Mark Heimann
About Mark Heimann
Mark Heimann is a Postdoctoral Researcher at Lawrence Livermore National Laboratory, specializing in feature representation learning methods for networks. He holds a Ph.D. in Computer Science from the University of Michigan and has extensive experience in data mining and research across various institutions.
Work at Lawrence Livermore National Laboratory
Mark Heimann has been employed as a Postdoctoral Researcher at Lawrence Livermore National Laboratory since 2020. His role involves conducting advanced research in computer science, focusing on data mining and network analysis. His work contributes to the laboratory's mission of addressing national security challenges through innovative scientific research.
Education and Expertise
Mark Heimann holds a Doctor of Philosophy (Ph.D.) in Computer Science from the University of Michigan, where he studied from 2015 to 2020. He also earned a Master of Science (M.S.) in Computer Science from Washington University in St. Louis, completing his studies from 2013 to 2015. In addition to his computer science background, he has a Bachelor of Arts (B.A.) in Mathematics and Economics from the same institution, which he completed from 2011 to 2015.
Background
Prior to his current position, Mark Heimann gained diverse experience in research and internships. He worked as a Visiting Researcher at the Information Sciences Institute for two months in 2019. His earlier roles include a Graduate Research Intern at Oak Ridge National Laboratory and a Software Engineer Intern at Algorithmia Inc. He also served as a Graduate Student Instructor and Teaching Assistant at the University of Michigan and Washington University in St. Louis, respectively.
Research Contributions
Mark Heimann has developed new feature representation learning methods for nodes in networks, which have been utilized to address complex data mining tasks across large networks. He has collaborated with various technology companies to implement node embeddings on extensive datasets containing millions of entities. His published work has received recognition, earning best paper awards in leading data mining conferences.
Internship Experience
Mark Heimann has completed several internships that enhanced his research and technical skills. He served as a Data Science Research Intern at Adobe in 2019 and as a Graduate Research Intern at Oak Ridge National Laboratory in 2018. Earlier in his career, he was an Undergraduate Researcher at Harvey Mudd College and The University of North Carolina at Greensboro, as well as a Student Intern at Washington University School of Medicine.