Camilo Lamus

AI Researcher

Austin, Texas, United States23 yrs experience
Most Likely To SwitchHighly Stable

Key Highlights

  • Ph.D. trained computational neuroscientist with diverse expertise.
  • Led significant machine learning projects at Netflix and Yahoo.
  • Innovative algorithm developer for EEG/MEG imaging techniques.
Stackforce AI infers this person is a Computational Neuroscientist specializing in Machine Learning applications in Healthcare and Streaming industries.

Contact

LinkedIn

Skills

Core Skills

Machine LearningData ScienceComputational NeuroscienceEducationHealthcareBiomedical Engineering

Other Skills

Statistical MethodologyGeneralized Additive ModelsData Pipeline DevelopmentForecastingStatistical ModelingData AnalysisModel DevelopmentUser Engagement PredictionCross-Validation TechniquesEEG/MEG AlgorithmsDynamic Multi-Task Subspace PursuitHigh-Dimensional ModelingEEG/MEG ImagingTeachingStatistics

About

Ph.D. trained computational neuroscientist with experience leading research and data analysis projects to drive business value. Experienced in building and analyzing systems using statistical, algorithmic, and mathematical modeling principles, with applications in election forecasting, brand sentiment analysis, internet streaming, advertising technology, and medical imaging. Deep expertise in machine learning, causal inference, time series, and large-scale predictive modeling.

Experience

23 yrs
Total Experience
3 yrs 4 mos
Average Tenure
7 yrs 8 mos
Current Experience

Netflix

Senior Data Scientist

Oct 2018 – Present · 7 yrs 8 mos · San Francisco Bay Area

  • Developed an experimentation pipeline and statistical methodology to test the impact of firmware changes in Netflix's content delivery network using generalized additive time series models in a difference-in-differences framework.
  • Implemented data pipeline and methodology to forecast the demand for Netflix traffic in different geographic locations.
  • Developed and implemented the data pipeline and models to estimate the effective throughput capacity of servers in Netflix's content delivery network.
Statistical MethodologyGeneralized Additive ModelsData Pipeline DevelopmentForecastingMachine LearningData Science

Yahoo

Senior Research Scientist

Aug 2016 – Oct 2018 · 2 yrs 2 mos · San Francisco Bay Area

  • Led and executed the migration of the ML component of the conversion prediction system during Yahoo's acquisition.
  • Developed and tested models to predict conversions and user engagement that leverages temporal information.
Machine LearningModel DevelopmentUser Engagement PredictionData Science

Harvard medical school

Postdoctoral Research Fellow

Oct 2015 – Jul 2016 · 9 mos · Greater Boston Area

  • Developed and tested cross-validation techniques for tensor data (space x time x trial) to optimize EEG/MEG sparse source localization algorithms.
Cross-Validation TechniquesEEG/MEG AlgorithmsComputational NeuroscienceData Science

Neuroscience statistics research laboratory, mit

3 roles

Ph.D. Candidate

Promoted

Sep 2009 – Aug 2015 · 5 yrs 11 mos · Greater Boston Area

  • Developed the Dynamic Multi-Task Subspace Pursuit algorithm to obtain sparse estimates in high-dimensional state-space models. Applied method to estimate brain activity from EEG/MEG time series data.
  • Performed theoretical analysis using tools from control theory to show that modeling brain activity as a network of dynamic units in EEG/MEG imaging improves the spatial resolution of brain activity estimates by an order of magnitude.
  • Collaborated in the development of a spatially hierarchical greedy algorithm for the EEG/MEG inverse problem, where the hierarchical component reduces correlations between regressors yielding improved source estimates.
Dynamic Multi-Task Subspace PursuitHigh-Dimensional ModelingEEG/MEG ImagingComputational NeuroscienceData Science

Teaching Fellow

Jan 2008 – Jan 2010 · 2 yrs · Greater Boston Area

  • Assisted in teaching MIT's course Statistics for Brain and Cognitive Sciences. Topics included likelihood and Bayesian techniques for parameter estimation, hypothesis testing, the linear model, ANOVA, the bootstrap, and Monte-Carlo simulations.
  • Shared responsibility for lectures, recitations, exams, homework assignments, and grades.
TeachingStatisticsEducation

Graduate Research Assistant

Sep 2007 – Aug 2009 · 1 yr 11 mos · Greater Boston Area

  • Developed an Empirical Bayes (Automatic Relevance Machine) dynamic algorithm for the EEG/MEG inverse problem using the Expectation-Maximization and Fixed-Interval Smoother algorithms. The algorithm produces spatially sparse and improved estimates.
Empirical BayesEEG/MEG Inverse ProblemComputational Neuroscience

Neuroscience statistics research laboratory, massachusetts general hospital

Research Assistant

Jul 2005 – Aug 2007 · 2 yrs 1 mo · Greater Boston Area

  • Designed and implemented state-space Kalman filtering algorithms for the magnetoencephalography inverse problem.
  • Assisted in the execution of a complex clinical study aimed at characterizing brain function under anesthesia.
Kalman FilteringClinical Study ExecutionHealthcare

Biomedical engineering group, universidad de los andes

Research Intern

Jan 2004 – Jun 2004 · 5 mos · Bogota, Colombia

  • Developed algorithms using image segmentation and flexible contour techniques to detect edges in cardiac ultrasound images. Improved measures of cardiac wall width to diagnose disease.
Image SegmentationAlgorithm DevelopmentBiomedical Engineering

Rehabilitation research group, escuela de ingeniería de antioquia

Undergraduate Researcher

Jan 2003 – Jun 2005 · 2 yrs 5 mos · Medellin, Colombia

  • Designed and constructed an intra-oral wireless mouse mounted on a dental retainer that allows patients with motor disabilities to access a computer. Implemented mouse emulator for microcontroller in assembly code.
Wireless Mouse DesignMicrocontroller ProgrammingBiomedical Engineering

Education

Massachusetts Institute of Technology

Doctor of Philosophy (Ph.D.) — Computational Neuroscience

Jan 2007 – Jan 2015

Escuela de Ingeniería de Antioquia

Bachelor’s Degree — Biomedical Engineering

Jan 2001 – Jan 2005