I am interested in increasing access to medical technologies, particularly in low-resource settings. I develop computational and bio-analytical technologies for early detection of disease, presently focusing on methods to increase sensitivity and multiplexing capabilities in diagnostic devices. Through developing these systems, I get to explore and play with subjects such as statistical modeling, image processing, manipulation and design of molecular systems, and optimization techniques. As a student, I have gotten to take classes ranging from many project based computation courses to linear dynamical systems to deep dives into chemistry of therapeutic drug development. I look forward to bringing my wide base of experiences in both computational and biological realms towards breakthroughs in precision health and diagnostics amenable to lower resource settings.

I also am always excited to teach and mentor, and have been involved with a myriad of opportunities including curriculum development and teaching AI/ML to high school students in US and India, K-12 STEM outreach in US, Scratch curriculum teaching to teachers in Taiwan, and graduate level courses such as Biological macromolecules to Stanford students! Im always happy to chat about how to best reach and inspire students and people of all ages, so please reach out!

Honors & Awards

  • Stanford Graduate Fellowship (SGF), Stanford University (2017-Present)
  • Graduate Research Fellowship, NSF (2019-Present)
  • Whitaker International Fellow, Whitaker International (2015-2016)
  • U.S. Student Fulbright Scholar, Fulbright (2015-2016)

Professional Education

  • Doctor of Philosophy, Stanford University, BIOE-PHD (2023)
  • Master of Science, Stanford University, EE-MS (2021)
  • BS, University of Washington, Bioengineering (2015)

Stanford Advisors

All Publications

  • Real-Time Spatiotemporal Measurement of Extracellular Signaling Molecules Using An Aptamer Switch-Conjugated Hydrogel Matrix. Advanced materials (Deerfield Beach, Fla.) Park, C. H., Thompson, I. A., Newman, S. S., Hein, L. A., Lian, X., Fu, K., Pan, J., Eisenstein, M., Soh, H. T. 2023: e2306704


    Cells rely on secreted signaling molecules to coordinate essential biological functions including development, metabolism, and immunity. Unfortunately, such signaling processes remain difficult to measure with sufficient chemical specificity and temporal resolution. To address this need, we have developed an aptamer-conjugated hydrogel matrix that enables continuous fluorescent measurement of specific secreted analytes - in two dimensions, in real-time. As a proof of concept, we performed real-time imaging of Dictyostelium discoideum cells, a well-studied amoeba model wherein inter-cellular communication is performed though cAMP signaling. We engineered a set of aptamer switches that generate a rapid and reversible change in fluorescence in response to cAMP signals. By combining multiple switches with different dynamic ranges, we can measure cAMP concentrations spanning three orders of magnitude in a single experiment. These sensors are embedded within a biocompatible hydrogel on which cells are cultured and their cAMP secretions can be imaged using fluorescent microscopy. Using this aptamer-hydrogel material system, we achieved the first direct measurements of oscillatory cAMP signaling that correlate closely with previous indirect measurements. Using different aptamer switches, this approach could be generalized for measuring other secreted molecules to directly visualize diverse extracellular signaling processes and the biological effects that they trigger in recipient cells. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1002/adma.202306704

    View details for PubMedID 37947789

  • Extending the dynamic range of biomarker quantification through molecular equalization. Nature communications Newman, S. S., Wilson, B. D., Mamerow, D., Wollant, B. C., Nyein, H., Rosenberg-Hasson, Y., Maecker, H. T., Eisenstein, M., Soh, H. T. 2023; 14 (1): 4192


