Support Biomedical Innovation: BMES Technical Projects

Join our Campaign!

The Biomedical Engineering Society at UCLA (BMES) is in the midst of its annual Crowdfunding Campaign to fuel student‑driven innovation in healthcare technology. After months of computer modeling our design and research projects, we’re ready to build real‑life prototypes and advance cancer‑treatment research that could help shape the future of healthcare.

Our goal is $6,000, and every gift, no matter the size, helps bring breakthrough ideas to life.

Who are we?

BMES is a student-led organization that gives young engineers the opportunity to gain hands-on experience through our year-long design and research teams. Our team members design original, innovative projects that tackle key biomedical issues threatening local and global communities.

Please support our efforts by donating today! Your contributions will fund the materials we need to construct, implement, and share our innovations.

Design: Engineering Novel Solutions

BMES is committed to developing creative, cost-effective solutions to problems in the biomedical space. Our current design projects focus on user-centered and affordable designs to promote equitable healthcare and hazard prevention. Each design team will identify high-impact solutions, develop working prototypes, and advance their innovations through conferences and design competitions.

Intravesical Drug Delivery
Patients with urothelial cancers currently need repeated clinic visits to have chemotherapy placed directly into the bladder. In partnership with Cedars-Sinai, we hope to change that by developing sustained-release devices that deliver medication over several weeks: a drug-releasing Foley balloon for the bladder, and a dissolvable bead-on-wire system that can reach the bladder, ureter, or kidney. Overall, we are excited to use engineering to make cancer treatment less burdensome for the patients who need it! 

Project Manager: Isaac Rodney

Maxillary Sinus Biopsy Tool for Oral Surgeons
Before a sinus lift or bone graft, undetected infection or sinus disease can cause the graft to fail, yet oral surgeons have few ways to evaluate the sinus without delays or outside referrals. We hope to address this by designing a minimally invasive tool that combines a camera and light, suction, and a rotating tissue sampler in a single device. Overall, we are excited to use engineering to help surgeons make better decisions and get patients to their implants sooner!

Project Managers: Ellen Zulkarnain and Emilie Liao

Redesigning the Obstetrics Forceps for Safer Assisted Delivery and Improved Physician Training

Present-day obstetrics forceps are associated with not only causing maternal and fetal injuries, but also lacking good  visualization for obstetrics training. We hope to address these challenges by redesigning the forceps to be thinner, and to contain sensors and safer biocompatible materials. Overall, we are excited to utilize engineering to make the forceps easier to use and more comfortable for the patients who may need them!

Project Managers: Michael Makhoul and Teresa Tao

Skin-Conformal Electrode Strip for Site-Specific Neuromuscular Evaluation

Our project aims to develop a skin-conformal electrode strip designed to capture site-specific neuromuscular activity and movement with high spatial precision. Within the system, multiple strips will be able to synchronize across different muscle groups to analyze how muscles work together and track movement patterns during tasks such as kicking, throwing, walking, or breathing. The platform will ultimately be able to support applications in sports performance, movement analysis, and muscular rehabilitation.

Project Managers: Ish Bali and Vijay Karthikeyan 

Predictive Asthma Care via ML-Powered Longitudinal Wearable Monitoring

We aim to develop a wearable monitoring system for asthma patients that combines breathing, environmental, and activity-related sensor data to provide early warnings for potential asthma attacks. The system would use an ergonomic upper-chest garment, a clinician-facing dashboard, and machine learning models to help patients better understand their condition, reduce the burden of asthma management. We hope to ultimately make possible more proactive, personalized care for asthma. 

Project Managers: Anson Ting and Ryan Knight

Research: Tackling Biomedical Questions

BMES researchers are investigating the scientific questions at the heart of medical innovation. Our current research projects focus on understanding metabolic memory in cells exposed to hyperglycemia and engineering bacterial biosensors for toxic groundwater arsenic. Our research teams pursue these goals through rigorous experimental methods and share their findings with the scientific community at local and national conferences.

Investigating Metabolic Memory in Cells Exposed to Hyperglycemia

We are studying metabolic memory, the phenomenon in which cells continue to show disease-related changes long after a harmful metabolic condition, such as high blood glucose, has been corrected. We will culture cells under high-glucose conditions, return them to normal glucose levels, and measure how gene expression, mitochondrial function, and oxidative stress change over time. By analyzing the differences between cells with and without prior exposure, we hope to identify the molecular mechanisms that sustain this memory and could be targeted to prevent long-term diabetic complications.

Project Managers: Aarthi Raghavan and Shardul Singh

Smartphone-Integrated Bacterial Biosensor for Point-of-Need Arsenic Detection

Arsenic is a silent killer that causes cancer, cardiovascular disease, and developmental issues through groundwater contamination. 140+ million people across 50+ countries are exposed to arsenic-contaminated groundwater above the WHO’s safe limit of 10 ppb, and because groundwater arsenic levels are dynamic, they require continuous monitoring and testing. Our objective is to engineer several arsenic-responsive E. coli strains, then immobilize the bacteria on a membrane for detection with a 3D-printed smartphone dark box. This multiplexed biosensor can be paired with custom software to enable accessible point-of-need aqueous arsenic concentration quantification. 

Project Managers: Yeonjun Kim and Michael Portnoy

Computational: Accelerating Discovery with Code

BMES computational researchers use modeling, algorithms, and high-performance computing to answer biological questions that are slow or costly to tackle in the lab. Our current project applies logic-based models of gene regulatory networks to predict which genetic interventions produce a desired outcome, helping guide experiments before they ever reach the bench.

Logic-Based Optimization of Gene Regulatory Networks

Finding which combinations of genes to switch on or off to get a desired result, such as maximizing protein production or activating programmed cell death, usually requires expensive and time-consuming wet lab experiments. We hope to address this by building a computational framework that models gene networks with Boolean logic and uses SAT solvers to find the best gene states, drawing on public databases like Reactome and KEGG and running on UCLA’s Hoffman2 computing cluster. Overall, we are excited to use computation to make biological discovery faster and more accessible!

Project Managers: Siddharth Bommareddy

Please contact us at bmes@g.ucla.edu  if you have any questions!

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