Mondal Lab Team

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Shiyi Li

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Shi Yi
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Shiyi Li is a postdoctoral associate and is currently working in Dr. Mondal’s lab. His research mainly focuses on understanding the impact of ischemia injury on human DCD hearts. He is also working towards finding potential non-invasive biomarkers that can predict complications in LVAD patients. Additionally, he is investigating the impact of cardiac surgical procedures on endothelial function, which may help find potential biomarkers to predict cardiac surgery-related complications. The ultimate goal of his research is to optimize the medical management of these patients under the supervision of Dr. Mondal.

”Dr. Mondal is not only a brilliant scientist but also a kind and compassionate mentor. His humility and approachability make us a pleasure to work with. His lab is very productive, and he is very patient and willing to guide me through challenging research problems, I have made a lot of progress since I joined his lab. I really
appreciate that I can work in this amazing lab.”

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Katherine Nordick, M.D.

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Katherine Nordick, M.D.
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Dr. Katherine Nordick is a medical resident currently working in the Mondal Lab. She earned an MD from Creighton University School of Medicine in Omaha, Nebraska, and ended up matching into the General Surgery Research Track at Baylor. Her focus in cardiothoracic surgery has been on mechanical circulatory support (MCS) and transplant, as well as minimally invasive cardiac surgery. Katie is actively involved in both new and ongoing cutting-edge basic and clinical translational research in human DCD heart transplantation, OCS devices, MCS, and robotic cardiac surgery. Her research aims to advance the field and contribute to the development of new techniques and technologies.   

”Dr. Mondal has extensive basic and clinical translational research experience in cardiac surgery and has gotten me involved in a number of projects. He has been a dedicated mentor, and I am eager to continue to learn from his experience in conducting such research as part of the Mondal Lab team.”

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Ivan Murrieta-Alvarez, M.D.

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Ivan Murrieta-Alvarez, M.D.
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Dr. Ivan Murrieta-Alvarez works as a research coordinator in the Mondal Lab. He holds a Medical Degree from The Universidad Popular Autónoma del Estado de Puebla (UPAEP) in Puebla, México, and was involved with numerous research projects focused on immune modulation, hematopoietic stem cell therapy, and quantitative neuroimaging clinical analysis for demyelinating diseases. At Mondal Lab, his research activities are focused on the impact of the brain's morphological and architectural integrity on the development of neurological dysfunction in patients who are undergoing mechanical circulatory support. Under the supervision of Dr. Mondal, this research utilizes advanced neuroimaging pipelines to gain insights into this critical area of study.

”Working at the Mondal Lab has been an exceptional experience, characterized by collaborative teamwork, exciting research discoveries, and the inspiring leadership of Dr. Mondal.”

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Rishav Bhattacharya

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Rishav Bhattacharya
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Rishav Bhattacharya, a Junior at Texas A&M University, is currently studying Biochemistry with the intention of pursuing a career in medicine. Alongside his major, he is also pursuing minors in Spanish for Health Professionals. He aims to use his language skills to communicate more effectively with patients, providing them with better care. Rishav is dedicated to his studies, with a focus on his long-term goal of becoming an M.D./PhD. He is interested in the biochemical basis of heart diseases as well as ways to manipulate the chemistry to create novel solutions.

”Thus far, joining the Mondal Lab has been a great decision. Dr. Mondal has been a great mentor who has been very dedicated to his students. Though he is often busy, he always has helped guide me towards my desired career. Additionally, even when I have been slow to understand concepts as an undergraduate, Dr. Mondal has been very patient and supportive. I am glad to have joined the lab and look forward to contributing in the future.”

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Parker Kirby

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Parker Kirby
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Parker Kirby is a third-year medical student at Baylor College of Medicine and has a keen interest in the field of Cardiothoracic Surgery. His ultimate goal is to specialize in congenital heart surgery, and to that end, he is dedicatedly working towards acquiring in-depth knowledge of the underlying pathology responsible for heart failure under the supervision of Dr. Mondal. Parker is also intrigued by the biological effects of artificial circulation and artificial hearts, and he is determined to explore this fascinating area of research further. He is constantly exploring the potential of machine learning for the advancement of cardiothoracic surgery research. He aims to uncover new insights and develop novel solutions that can improve patient outcomes and quality of life.

”I have loved working with Dr. Mondal, as he loves mentoring students, and getting anyone who is interested involved in his research. He has been accommodating towards my medical school schedule and constantly works to make sure everyone can contribute to his projects using their unique perspective.”

