Dr. Eckart Bindewald is a seasoned bioinformatics and computational biology expert with over two decades of experience developing cutting-edge AI/ML algorithms for biomedical research. He holds a Ph.D. in Natural Sciences from the University of Heidelberg, Germany, specializing in structural bioinformatics and protein structure prediction.

Dr. Eckart Bindewald has more than 30 peer reviewed publications in the areas of bioinformatics and machine learning. He developed computational approaches for protein fold recognition, RNA structure prediction and design, nucleic acid nanotechnology as well as genome annotation. He taught courses in bioinformatics, mathematics, machine learning and AI.

Dr. Bindewald has made significant contributions to the field of biomarker discovery, mainly through integrating multi-omics data and advanced machine-learning techniques. His work has been pivotal in advancing the understanding of RNA and protein structures and developing novel computational tools for RNA and DNA structure prediction and design.

At Karyon Bio, Dr. Bindewald leads the AI/ML initiatives, driving innovations in biomarker discovery by leveraging his extensive experience in generative AI, deep learning, and data mining. His research efforts are focused on harnessing the power of artificial intelligence to uncover new biomarkers and therapeutic targets, ultimately advancing personalized medicine.

Mahati is an accomplished Bioinformatics Data Scientist with a proven track record in leveraging AI and machine learning for biomarker discovery. With a Master’s in Bioinformatics from Indiana University and a Bachelor’s in Biotechnology, Mahati excels at applying advanced computational techniques to genetic research.

Previously, she developed predictive models for gene biomarker identification, significantly advancing the classification of diseases like cancer and diabetic retinopathy using deep learning. Mahati also enhanced data accessibility through biomedical ontologies and NLP, and her expertise in Next-Generation Sequencing (NGS) supports informed decision-making in drug discovery.

Proficient in Python, R, TensorFlow, and PyTorch, Mahati is adept at leading interdisciplinary teams to create innovative AI-driven solutions. Her work is driven by a passion for precision medicine and improving patient outcomes through cutting-edge bioinformatics.