Elisa W. Email & Phone Number

Ann Arbor, Mi, Us

Foster City, California, Us

Ann Arbor, Michigan, Us

1. Developed statistical/machine learning algorithms for predictive disease modeling that were presented as full publications in three prestigious engineering conferences. The algorithms featured multimodal learning, specifically privileged learning, co-learning methods, and fusion.2. Leveraged PyTorch and sklearn for novel deep learning and non-deep learning approaches to detect overall survival in brain glioma histopathology, glioma pseudoprogression in MRI, temporomandibular osteoarthritis in dental data, and intraocular lens power in tabular surgical data.3. Published 18 academic works by graduation (most involving statistical and ML methods), accruing over 300 citations.4. Led diverse lab activities, from website construction to establishing best practices in code/data management, ensuring streamlined operations and fostering collaborative research.5. Additional unpublished projects involved work with CT, omics and ARDS detection in 1-D ECG data.6. THESIS FOCUS: Multimodal learning. Submitted a review on multimodal learning (under peer review), designed a low-parameter multimodal fusion model for MRI and a privileged learning model using Random Forest.

South San Francisco, California, Us

1. Leveraged cutting-edge deep learning methodologies to derive biological insights, focusing on RNA-seq prediction from histology slides via computer vision.2. Coding in both R and Python. Worked with Seurat files, normalizing and creating signature values. Develop models with PyTorch to predict RNA expression in histological tissue. Led to authorship on at least one paper.3. Optimized image processing workflows by enhancing data preprocessing steps and redesigning the Dataset class. This increased the speed from which the model processed by 100x.4. My work on quality assurance of spatial transcriptomic data provided a set of quantifiable rules, supported by lots of evidence, by which we would consider some sequence data unreliable.5. Replicated the ST-Net paper and developed m own version of ST-Net using ResNets and built on it.6. Assisted in experiments for our team-developed improvement to the HE2RNA model.7. Praised for strong documentation

1. Data Engineer and Sales Engineer work at a start-up which graduated from its San Diego incubator and moved to Detroit. Developed machine-learning solutions to improve our data preparation software’s recognition of imported dataset columns which was a feature later adopted into the software.2. Wrote several scripts leveraging REST APIs and web scraping to create demos for customers. Also created data obfuscation scripts.3. Track record of excellent communication skills. Presented at a company booth at the TriCon Molecular conference to promote the product. Also communicated directly with customers to get feedback on how to improve our software.4. Ran data analysis and visualizations on publicly available datasets, providing reports with Tableau or matplotlib figures.5. Corresponded with the software developers and CTO daily to fix bugs. Performed daily software testing and QA which addressed tens of minor issues of the product over a year and increased user experience.

Ann Arbor, Mi, Us

1. Proteomic analysis of post-translational modifications in a potential biomarker for hepatocellular carcinoma2. Presented an abstract on my work at ASMS 20173. I wrote significant portions of a review for Mass Spectrometry Reviews (IF: 9.3) resulting in second authorship

Ann Arbor, Michigan, Us

TEACHING: LSA Psychology: PSYCH 345 Human Neuropsychology. Also taught in Fall Semester September-December 2017.

Juelich, De

1. Created a statistical algorithm for biological age using SAS and python based on literature2. My python version was used in a Harvard study on mouse aging, resulting in co-authorship in a Nature Communications paper with the lab of famous anti-aging scientist Dr. David Sinclair.

Ann Arbor, Michigan, Us

TEACHING: Instructional Aide for N527: Promoting Optimal Models for Healthcare Delivery at the School of Nursing. Work includes holding office hours for students, facilitating group discussions that guide student groups in their independent projects, working with the professor and other instructional aides, discussing elements of class design, and grading weekly as well as midterm assignments.

Doctor Of Philosophy - Phd, Bioinformatics

Master Of Science - Ms, Bioinformatics

Master Of Public Health - Mph, Molecular Epidemiology

Bachelor Of Science - Bs