Melax Tech Appoints Xiaoyan Wang, Ph.D. as Chief Scientific Officer
Jan 19, 2023
A leader with a track record of driving innovations and transforming healthcare with data intelligence
Houston, TX: Melax Tech, a world leader in biomedical natural language processing (NLP) technology, appoints Xiaoyan Wang, PhD., as Chief Scientific Officer of the company. Dr. Wang has spent two decades committed to driving innovations in healthcare AI modeling and transforming health care with data intelligence.
Xiaoyan Wang, Ph.D., served as the Vice President of Healthcare Analytics, Informatics, and Biopharma Solutions at Sema4 for three years, where she led the development of clinical evidence-generation platforms and clinical research in oncology, immunology, cardiovascular, respiratory, neurology, and rare diseases. Before joining the biopharma industry, Dr. Wang was a faculty member and principal investigator at the University of Connecticut, UConn Health Center, and Mount Sinai Health Systems bridging research, healthcare services, and teaching.
“Throughout the journey of academic and industrial worlds, I have witnessed challenges and promises of unlocking insight from data. I believe in the power of NLP and AI technology to revolutionize healthcare and improve patient outcomes. We can make the vast amounts of data in the biomedical field accessible and actionable for health care professionals. Now it is the time to reimagine the future. I am excited to be a part of a team at the forefront of the field,” says Dr. Xiaoyan Wang, CSO of Melax Tech.
“Dr. Wang brings incredible knowledge and leadership to Melax Tech and our customers. With years of experience in the NLP industry, Xiaoyan’s impact has been immediate. It shows again that Melax Tech is committed to providing the best in class expertise and products to our clientele," says Andre Pontin, CEO of Melax Tech.
About Melax Tech: Melax Tech empowers healthcare and life science organizations to use data science approaches such as AI / Natural Language Processing (NLP) technology to extract information from biomedical textual data to solve real-world problems.