Sergey Klimov, Msc, Phd Email & Phone Number

Irving, Texas, US

Irving, Texas, US

Irving, Texas, US

Atlanta, GA, US

• Derived multiple assays, from immunohistochemistry and clino-pathological variables, to fit into a logistic regression which predicted >6x higher risk for specific site of breast metastasis over a 15-year follow-up.
• Designed a state of art breast cancer image analysis pipeline which annotated surgical tissue before using a handcrafted list of over 3k textural and spatial features and a machine learning zoo to identify patients who.
• Developed a nested CNN image analysis model to predict Pancreatic Neuroendocrine tumor (PanNET) metastasis risk. The novel 3 step approach (annotation, whole slide feature extraction, outcome prediction) leveraged over.
• Biostatistical lead in expansive international collaborations to identify various protein expression prognostic value, depending on race, through survival analysis.
• Designed a machine learning approach for determining tumor growth linking a unique in-vivo dataset and patient outcomes. Patients with fast growing tumors had almost a 4x higher chance of dying even when controlling.
• Patented a non-invasive approach to identifying liver fibrosis through analyzing time series ultrasound waves with varied machine learning algorithms and preprocessing.

New York, NY, US

• Developed, and productionalized, an AutoML model to predict members at high risk of avoidable hospitalizations due to sepsis. Using a wide collection of disparate features, including claims, procedures, behavioral, and.
• Created the first productionalized python model for Healthfirst, with c-level support thanks to highly intuitive visualizations and communication, which identified expecting mothers, at the earliest point, who were at.

Worldwide, OO

• Developed, and optimized, multiple models (random forests, XGBoost, etc.) combining 25 million observations and proprietary marketing, behavioral, and clinical features to predict, on both the individual (using SAS).
• Implemented end-to-end deep learning, including RNN’s and transformers, and traditional ML NLP pipelines, such as tf-idf with naïve bayes, to identify EMR based prognostic patterns which could differentiate COVID.
• Investigated temporal emergency department visits, laboratory results, and mobility data to predict both temporal and spatial features responsible for COVID outbreaks as part of the CDC surveillance effort. Used.
• Investigated a cloud based de-identification pipeline and developed helper functions to synthetically create data, score outputs, and analyze performances.
• Guided peer-reviewed publications, white papers, and conference efforts with commercial and academic partners.

Los Angeles, CA, US

• Led analysis linking single-cell morphology and genetics to predict pancreatic cancer metastasis risk.
• Consulted on statistical and survival analysis for publications

Ti:Ger Certificate, Business Administration And Management, General

Doctor Of Philosophy - Phd, Biology/Mathematics And Statistics

Master Of Science (M.S.), Biology, Bioinformatics

Bachelor'S Degree, Biomedical/Medical Engineering