering, Electrical and Electronics Engineering (2017)

Contact

  • Academic
    mzislam@stanford.edu
    University - Student Department: Electrical Engineering Position: Graduate

Additional Info

Links

Current Research and Scholarly Interests

My current research involves working on insulator-metal-transition oxides such as NbO2 and LaCoO3 to understand their switching physics in electrical devices compared to thermal switching, and use various electrical and materials characterization as well as novel in-situ spectroscopy techniques in my work. I am interested in their applications in memory selectors, ESD protection clamps, and brain-inspired computing.

As part of my PhD work, I have collaborated with both academia (Purdue, Rutgers, USC, Sandia NL, Lawrence Berkeley NL) as well as the industry (NGC, On Semi) outside of Stanford.

I have also completed a NAND pathfinding internship at Micron Technology where I used my knowledge of semiconductor device physics and process fabrication skills to design experiments and study the challenges of tier pitch scaling in 3D NAND. As part of the Process Integration team, I have collaborated closely with other Process teams as well as Device and TEM imaging labs.

All Publications

  • Intrinsic and Extrinsic Factors Influencing the Dynamics of VO2 Mott Oscillators PHYSICAL REVIEW APPLIED Bohaichuk, S. M., Kumar, S., Islam, M., Rojo, M., Williams, R., Pitner, G., Jeong, J., Samant, M. G., Parkin, S. P., Pop, E. 2023; 19 (4)

    View details for DOI 10.1103/PhysRevApplied.19.044028

    View details for Web of Science ID 000970240900002

  • Electro-thermal Characterization of Dynamical VO2 Memristors via Local Activity Modeling. Advanced materials (Deerfield Beach, Fla.) Brown, T. D., Bohaichuk, S. M., Islam, M., Kumar, S., Pop, E., Williams, R. S. 2022: e2205451

    Abstract

    Translating the surging interest in neuromorphic electronic components, such as those based on nonlinearities near Mott transitions, into large-scale commercial deployment faces steep challenges in the current lack of means to identify and design key material parameters. These issues are exemplified by the difficulties in connecting measurable material properties to device behavior via circuit element models. Here we use the principle of Local Activity to build a model of VO2 / SiN Mott threshold switches by sequentially accounting for constraints from a minimal set of quasi-static and dynamic electrical and high spatial resolution thermal data obtained via in-situ thermoreflectance mapping. By combining independent data sets for devices with varying dimensions, we distill the model to measurable material properties and established device scaling laws. The model can accurately predict electrical and thermal conductivities and capacitances and locally active dynamics (especially persistent spiking self-oscillations). The systematic procedure by which we develop this model has been a missing link in predictively connecting neuromorphic device behavior with their underlying material properties, and should enable rapid screening of material candidates before employing expensive manufacturing processes and testing procedures. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1002/adma.202205451

    View details for PubMedID 36165218

  • Lateral electrical transport and field-effect characteristics of sputtered p-type chalcogenide thin films APPLIED PHYSICS LETTERS Wahid, S., Daus, A., Khan, A., Chen, V., Neilson, K. M., Islam, M., Chen, M. E., Pop, E. 2021; 119 (23)

    View details for DOI 10.1063/5.0063759

    View details for Web of Science ID 000729364800005

  • First-principles calculation of the optoelectronic properties of doped methylammonium lead halide perovskites: A DFT-based study COMPUTATIONAL MATERIALS SCIENCE Rahman, N., Adnaan, M., Adhikary, D., Islam, M., Alam, M. 2018; 150: 439-447

    View details for DOI 10.1016/j.commatsci.2018.04.048

    View details for Web of Science ID 000433221000056

  • Transfer Matrix Formalism-Based Analytical Modeling and Performance Evaluation of Perovskite Solar Cells IEEE TRANSACTIONS ON ELECTRON DEVICES Wahid, S., Islam, M., Rahman, M., Alam, M. 2017; 64 (12): 5034-5041

    View details for DOI 10.1109/TED.2017.2763091

    View details for Web of Science ID 000417727500032

  • Effect of spatial distribution of generation rate on bulk heterojunction organic solar cell performance: A novel semi-analytical approach ORGANIC ELECTRONICS Islam, M., Wahid, S., Chowdhury, M., Hakim, F., Alam, M. 2017; 46: 226-241

    View details for DOI 10.1016/j.orgel.2017.04.021

    View details for Web of Science ID 000402708700030

  • Physics-based modeling and performance analysis of dual junction perovskite/silicon tandem solar cells PHYSICA STATUS SOLIDI A-APPLICATIONS AND MATERIALS SCIENCE Islam, M., Wahid, S., Alam, M. 2017; 214 (2)

    View details for DOI 10.1002/pssa.201600306

    View details for Web of Science ID 000395007800002

https://orcid.org/0000-0002-4112-0477