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Software Development Manager at AWS.
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Assessing your cultural and operational fit
Engineering leader at the intersection of AI and security. With deep technical expertise in distributed systems, big data, and cloud computing, I lead teams that apply machine learning and statistical methods to detect threats at AWS scale. My current focus is on solving the emerging AI security problems that stand in the way of enterprise adoption.
Michigan Technological University
PhD, Electrical Engineering
January 1, 2005 – January 1, 2009
Wuhan University
BS, Electrical Engineering
January 1, 2001 – January 1, 2005
Amazon Web Services (AWS)
Software Development Manager
November 1, 2020 – Present
MathWorks
Software Engineering Manager
April 1, 2018 – November 1, 2020
MathWorks
Team Lead
April 1, 2016 – April 1, 2018
MathWorks
Senior Statistics and Machine Learning Software Developer
May 1, 2015 – April 1, 2016
MathWorks
Statistics Software Developer
October 1, 2011 – May 1, 2015
Thorlabs
Application Engineer
May 1, 2010 – October 1, 2011
Newton, New Jersey, United States
Michigan Technological University
Lecturer and Post Doc
December 1, 2009 – May 1, 2010
MATLAB Regression Learner App
April 1, 2018 – November 1, 2020
Manage the team that develops the Regression Learner App. Interactively train, validate, and tune regression models. Choose among various algorithms to train and validate regression models. After training multiple models, compare their validation errors side-by-side, and then choose the best model.
MATLAB Classification Learner App
April 1, 2018 – November 1, 2020
Manage the team that develops the Classification Learner App. The Classification Learner app trains models to classify data. Using this app, you can explore supervised machine learning using various classifiers. You can explore your data, select features, specify validation schemes, train models, and assess results. You can perform automated training to search for the best classification model type, including decision trees, discriminant analysis, support vector machines, logistic regression, nearest neighbors, naive Bayes, and ensemble classification.
Statistics and Machine Learning with Big Data Using Tall Arrays
April 1, 2015 – April 1, 2018
Lead the research and development of statistics and machine learning algorithms for out-of-memory big data
MATLAB Tall Array and Tall Table big data processing framework
April 1, 2014 – April 1, 2016
Tall arrays provide a way to work with data backed by a MATLAB datastore that can have millions or billions of rows. Since the data is not loaded into memory all at once, tall arrays can be arbitrarily large in the first dimension (that is, they can have any number of rows). Instead of writing special code that takes into account the huge size of the data, such as with techniques like MapReduce, tall arrays let you work with large data sets in an intuitive manner that is similar to the way you would work with in-memory MATLAB® arrays. Many core operators and functions work the same with tall arrays as they do with in-memory arrays including statistics and machine learning functions.
Unified mapreduce framework for large-scale data processing
April 1, 2014 – April 1, 2016
A big data processing framework in MATLAB for analyzing data sets that do not fit in memory
MATLAB datastore to read large collections of data
April 1, 2014 – April 1, 2016
A datastore allows you to read and process data stored in multiple files on a disk, a remote location, or a database as a single entity. If the data is too large to fit in memory, you can manage the incremental import of data, create a tall array to work with the data, or use the datastore as an input to mapreduce for further processing.
Cultural Fit Analysis
The candidate has a strong background in both academic research (PhD, Lecturer) and industry (MathWorks, AWS), demonstrating adaptability. The progression from individual contributor to team lead and manager roles at MathWorks and then to a Software Development Manager at AWS shows a career trajectory focused on leadership and impact. The projects are highly technical and focused on data processing and machine learning, aligning well with a data-driven culture. However, the projects listed are primarily personal and heavily focused on MATLAB, which might indicate a specific tool preference. The target role is 'Data Analyst', but the candidate's recent experience is heavily skewed towards management and software development, which might represent a slight mismatch if the Data Analyst role is purely individual contributor focused without leadership responsibilities. The breadth of technologies outside of MATLAB is not explicitly detailed in the project descriptions.
Soft Skills & Operational Fit
The candidate's experience as a Software Development Manager at AWS and Software Engineering Manager at MathWorks suggests strong leadership, team management, and strategic planning skills. The descriptions of launching complex systems and scaling teams indicate a proactive and results-oriented approach. The focus on cybersecurity threat detection and anomaly detection implies strong analytical thinking and problem-solving under pressure. However, specific details on communication style, stress handling, or direct team collaboration are not explicitly provided in the given data.