Lab Members

Heiko Enderling, Ph.D.
Professor, Radiation Oncology
HEnderling@MDAnderson.org

Past President, Society for Mathematical Biology
Fellow, Society for Mathematical Biology

Nahum Puebla‑Osorio, D.V.M., Ph.D.
Assistant Professor

Nahum is trained as a veterinarian and immunologist. He earned his D.V.M. from the National Autonomous University of Mexico (UNAM) and his Ph.D. in comparative immunology from Texas A&M University.

Nahum’s research investigates how the tumor microenvironment (TME) shapes and can be re‑shaped by radiotherapy to improve the efficacy of adoptively transferred T cells against solid tumors. He integrates cellular and molecular immunology expertise, genomic instability and DNA‑repair pathways to design next-generation therapeutic approaches. Current efforts include engineering chimeric antigen receptors (CARs) for solid tumor targeting and elucidating how low-dose radiotherapy enhances T cell effector function. Two investigator‑initiated clinical trials (non-small cell lung cancer and advanced tumor-infiltrating lymphocyte therapy) test Nahum’s low-dose radiotherapy protocols paired with cellular therapies. Additionally, Nahum completed a nine-month intensive course in Data Science and Business Analytics (UT McCombs School of Business, 2023) and received advanced training in Python for Machine Learning and AI in 2024. He is applying these skills to develop novel machine-learning methods that address the challenges of missing data in radiation oncology research and using neural networks to generate synthetic Gramian angular fields representing time series. Nahum also serves the scientific community as a lead editor for the journals Frontiers in Immunology and Frontiers in Oncology, and as an ad‑hoc reviewer for funding agencies.

Mohammad Zahid, Ph.D.
Instructor

Mohammad received his Ph.D. in bioengineering from the University of Illinois Urbana-Champaign in 2018, where he worked in Andrew Smith’s lab and developed tools for quantitative molecular imaging. Since then, he’s been working in the Enderling Lab on mathematical models of response to various types of cancer treatment (e.g., radiotherapy, immunotherapy, photodynamic therapy) with a focus on modeling metrics for and shifts in tumor and immune dynamics.

Maureiq Ojwang, Ph.D.
Postdoctoral Fellow

Maureiq received her Ph.D. in biomathematics from North Carolina State University, Raleigh, North Carolina. She is interested in exploring biological processes using network, mathematical and agent-based modeling of dynamical systems. More specifically, her research interests include a data-driven understanding of tumor-immune-microenvironment interactions with respect to personalized therapy options. Outside work, she enjoys dancing, running and cat sitting.

Lois Okereke, Ph.D.
Postdoctoral Fellow

Lois received her Ph.D. in pure and applied mathematics at the African University of Science and Technology (AUST) Abuja Nigeria. She was a postdoctoral fellow at the Center for Computational Oncology at UT Austin where she worked on identifying optimal therapeutic regimens for cancer by exploiting nullclines in the systems of differential equations describing tumor growth and treatment response for cancers of the brain and breast. She brings this expertise to our work on clinical radiation response modeling for different cancers, helping us to further develop novel, patient-specific radiation protocols that improve response and outcome.

Reshmi Patel, Ph.D.
Postdoctoral Fellow

Reshmi received her Ph.D. in biomedical engineering from the Center of Computational Oncology at UT Austin. She is interested in developing mathematical models of tumor-immune interactions and building digital twins for cervical cancer radiotherapy.

Malgorzata Weh, Ph.D.
Postdoctoral Fellow

Gosia received her Ph.D. in integrated mathematical oncology at the Moffitt Cancer Center for her research on the impact of mutations on evolving populations. She is interested in applying mathematical oncology to clinical problems. Specifically, her research includes studies of tumor-immune interactions and how to best irradiate different tumors to harness robust immune response for cancer clearance.  

Shambhavi Kurup
Data Scientist

Shambhavi received her master's degree in computer science, data science and machine learning specialization from Rice University. She is working on abstracting clinical data for the development of digital twin models, as well as identifying novel predictive and prognostic biomarkers from routine biopsy tissues.

Ashna Patel
Research Intern

Ashna is a second-year undergraduate student at Northwestern University majoring in biomedical engineering and an undergraduate research intern in Enderling Lab. Her previous research involved using an agent-based model to determine trends in tumor invasion speed and developing sets of synthetic patients to train a machine learning algorithm to correctly predict recurrence outcomes in non-small cell lung cancer patients. Her current research involves working with mathematical models of radiation therapy.

Vikram Shah

Vikram received his B.A. in computational and applied mathematics from Rice University. He is leading the lab's work on simulating tumor growth and treatment response using partial differential equations.