Lab Members

Asiri Ediriwickrema M.D., Ph.D.
Principal Investigator
asiri (at) stanford.edu
ORCID

I earned my undergraduate degree in Mechanical Engineering from MIT with a minor in Biomedical Engineering. During this time, I had the privilege of working under the mentorship of Dr. Robert Langer and Dr. Rajiv Saigal. We explored how conductive polymers could mitigate neuronal damage following excitotoxic injuries. These experiences provided foundational training in biomedical research and quantitative methods, and motivated me to continue research during my medical training.

I therefore joined the lab of Dr. Mark Saltzman's while completing my medical education at Yale School of Medicine. We designed both systemic and topical nanoparticle platforms for preventative and therapeutic applications in cancer treatment. Following medical school, I moved to Stanford to complete my residency, fellowship, and Ph.D. in Hematology and Cancer Biology. Under the guidance of Dr. Ravi Majeti, I built a framework for studying healthy and malignant hematopoiesis using single cell multi-omics, and identified new multipotent progenitor cell populations in normal hematopoiesis and high-risk leukemia stem cells in acute myeloid leukemia.

As the principal investigator of the Asiri Lab, we are further developing these methods by integrating single-cell technologies, computational biology, machine learning, and functional hematology to investigate the complexities of both normal and malignant blood cell development.

Kotoha Togami, B.S.
Life Science Research Professional
kotoha (at) stanford.edu
ORCID

I grew up in Seattle, Toronto, Kochi (Japan), and all over California. I stayed in California to complete my bachelor’s degree in Statistical Data Science with a minor in Mathematics at UC Davis. During my undergrad, I joined Dr. Stefan Keller’s lab at UC Davis Veterinary Medicine where we developed methods to turn messy clinical data into clinician-ready tools. I automated a pipeline to parse, normalize, and validate veterinary lab data to produce clinical reports, reducing manual prep time. Additionally, I helped develop unsupervised machine learning models for clinical decision support which are now being used by veterinarians to assist diagnosis and prognostication of dog and equine diseases. Also during my undergrad, I interned as a Product Manager on Stanford Medicine’s MyHealth (patient portal) team, analyzing EHR, usage data, and patient surveys to improve patient experience and care delivery through MyHealth. During this time, I had the opportunity to join Dr. Jonathan H. Chen’s lab. Under his mentorship I contributed to the “Science & Medicine” chapter in the 2025 AI Index, focusing on LLM integration in clinical workflows and the role of social determinants of health in model performance and fairness. In the Asiri Lab, I am excited to apply my skills in data science and machine learning to build new clinical prediction systems for patients with myeloid malignancies. Outside of the lab, I like to go swimming in the summer, skiing in the winter, and watercolor paint year-round.

Michael Zheng, B.S., M.S.
Life Science Research Professional
mmzheng (at) stanford.edu

I grew up in the Bay Area and earned my Bachelor of Science at UC Santa Barbara, where I double majored in Statistics & Data Science and Biochemistry-Molecular Biology. As an undergraduate, I explored RNA regulation using a functional variant of CRISPR, gaining hands-on wet lab experience and becoming familiar with a wide range of molecular biology techniques. I later pursued a Master of Science in Computational Biology at Carnegie Mellon University to strengthen my foundation in computer science and pivot toward computational research. There, my work focused on optimizing the performance of a Hypergraphlet Counter through parallel programming in C++ and designing a Python-based sequence generator for synthetic intrinsically disordered proteins. Outside of research, I enjoy reading and playing bridge. In the Asiri Lab, I am excited to apply my computational skills to study blood development using single cell lineage tracing.

Ayush Garg
Undergraduate Student at Stanford.
ayushgarg (at) stanford.edu

I’m a freshman at Stanford University interested in bioinformatics, computer science, and artificial intelligence. I grew up in Dublin, California and have worked on research projects in the past with computer vision for brain and dental disease detection, as well as contributed to correlation studies on brain fMRI and structural MRI data. I’m passionate about using artificial intelligence to solve problems in healthcare and biomedicine, especially through machine learning models, and am excited to work on developing new computational methods for studying hematopoiesis and myeloid cancers in the Asiri Lab! In my free time, you can find me hiking, playing games, or just hanging out with friends.

Erika Chengxiang Li
Undergraduate Student at Stanford. Computer Science Major with Systems Concentration
erikaecl (at) stanford.edu

I’m currently a junior at Stanford University studying Computer Science with a concentration in Systems. I grew up in Orange County, California, where I first learned how to code. Since coming to Stanford, I’ve become passionate about applying AI to real-world systems that leverage big data—particularly in healthcare, where I’ve been working on using large language models (LLMs) to process and analyze unstructured data. In my free time, I’m an active member of aKDPhi, Stanford’s Asian-interest sorority, and I love going on long walks and exploring nature. In the Asiri Lab, I’m developing computational tools that use LLMs to interrogate large datasets in both healthy and malignant hematopoiesis

Camille Chu
High School Student at the Nueva School
camchu (at) stanford.edu

I am a high school student passionate about translational research in hematologic malignancies and solid tumors using both computational and experimental methods. In collaboration with the lab of Dr. Ravi Majeti in the Stanford Institute for Stem Cell Biology and Regenerative Medicine, and I am leveraging single-cell multi-omic data to identify differentially expressed cell surface markers within important cellular subpopulations in AML and other myeloid malignancies.

Evelyn Fonseca
Administrative Associate
evecarol (at) stanford.edu

I am an aspiring admin associate with roots in the vibrant city of Rio de Janeiro, Brazil. Growing up surrounded by Rio’s culture and stunning landscapes, I cultivated a passion for organization and efficiency that aligns with my love for connection and collaboration. With a keen eye for detail, I really enjoy coordinating tasks and supporting teams to help them reach their goals. My diverse background allows me to bring a unique perspective that adds warmth and hospitality to every interaction. Now settled in Mountain View, I’m eager to apply my skills and experiences to create a positive impact in my workplace while sharing the vibrant essence of Brazilian culture with my colleagues. Outside of the office, I love hiking in the beautiful California mountains, dancing, cooking, dogsitting, and staying active with my functional workouts.