People

Mohamad is a Ph.D. candidate in Bioengineering. He conducted research in computational fluid dynamics and applied machine learning methods to analyze medical data in the past. His current research interest includes developing in silico techniques to understand biological systems. He is working on increasing the detection of drugs’ side effects using network modeling. In his free time, he enjoys listening to audiobooks, watching movies, going to nature, and spending time with friends.

Rayo Suseno (pronounced rah-yo su-say-no) is a Master’s student in the Department of Bioengineering at UCLA. During his internship for a genetics company as a bioinformatician, he was introduced to the idea of pharmacogenomics, which inspired him to join LUNE. Rayo aims to apply and learn bioinformatics skills for the validation and further advancement of drug network research. Specifically, he would like to investigate how patient genetic variants affect the development of disease pathways in PathFX, by utilizing various databases. In his free time, Rayo enjoys running, playing music, and listening to old songs, mainly from the 80s.

Shawn Liu is a bioengineering graduate student at UCLA. Shawn is interested in mining clinical data to engineer computational models, as it has shown potential to be an integral tool to improving clinical predictions in medicine. Shawn has extensive dry lab and wet lab experiences, as he has previously worked with induced pluripotent stem cells and ODE models. When Shawn is not working in the lab, he can be found playing and composing music, running, hiking, cooking, teaching, and hanging out with friends. 

Anjali is an undergraduate studying Bioengineering at UCLA. Anjali is currently working on disease phenotyping the electronic health record by researching the clinical diagnosis and assessment of various diseases and translating them into computable terms corresponding with the electronic health record. The goal of this project is to analyze patterns and findings of the phenotyping process. These definitions can then help conduct observational studies to study predicted drug pathways provided by the PathFX algorithm.

Jay is an undergraduate bioengineering student at UCLA. Currently, he is working on modeling the downstream effects of drugs on cardiac networks through using PathFX. He hopes to further understand cardiac-related drugs and their phenotypes by analyzing drug targets and their associations with other proteins through network modeling. Jay enjoys running, rooting for his favorite sports teams, and playing the guitar in his free time.

Coming soon!

Avani is a fourth-year statistics major and mathematical biology minor student at UCLA. As a part of the LUNE, she is working collaboratively to understand how gene variants affect drug side effects. In the future, Avani is hoping to pursue biostatistics and public health, aiming to get an MPH in a few years. Outside of academics, Avani is an active part of residential life at UCLA, and the Internal Vice President of Bruin Club Tennis.

Josh is an undergraduate bioengineer at UCLA. Currently, he researches biomedical vocabularies and leverages the Unified Medical Language System to design translation tools. He aims to curb network overprediction via comparisons with established drug-condition relationship data. In his free time, Josh enjoys game development, programming, and distance running.

Yifei is an undergraduate in the department of bioengineering at UCLA. Currently, Yifei is working to understand the various methods of modeling drug synergy in silico which is advantageous in cost and flexibility compared to in vitro drug combinatory screenings. Building on this knowledge, the goal of this project is to utilize a network approach, taking into consideration drug targets and protein pathways among other features, to model the effect of synergistic drug combinations. Outside of school, Yifei enjoys exploring the outdoors through activities such as hiking and learning to cook new dishes with moderate success.

Kyle is currently a sophomore at University of Massachusetts, Amherst studying computer science and his interests are in software design. Kyle worked with Dr. Wilson during 2021 to build the benchmark_PathFX tool – a suite of code that compares how various sources of input data affect network predictions. With Kyle’s tool, the lab is actively investigating how changing drug binding and protein-protein interaction input data affect the ability to predict drug side effects.

All graduate applications must go through the Bioengineering application process. If interested in joining the lab, or if you have questions about research projects, please email Dr. Wilson.