    Precision medicine requires highly scalable methods of multiplexed biomarker quantification that can accurately describe patient physiology. Unfortunately, contemporary molecular detection methods are generally limited to a dynamic range of sensitivity spanning just 3-4 orders of magnitude, whereas the actual physiological dynamic range of the human plasma proteome spans more than 10 orders of magnitude. Current methods rely on sample splitting and differential dilution to compensate for this mismatch, but such measures greatly limit the reproducibility and scalability that can be achieved-in particular, the effects of non-linear dilution can greatly confound the analysis of multiplexed assays. We describe here a two-pronged strategy for equalizing the signal generated by each analyte in a multiplexed panel, thereby enabling simultaneous quantification of targets spanning a wide range of concentrations. We apply our 'EVROS' strategy to a proximity ligation assay and demonstrate simultaneous quantification of four analytes present at concentrations spanning from low femtomolar to mid-nanomolar levels. In this initial demonstration, we achieve a dynamic range spanning seven orders of magnitude in a single 5l sample of undiluted human serum, highlighting the opportunity to achieve sensitive, accurate detection of diverse analytes in a highly multiplexed fashion.

    View details for DOI 10.1038/s41467-023-39772-z

    View details for PubMedID 37443317

  • Improved immunoassay sensitivity and specificity using single-molecule colocalization. Nature communications Hariri, A. A., Newman, S. S., Tan, S., Mamerow, D., Adams, A. M., Maganzini, N., Zhong, B. L., Eisenstein, M., Dunn, A. R., Soh, H. T. 2022; 13 (1): 5359


    Enzyme-linked immunosorbent assays (ELISAs) are a cornerstone of modern molecular detection, but the technique still faces notable challenges. One of the biggest problems is discriminating true signal generated by target molecules versus non-specific background. Here, we developed a Single-Molecule Colocalization Assay (SiMCA) that overcomes this problem by employing total internal reflection fluorescence microscopy to quantify target proteins based on the colocalization of fluorescent signal from orthogonally labeled capture and detection antibodies. By specifically counting colocalized signals, we can eliminate the effects of background produced by non-specific binding of detection antibodies. Using TNF-alpha, we show that SiMCA achieves a three-fold lower limit of detection compared to conventional single-color assays and exhibits consistent performance for assays performed in complex specimens such as serum and blood. Our results help define the pernicious effects of non-specific background in immunoassays and demonstrate the diagnostic gains that can be achieved by eliminating those effects.

    View details for DOI 10.1038/s41467-022-32796-x

    View details for PubMedID 36097164

  • High density DNA data storage library via dehydration with digital microfluidic retrieval. Nature communications Newman, S., Stephenson, A. P., Willsey, M., Nguyen, B. H., Takahashi, C. N., Strauss, K., Ceze, L. 2019; 10 (1): 1706


    DNA promises to be a high density data storage medium, but physical storage poses a challenge. To store large amounts of data, pools must be physically isolated so they can share the same addressing scheme. We propose the storage of dehydrated DNA spots on glass as an approach for scalable DNA data storage. The dried spots can then be retrieved by a water droplet using a digital microfluidic device. Here we show that this storage schema works with varying spot organization, spotted masses of DNA, and droplet retrieval dwell times. In all cases, the majority of the DNA was retrieved and successfully sequenced. We demonstrate that the spots can be densely arranged on a microfluidic device without significant contamination of the retrieval. We also demonstrate that 1TB of data could be stored in a single spot of DNA and successfully retrieved using this method.

    View details for PubMedID 30979873

  • Puddle: A Dynamic, Error-Correcting, Full-Stack Microfluidics Platform Willsey, M., Stephenson, A. P., Takahashi, C., Vaid, P., Nguyen, B. H., Piszczek, M., Betts, C., Newman, S., Joshi, S., Strauss, K., Ceze, L., ACM ASSOC COMPUTING MACHINERY. 2019: 183–97
  • Random access in large-scale DNA data storage NATURE BIOTECHNOLOGY Organick, L., Ang, S., Chen, Y., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., Takahashi, C. N., Newman, S., Parker, H., Rashtchian, C., Stewart, K., Gupta, G., Carlson, R., Mulligan, J., Carmean, D., Seelig, G., Ceze, L., Strauss, K. 2018; 36 (3): 242-+


    Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.

    View details for DOI 10.1038/nbt.4079

    View details for Web of Science ID 000426698700018

    View details for PubMedID 29457795