Our Team

Our Team

Felix Dietlein, MD PhD

Principal Investigator

Dr. Felix Dietlein is an Assistant Professor at Harvard Medical School and faculty in the Computational Health Informatics Program at Boston Children’s Hospital. He is also an Associate Member at the Broad Institute of MIT and Harvard and an Investigator at the Dana-Farber Cancer Institute. He holds an MD and PhDs in mathematics and molecular medicine. He completed his postdoctoral training at Dana-Farber.

His mission is to advance precision medicine by identifying molecular vulnerabilities in tumor genomes, translating them into targeted therapies, and improving diagnostics in the clinical setting. His multidisciplinary training in medicine, biology, and mathematics allows him to approach complex problems from diverse perspectives. He is dedicated to training the next generation of interdisciplinary scientists by providing mentorship to researchers at various stages in their careers and integrating them into an inclusive and collaborative laboratory environment.

Matti Corren

Medical and Computer Science Student, Hebrew University of Jerusalem (remote)

Matti Corren’s research aims to build machine learning-based classifiers based on methylation and cell-free DNA for early-stage detection of precancer lesions in tumor patients. He combines cancer genomics mechanisms with clinical observational phenotypes to define early lesions that prime cells for tumor development.

Antti Haekkinen, PhD

Senior Postdoc, HMS

Dr. Antti Haekkinen has in-depth expertise in computational methods for phenotype profiling and an established track record of analyzing multi-omics data of ovarian cancer. His long term vision is to advance personalized medicine by the rational design of combination therapies that leverage mechanisms in noncoding cancer genomics, DNA repair, and the translational potential of clinical data.

Mirue Kang

BSc student, Brandeis

Mirue Kang is an  undergraduate student at Brandeis University. Her research focuses on defining genomic loci that confer risks for cancer phenotypes, identifying differences between normal and epithelial cancer stem cells, and applying genetic risk scores to personalized medicine.

Robert Khashan

Incoming Medical Graduate Student, University of Gothenburg, Sweden

Robert Khashan is a medical student specializing in pediatric tumor biology. He combines genomic, proteomic, and expression data with innovations in data science for an in-depth analysis of oncogenic pathways that drive lymphomas and neuroblastomas. His long-term goal is to advance our biological understanding of pediatric tumors and the efficacy of personalized therapies for children with cancer.

Wanru Liu, BSc

Incoming MSc student, Harvard

Wanru Liu is a master’s student in the Global Health and Population program of the Harvard School of Public Health. Her primary focus is on biostatistics and cancer epidemiology. By amalgamating data from both fields, she aims to address health disparities in cancer and gain genomic insights that could improve screening methods and population health.

Platon Lukyanenko, PhD

Postdoc, HMS

Dr. Platon Lukyanenko intersects cancer biology with machine learning methods to decode multifaceted roles of oncogenic mutations. By training autoencoder models on multiomics data, he aims to illuminate the coordinated activity of mutations in tumorigenesis and pave the way for genome-inspired personalized combination therapies.

Sara Uhan, MSc

Incoming PhD Student; co-mentored with Drs. Wirth and Keller, Charité Berlin

Sara Uhan is a PhD student and Fulbright Scholar . She studies SUMOylation as a pivotal post-translational modification in tumor cells and its effect on the localization, stability, and activity of proteins. She pairs experimental with computational strategies to define SUMO-specific networks in cancer cells and translate them into new drug targets for precision medicine.

Yuelai (Eli) Wang, BSc

MSc student, Harvard

Eli Wang is a master’s student in the Computational Biology and Quantitative Genetics program of the Harvard School of Public Health. He focuses on single-cell epigenomics and studies regulatory regions in cancer genomes. He has mastered a diverse repertoire of tools and pipelines to process and harmonize these data and combines them with statistical models in cancer genomics.

Yuxiang Zhou, BSc

MSc student, Boston University

Yuxiang Zhou has extensive experience in the design of differential expression analyses and their application to diverse diseases. His current work combines these tools with functional experimental data to study the effect of somatic mutations on cancer gene expression. He further aims to characterize complex oncogenic signaling changes that cause malignant transformation.

Aniket Dey

Alumini (Research Intern 2022-23)

Aniket Dey studies interactions of tumor cells and the microenvironment. He pairs functional data from cell lines with genomic profiles from cancer patients to dissect mechanisms that allow tumors to spread to distant organs. He also combines tumor biology with aspects of public health for harmonizing the assessment of personalized cancer risk across demographics.

Ian Lo, BSc

Alumini (MSc student, Harvard, 2022-23)

Ian Lo is a master’s student in the Health Data Science program at the Harvard T.H. Chan School of Public Health. Her research interests include the use of machine learning and other computational approaches to studying human genetic diseases and disorders.

Vatsal Parikh

Alumni (Research Intern 2022)

Vatsal Parikh’s research focuses on applying machine learning techniques to tumor expression profiles, pairing them with data from scalable experimental assays, and inspiring the design of targeted therapies. He also designs interactive web resources to communicate his science to a broad audience.

Yi-Ting Tsai, BSc

Alumini (MSc student, Harvard, 2022-23)

Yi-Ting Tsai is a master’s student in the Health Data Science program at the Harvard T.H. Chan School of Public Health. Her research focuses on developing new computational strategies for maximizing the value of sequencing in patient care by pairing clinical with genome data.

Additional profiles coming soon!
Please see www.chip.org/people/postdoctoral-fellows for an overview of the profiles of other CHIP Fellows in our program.

Join Our Team

Please contact us to learn more about
career opportunities and the philosophy of our lab.