Meet UCLA Senior, Arjun Verma, who is majoring in Molecular, Cell and Developmental Biology with a minor in Bioinformatics. As a member of the Undergraduate Research Scholars Program, he submitted work and presented at the Western Thoracic Surgical Association and was one of 19 podium presentations at a conference that typically only accepts residents and attending physicians for presentation.

Arjun was published as a first author in the article “Incidence and Outcomes of Laryngeal Complications Following Adult Cardiac Surgery: A National Analysis” that discuss the increased morbidity of Laryngeal complications which call for further development of active screening protocols in order to increase early detection. In addition, Arjun recently co-authored a publication in JAMA Cardiology called “Center-Level Variation in Transplant Rates Following the Heart Allocation Policy Change“.

 

How did you first get involved in your research project? 

During junior year of high school, an eye opening research experience at the University of Massachusetts Amherst solidified my passion for biomedical research. After searching for research opportunities online, I found the CORE Lab’s website and saw a plethora of clinical outcomes research projects. I knew that clinical outcomes research was the perfect opportunity for me to apply my machine learning knowledge to clinical problems. Thus, when I committed to UCLA, I immediately emailed Dr. Benharash and joined the lab in my first quarter on campus.

 

How would you describe your research experience at UCLA?

My research experience at UCLA has been extremely rewarding. When I joined Dr. Benharash’s CORE Lab, I was immediately greeted with a warm, collaborative lab environment. Members in the lab, including surgical residents, medical students and other undergraduates, were excited to have me contribute to their projects and develop my research skills. My research typically involves applying data science and machine learning techniques to large datasets of surgical patients in order to identify clinical and hospital factors that contribute to postoperative complications and prolonged length of stay. One of my most impactful projects has been to develop machine learning models to predict length of stay after cardiac operations. These tools will be implemented in the UCLA electronic medical record systems and will help inform patient scheduling strategies. Ultimately, this project allows hospital administrators and surgeons to reduce waiting list times. Through my experiences in the CORE Lab, I further developed my programming skills, learned several machine learning techniques and how to write professional, scientific manuscripts that are suitable for publication in peer reviewed journals.

 

What is one piece of advice you have for other students thinking about getting involved in research?

I think that there are two important things that make a good research experience: an amazing mentor and a true passion for the research topic. I would recommend taking time to find a research project and mentor that will provide you with opportunities that will be both personally and professionally fruitful. In addition, I would encourage people to reach out to labs with the intent of diving deeply into the subject material.

 

What are your future career goals?

After graduation, I plan to attend medical school and pursue a career as a physician scientist. I hope that my future research projects will also involve developing additional machine learning models to predict clinical outcomes following surgery.