Professional Affiliations and Activities

  • Trainee, Stanford NIH Biotechnology Training Grant Program (2017 - Present)
  • Member (previously Corresponding Secretary), Tau Beta Pi (Engineering Honor Society) (2013 - Present)
  • Member (previously Vice President), Alpha Eta Mu Beta (Biomedical Engineering Honor Society) (2013 - Present)

Education & Certifications

  • Bachelor of Science, Boston University, Biomedical Engineering (2015)
  • Master of Science, Stanford University, BIOE-MS (2017)

Stanford Advisors

All Publications

  • A confirmatory test for sperm in sexual assault samples using a microfluidic-integrated cell phone imaging system. Forensic science international. Genetics Deshmukh, S., Inci, F., Karaaslan, M. G., Ogut, M. G., Duncan, D., Klevan, L., Duncan, G., Demirci, U. 2020; 48: 102313


    Rapid and efficient processing of sexual assault evidence to accelerate forensic investigation and decrease casework backlogs is urgently needed. Therefore, the standardized protocols currently used in forensic laboratories can benefit from continued innovation to handle the increasing number and complexity of samples being submitted to forensic labs. To our knowledge, there is currently no available rapid and portable forensic screening technology based on a confirmatory test for sperm identification in a sexual assault kit. Here, we present a novel forensic sample screening tool, i.e., a microchip integrated with a portable cell phone imaging platform that records and processes images for further investigation and storage. The platform (i) precisely and rapidly screens swab samples (<15 min after sample preparation on-chip); (ii) selectively captures sperm from mock sexual assault samples using a novel and previously published SLeX-based surface chemistry treatment (iii) separates non-sperm contents (epithelial cells and debris in this case) out of the channel by flow prior to imaging; (iv) captures cell phone images on a portable cellphone-integrated imaging platform, (v) quantitatively differentiates sperm cells from epithelial cells, using a morphology detection code that leverages Laplacian of Gaussian and Hough gradient transform methods; (vi) is sensitive within a forensic cut-off (>95% accuracy) compared to the manual counts; (vii) provides a cost-effective and timely solution to a problem which in the past has taken a great deal of time; and (viii) handles small volumes of sample (20 muL). This integration of the cellphone imaging platform and cell recognition algorithms with disposable microchips can be a new direction toward a direct visual test to screen and differentiate sperm from epithelial cell types in forensic samples for a crime laboratory scenario. With further development, this integrated platform could assist a sexual assault nurse examiner (SANE) in a hospital or sexual assault treatment center facility to flag sperm-containing samples prior to further downstream testing.

    View details for DOI 10.1016/j.fsigen.2020.102313

    View details for PubMedID 32570000