What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Gene
The scientist’s investigation covers issues in Computer vision, Artificial intelligence, Rendering, Genetics and Computer graphics.
His research combines Representation and Computer vision.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Linear subspace and Affine transformation.
His study in the field of Real-time rendering is also linked to topics like Tracking system.
The concepts of his Genetics study are interwoven with issues in Reference population and Genetic diversity.
His work in Computer graphics addresses issues such as Visual hull, which are connected to fields such as Opacity.
His most cited work include:
- Plenoptic modeling: an image-based rendering system (1250 citations)
- Image-based visual hulls (845 citations)
- Unstructured lumigraph rendering (695 citations)
What are the main themes of his work throughout his whole career to date?
Leonard McMillan focuses on Artificial intelligence, Computer vision, Genetics, Computer graphics and Rendering.
His Artificial intelligence research integrates issues from Set, Linear subspace and Pattern recognition.
In Computer vision, he works on issues like Representation, which are connected to Data structure and Polygon mesh.
Leonard McMillan has included themes like Surface, Video processing and Visual hull in his Computer graphics study.
His research in the fields of Image-based modeling and rendering and Real-time rendering overlaps with other disciplines such as Viewpoints.
His research investigates the link between Genome and topics such as Computational biology that cross with problems in Phylogenetics.
He most often published in these fields:
- Artificial intelligence (44.77%)
- Computer vision (37.21%)
- Genetics (22.67%)
What were the highlights of his more recent work (between 2012-2020)?
- Genetics (22.67%)
- Genome (15.12%)
- Computational biology (10.47%)
In recent papers he was focusing on the following fields of study:
Genetics, Genome, Computational biology, Allele and Gene are his primary areas of study.
His research integrates issues of Genotyping and Sequence assembly in his study of Genome.
Leonard McMillan has researched Computational biology in several fields, including Genome-wide association study, Genetic linkage, Human genetics and Phylogenetic tree.
His work deals with themes such as Inheritance Patterns and Dosage compensation, which intersect with Allele.
His Gene research incorporates themes from Lasso and Regression.
Leonard McMillan has researched Artificial intelligence in several fields, including Content and Machine learning.
Between 2012 and 2020, his most popular works were:
- Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance (150 citations)
- Modeling host genetic regulation of influenza pathogenesis in the collaborative cross. (142 citations)
- The Mouse Universal Genotyping Array: From Substrains to Subspecies (116 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Gene
- Statistics
His primary areas of investigation include Genetics, Genome, Allele, Inbred strain and Gene.
His study in Meiotic drive, Quantitative trait locus, Haplotype, Reference genome and Genetic variation are all subfields of Genetics.
His work deals with themes such as Phenotype and Genetic diversity, which intersect with Quantitative trait locus.
His research integrates issues of Genotyping, Set and Gene mapping in his study of Genome.
His biological study spans a wide range of topics, including Python, Construct and Computational biology.
His Allele research incorporates elements of Expression quantitative trait loci, Phylogenetics, Imprinting and Dosage compensation.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
