Rohit Singla

Rohit Singla
  • MD/PhD Student
  • School of Biomedical Engineering and Faculty of Medicine
  • University of British Columbia
  • ro[at]rsingla[dot]com
  • CV

About Me

I am an MD/PhD student in the School of Biomedical Engineering and Faculty of Medicine at the University of British Columbia, with my primary clinical training at the Island Medical Program, University of Victoria. My research focuses on the applications of ultrasound imaging, computer vision, machine learning, and physics within nephrology and organ transplantation. Under the mentorship of Prof. Robert Rohling and Dr. Christopher Nguan, I have pioneered AI-enabled ultrasound diagnostics for non-invasive assessment of intrinsic glomerular disease, significantly advancing early-stage disease detection and quantification.

As a clinician-engineer, I leverage my expertise in software engineering and biomedical data science to innovate medical technology. My research has been recognized nationally, with publications in journals such as the Journal of Medical Imaging, Ultrasound in Medicine & Biology, and Medical Imaging with Deep Learning. My contributions have garnered numerous accolades, including the top-ranked Vanier Scholarship and the Canadian Medical Hall of Fame Award for Medical Students.

I hold a MASc in Biomedical Engineering and a BASc in Computer Engineering from the University of British Columbia, specializing in Software Engineering. My professional journey includes roles as a consultant for leading biotech investment firms, where I applied my technical and strategic acumen to guide innovation and investment decisions.

My aspiration is to continue advancing medical technology and enhancing patient care through interdisciplinary collaboration and the translation of cutting-edge research.

My Research

My research focuses on the integration and application of advanced computational techniques, including deep learning, computer vision, and quantitative ultrasound imaging, in the fields of nephrology and organ transplantation. I leverage multi-modal datasets, encompassing ultrasound imaging, clinical data, and machine learning algorithms, to develop innovative diagnostic tools and improve patient outcomes in kidney disease.

I have had the privilege of working with interdisciplinary teams that includes experts in biomedical engineering, computer science, immunology, foundational science, urology, organ transplantation, renal pathology, nephrology, anesthesiology, radiology, obstetrics, and sonography.

Ultrasound Diagnostics and Quantitative Kidney Imaging

  • Singla, R.*, Ringstrom, C., Hu, G., Lessoway, V., Reid, J., Nguan, C., & Rohling, R. (2023, October). The open kidney ultrasound data set. In International Workshop on Advances in Simplifying Medical Ultrasound (pp. 155-164). Cham: Springer Nature Switzerland.
  • Singla, R.*, Ringstrom, C., Hu, R., Hu, Z., Lessoway, V., Reid, J., ... & Rohling, R. (2023). Automatic measurement of kidney dimensions in two-dimensional ultrasonography is comparable to expert sonographers. Journal of Medical Imaging, 10(3), 034003-034003.
  • Singla, R.*, Hu, R., Ringstrom, C., Lessoway, V., Reid, J., Nguan, C., & Rohling, R. (2023). The Kidneys Are Not All Normal: Transplanted Kidneys and Their Speckle Distributions. Ultrasound in Medicine & Biology, 49(5), 1268-1274.

Computer Vision and Physics in Medical Imaging

  • Hu, R., Singla, R.*, Yan, R., Mayer, C., & Rohling, R. N. (2019, July). Automated placenta segmentation with a convolutional neural network weighted by acoustic shadow detection. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 6718-6723). IEEE.
  • Hu, R., Singla, R.*, Deeba, F., & Rohling, R. N. (2019). Acoustic shadow detection: study and statistics of B-mode and radiofrequency data. Ultrasound in medicine & biology, 45(8), 2248-2257.
  • Singla, R.*, Ringstrom, C., Hu, R., Lessoway, V., Reid, J., Rohling, R., & Nguan, C. (2022, December). Speckle and shadows: ultrasound-specific physics-based data augmentation for kidney segmentation. In International Conference on Medical Imaging with Deep Learning (pp. 1139-1148). PMLR.
  • Hu, R., Singla, R.*, Ringstrom, C., Hu, Z., Lessoway, V., Reid, J., ... & Rohling, R. N. (2022, September). Prediction of Kidney Transplant Function with Machine Learning from Computational Ultrasound Features. In International Workshop on Advances in Simplifying Medical Ultrasound (pp. 34-43). Cham: Springer International Publishing.

Image-Guided Therapies and Augmented Reality

  • Singla, R.*, Edgcumbe, P., Pratt, P., Nguan, C., & Rohling, R. (2017). Intra‐operative ultrasound‐based augmented reality guidance for laparoscopic surgery. Healthcare technology letters, 4(5), 204-209.
  • Edgcumbe, P., Singla, R.*, Pratt, P., Schneider, C., Nguan, C., & Rohling, R. (2018). Follow the light: projector-based augmented reality intracorporeal system for laparoscopic surgery. Journal of Medical Imaging, 5(2), 021216-021216.
  • Singla, Rohit, et al. "Interdisciplinary development and evaluation of a novel needle guide for ultrasound-guided lumbar epidural placement." BMJ Innovations 7.1 (2021).

Medical Education

  • Hu, R., Fan, K. Y., Pandey, P., Hu, Z., Yau, O., Teng, M., ... & Singla, R.* (2022). Insights from teaching artificial intelligence to medical students in Canada. Communications medicine, 2(1), 63.
  • Teng, M., Singla, R.*, Yau, O., Lamoureux, D., Gupta, A., Hu, Z., ... & Field, T. S. (2022). Health care students’ perspectives on artificial intelligence: countrywide survey in Canada. JMIR medical education, 8(1), e33390.
  • Pupic, N., Ghaffari-Zadeh, A., Hu, R., Singla, R.*, Darras, K., Karwowska, A., & Forster, B. B. (2023). An evidence-based approach to artificial intelligence education for medical students: A systematic review. PLOS Digital Health, 2(11), e0000255.

Translational Research in Clinical Areas

  • Dawidek, M. T., Singla, R.*, Spooner, L., Ho, L., & Nguan, C. (2022). Clinical validation of an audio-based uroflowmetry application in adult males. Canadian Urological Association Journal, 16(3), E120.
  • Burden, E., Khehra, K., Singla, R.*, Spooner, L., Cho, A., & Nguan, C. (2021). PatientLink: a patient-centred status dashboard for the perioperative process. BMJ Innovations, 7(4).

My Professional Experience

My professional experience spans various roles, including consulting for leading biotech investment firms, where I applied my technical and strategic expertise to guide innovation and investment decisions. At Bloom Burton & Co., I have been a Contract Scientific Consultant since April 2024, performing indication prioritization and refining analysis of key biotech subsectors. At Amplitude Ventures, I have been a Contract Consultant since November 2023, after completing the Pre-Amp Fellowship in 2022, leading landscape analyses and due diligence on innovative technologies. Additionally, I work with an undisclosed company to advance ultrasound technology applications. I co-founded Epiloid Biotechnology, focusing on reducing risk in epileptic drug development through brain organoid phenotypic screening

Outreach and Advocacy

I am dedicated to enhancing diversity and inclusion within STEM, actively participating in university committees and symposiums focused on equity. As a fervent advocate for organ donation, I am a registered organ donor and encourage others to join this cause.

Connect With Me

I am passionate about using technology to improve healthcare outcomes and am always eager to engage in new collaborations, share knowledge, or (on select occasion) provide mentorship. Please reach out via email at ro [at] rsingla [dot] com to discuss how we can work together to innovate and improve the healthcare landscape.