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Jacob Scioscia

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Jacob Scioscia
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Jacob Scioscia is a medical student at Baylor College of Medicine. He is from Pittsburgh, PA, and went to undergrad at Penn State. He has a background in chemical engineering and statistics. He enjoys playing soccer, running, and making his own kombucha! He is fascinated by the field of cardiology and cardiothoracic surgery as it blends chemical engineering with human anatomy and physiology. His research interests in the Mondal lab revolve around translational medicine. In particular, he is involved in machine learning and predictive modeling, especially in improving outcomes for patients with congestive heart failure.

”I would like to continue working with Dr. Mondal because I believe the research that he is conducting has the potential to change the standard of care for these patients. He is an excellent mentor and has helped me better learn the research process and refine my skills in writing and presenting information.”

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Adel Hassan

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Adel Hassan
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Adel Hassan is an enthusiastic medical student at Baylor College of Medicine who has a keen interest in the workings of the heart at Mondal Lab. Adel's research interests involve using computational analysis and machine learning to identify novel biomarkers for early prediction of adverse outcomes in patients with cardiovascular disease. By leveraging big data, Adel aims to develop a more comprehensive understanding of how cardiovascular disease progresses and how it can be prevented or treated more effectively.

”Dr. Mondal has been an excellent mentor for my research. His lab is very productive, but despite how busy he is with all of his projects, he still makes time to guide his students and provide constructive feedback on how to conduct our research as effectively as possible. I look forward to continuing to work with this amazing lab.”

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Samuel Shenoi

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Samuel Shenoi
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Samuel Shenoi is a third-year medical student at Baylor College of Medicine. He received his Bachelor's degree in 2021 from Baylor University, where he majored in Bioinformatics. His research interests revolve around the application of computational workflows in medicine. He currently resides in Houston, TX, and is planning on going into Internal Medicine. His research interests in the Mondal lab include using various bioinformatics approaches toward analyzing omics data.

“Dr. Mondal’s cutting-edge research into the field of heart failure, heart transplantation, and circulatory support is of great interest to me. Specifically, Dr. Mondal’s ability to obtain, analyze, interpret, and apply proteomic and metabolomic data toward patient care.”

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Jason Uwaeze, Ph.D.

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Jason Uwaeze, Ph.D.
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Jason Uwaeze is a Computer Science Ph.D. student at Rice University. As a Nigerian-American born in San Francisco, he grew up in Austin, Texas, enjoying outdoor activities, traveling, and spending time with friends. His research in Mondal lab is focused on the application of machine learning algorithms to healthcare-related problems. He is specifically interested in leveraging imaging data (e.g., MRI and CT) or what kind of information can be learned through medical images.

”I have found research with Dr. Mondal to be both impactful and challenging, allowing me to utilize AI-based algorithms to solve challenging medical problems. With Dr. Mondal’s immense expertise in cardiovascular systems and surgical experience, I’d like to propel the integration of inexpensive and accurate AI-based solutions into healthcare.”

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Zicheng (Jeremy) Xu

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Zicheng (Jeremy) Xu
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Zicheng (Jeremy) Xu is a Junior undergraduate studying Computer Science and Mathematical Economic Analysis at Rice University. He is passionate about applying the latest technology and algorithms to the real world. Outside the academic realm, he enjoys playing basketball and piano. His research interest at Mondal Lab focuses on applying and developing state-of-the-art machine learning algorithms within the medical domain. Currently, he working on applying machine learning algorithms to classify and assess the risk of clinical complications in heart failure patients after mechanical circulatory support device implantation.

”Dr. Mondal provides me with opportunities to work with real-world datasets and channel my academic knowledge toward the betterment of human health. His experience in the medical field also gives guidance for developing innovative healthcare solutions.”

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Guangyao (Thomas) Zheng

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Guangyao (Thomas) Zheng
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Guangyao (Thomas) Zheng is a 2nd year Ph.D. student at Rice University, Department of Computer Science. He graduated from Johns Hopkins University with a B.S. degree in Applied Mathematics & Statistics and a minor in Computer Science. His research interest in Mondal Lab focuses on applying machine learning algorithms to hard problems in the medical field. For a very long time, statistical models were used to solve these problems, but they are limited in their ability. He aims to create better models to address the privacy, fairness, efficiency, explainability, and generalization problems associated with the application of machine learning to the medical field.

”I would like to continue working with Dr. Mondal for his widespread expertise in cardiothoracic research and invaluable first-hand access to patient data with crucial problems to solve.”