Associate Professor (part-time)2019 - PRESENTGeorge Washington University
Technologies: Machine Learning, Artificial Intelligence (AI), Neural Networks, Data Analysis, Keras, Simulations, Agent-based Modeling, Python, NumPy, TensorFlow, Pandas, SciPy, Plotly, NLTK, Sklearn, Regex, System Architecture, Text Categorization, Behavioral Science, Data Science, Databases
- Designed and taught a 2-course sequence on programming for analytics and machine learning and a course on simulation modeling for systems thinking.
- Ensured my students, who come from diverse backgrounds and little to no programming experience, leave with a comprehension of data wrangling, classic analytics methods, and statistical machine learning through my Programming for Analytics course.
- Taught the principles of neural networks and their applications in NLP, computer vision, time-series analysis, and algorithmic trading in this "advanced beginner" course, Neural Networks and Deep Learning.
- Taught various modeling methods from systems dynamics and differential equation methods to microsimulation, agent-based modeling, and large-scale mixed-method simulation models in the advanced course, Simulation Modeling.
CTO/Chief Scientist2013 - PRESENTOpen Health Network
- Led the creation and deployment of a system for practitioners to upload videos to a secure server, analyze content with a neural network, and extract relevant data. The major medical center analyzes >5,000 hours of video psychotherapy sessions.
- Created a first-in-its class conversational interface (chatbot) that administers a 12-session motivational interviewing and cognitive behavioral therapy program to assist patients in a smoking cessation program.
- Conducted extensive analysis of randomized clinical trials, analyzed the data using neural network text mining, and summarized using natural language generation to present to the client for a pharmaceutical co. requiring an analysis of its strategy.
- Designed a set of algorithms analyzing cross-provider linkage patterns in claims that correspond to fraudulent transactions in opioid prescriptions and durable health equipment, estimate the risk of fraud, and refer cases to investigators.
- Supervised a team of five developers and two data scientists. Ran an Agile and Kanban workplace with a distributed team in four different time zones.
Data Science Consultant2015 - 2016Global Consumer Packaged Goods Company (under NDA)
Technologies: Consumer Packaged Goods (CPG), Demand Forecasting, Artificial Intelligence (AI), Recurrent Neural Networks, Time Series Analysis, Geospatial Data, Geospatial Analytics, Keras, PostgreSQL, Linux, Python, NumPy, TensorFlow, Pandas, SciPy, Plotly, NLTK, Sklearn, System Architecture, Text Categorization, Data Science, Architecture, Databases, REST, AWS
- Served as a part of a 3-member data science team; analyzed CPG supply and demand data across the Latin American market. Utilized hyper-local data on weather, holidays, sports events and traffic to build comprehensive demand forecasting tool.
- Created a detailed map of product needs, demand, complementarity, and substitution using geospatial and time-series analysis. The resulting tool was used to pre-position supply trucks to optimize product sell-through and minimize retailer inventory.
- Analyzed the impact of signage and other promotional programs, as well as spill-over effects on competitive products.
- Developed and deployed the system that the client then spun off into a separate company that Salesforce has acquired.
Text Analysis and NLP Data Scientist2010 - 2013Real Capital Analytics
- Took over an antiquated REGEX-based news analysis and filtering system; revamped using emerging ML-based text analysis and classification tools. Extracted structured data from unstructured text.
- Reduced the time to analyze, process, and enter into the DB a data item from 5 min to 30 seconds with the resulting tool. Reduced the amount of rejected and irrelevant data from 60% in the legacy system to 24% in ML-based systems.
- Processed news items automatically linked to GIS, resulting in a real-time understanding of newsworthy developments in a specific geographical area.
- Reduced labor costs in the information processing team by approx. $4 million in the first year of system deployment while reducing the data processing backlog from about one week to zero.
- Built ML capabilities the client used as key IP in their merger, creating approx $10-15 million of additional value to investors.
Assistant Professor/Computational and Data Science2005 - 2012George Mason University
Technologies: Simulation modeling, agent based models, Machine Learning, Artificial Intelligence (AI), Simulations, Agent-based Modeling, Python, NumPy, System Architecture, Text Categorization, Behavioral Science, Data Science, Databases
- Developed five courses for my department, including Complex Systems 101, Social Network Analysis, Complex System Analysis and Modeling, Modeling of Human Behavior and Organizations, and Machine Learning for Simulation Modeling.
- Authored a textbook on social network analysis; topped at #48 on Amazon's data science best-seller list. https://books.google.com/books/about/Social_Network_Analysis_for_Startups.html?id=Tn-L5WoCeygC.
- Oversaw graduate school admissions process for interdisciplinary doctoral, master's, and certificate programs.
- Conducted research in the use of simulation modeling to understand the behavior of complex organizations and social systems. Published over 50 peer-reviewed papers on various topics in the area.
- Supervised a group of graduate students on multiple NSF and DARPA-funded research efforts.