Elena Popovici, Ph.D.

Data Science

Strategy and Execution

Based in Vancouver, BC, Canada


lýno̱ = to solve

-metry = art or science of measuring

About me

Computer Science PhD with 15+ years of industry experience managing science-driven projects using algorithms to solve complex, real-world business and engineering problems across a wide variety of domains.  Focused on making a difference in the sustainable energy sector and addressing environmental and social issues.

Scientific Expertise

  • Data Science
  • Machine Learning
  • Visualization
  • Search & Optimization
  • Evolutionary AI
  • Modeling and Simulation
  • Graph/Network Analysis
  • Text Mining
  • Algorithms, Math, Statistics


  • Energy Management
  • Naval Engineering
  • Fisheries
  • Healthcare
  • Pharma
  • Insurance
  • Advertising
  • & more


  • Applied Science
  • Research
  • Agile Software Development
  • Project Management
  • Cross-functional Team Leadership
  • Mentoring
  • Client Management
  • Consulting


  • Java, Scala, C++, Lisp
  • Python, R, Excel
  • SQL, InfluxDB
  • Shell scripting
  • git, SVN
  • Gephi, NetLogo
  • Jira, Pivotal Tracker
  • & more

Primary Professional Experience

Jan 2020 / August 2020 - Present, Head of Data Science / CTO

AWESENSE INC. – Vancouver, BC, Canada

Helping build a geo-spatial and time-series platform for digital energy to enable  the decarbonization of electricity grids

Jan 2020 - Present, Executive in Residence (EiR)


Advising clean tech startups on their data and computational strategy

Mar 2018 - Nov 2019, Senior Computer Scientist, Project Lead


Sample Projects

Forecasting home electricity consumption and generation

  • Applied supervised machine learning algorithms (neural nets and more) using time series of sensor and weather data to predict an individual home's electricity consumption and solar generation in the coming hours/days
  • Helped design and implement the software architecture to support data retrieval and processing, model training, prediction and evaluation, and whole system performance monitoring
  • Applied unsupervised machine learning algorithms (clustering) to consumption time series data, to facilitate change-point detection as well as to help determine which features to include in forecasting models

Storage optimization

  • Designed and evaluated custom heuristic optimization algorithms for controlling a battery so as to reduce electricity bills in different utility tariff regimens (time of use, demand charge)

2006-2017, Senior Complexity Scientist, Project & Client Manager


General Responsibilities

  • Work independently or as part of a team on client and internal R&D projects
  • Act as technical lead for small-to-medium teams
  • Participate in client meetings, learn about the client's domain, build common ground, and help identify the client's needs
  • Scope out project requirements, time estimates and budgets
  • Identify relevant computational, mathematical and statistical techniques
  • Identify potential data sources, from the client or public
  • Develop end-to-end solutions: build models, incorporate data, design and implement algorithms, run simulations, analyze and visualize results
  • Interact with the client on an ongoing basis, building their trust and understanding of the solution
  • Present results of complex analyses in simple actionable terms to non-technical business audiences
  • Produce technical documentation
  • Provide technical support to the business development and sales team
  • Conduct research and development for the generation of intellectual property suitable for patenting, licensing or sales
  • Keep up to date with the state-of-the-art in relevant scientific fields
  • Recruit scientists and software developers (review resumes, conduct interviews)
  • Mentor junior scientists

Sample Projects

Computational Design of Resilient Water-Distribution Networks

  • Developed and applied evolutionary and co-evolutionary algorithms to automate the placement of smart-valves in ship-based piping networks, so as to optimize damage/fault resilience both on average and in the worst case
  • Designed and implemented network segmentation algorithms and control algorithms delivering the perfect response to a given damage
  • Conducted theoretical research into co-optimization algorithms (see Publications page)
  • To be transitioned from applied research to technology development by the US Office of Naval Research
  • Used genetic programming to automate the design of fault (leak) detection algorithms based on flow meter (FM) sensor data

Healthcare Data Analysis and Visualization

  • Conducted statistical analysis of proprietary patient data to identify potential drivers of cancer survivability (Client: large international pharmaceuticals company)
  • Conducted exploratory data analysis of US Medicare-released data to gain insights into hospital usage
  • Developed interactive visualizations for navigating the data
  • Talk videos - part 1 & part 2

Text Visualization

  • Co-developed algorithms for multi-source text analysis and visualization, including extraction of salient features in the form of a network of words, detection of network clusters, and computation of network layout for display
  • Co-author on US patent – Technology was spun off as a start-up company (Infomous.com), whose clients include The Economist and Washington Post, and whose dynamic word “clouds” have been featured on blogs, news and social network sites all over the world

Blog-Network Analysis

  • Performed connectivity analysis and text mining for a large internet network of food-related blogs
  • Implemented network clustering algorithms to detect communities of blogs and visualized results
  • Used by large food manufacturing company to assess online opinion of their brand, and which blogs are most influential

Personnel Planning

  • Developed fast constraint optimization heuristics for grouping work tasks on Navy ships in a way that minimizes costs while improving schedule desirability for sailors
  • Compared to previous algorithms, reduced runtime by as much as two orders of magnitude while also improving solution quality

Fisheries Supply Chain Modeling

  • Co-developed open-source agent-based model and web-based simulation of the operation of a value chain moving tuna from a small-scale fishery all the way to consumers, through intermediaries and markets
  • Analyzed the impact of hypothetical interventions, to assist the Rockefeller Foundation with decision-making for their initiatives in support of sustainability of fish stocks and maintaining livelihoods of traditional tuna fishers

Strategic Portfolio Planning

  • Co-developed agent-based simulation of the operation of a drug-development pipeline
  • Developed evolutionary algorithms to automate the search for optimal portfolio strategies (fiscal, resource acquisition and allocation, R&D, portfolio management, deal making)
  • Designed and recorded screencast tutorials for the software
  • Resulting tool is actively used by large pharmaceutical company for long-range planning

Market Access

  • Co-developed simulation of the process whereby typical decision committees at private health-insurance companies select drugs to cover
  • Developed evolutionary algorithms to calibrate model parameters using historic data
  • Resulting tool is actively used by large drug-development company to predict the likelihood that a given drug in early clinical testing stages will be covered, once on the market, by various health-insurance companies

Route Optimization

  • Developed dynamic programming algorithm for optimizing traversal order of street segments on a postal route
  • Incorporated in tool actively used for route design by the French postal system

Fuel Pricing

  • Performed statistical analysis to investigate drivers of competitor pricing strategies
  • Developed evolutionary algorithms to predict unusual price movement
  • Client: large international petroleum company

Financing Term-sheet Optimization

  • Developed evolutionary algorithms to search for term-sheets optimizing fairness of economic outcomes (e.g. capitalization tables) under multiple scenarios (e.g. IPO, liquidation)
  • Incorporated in tool built in collaboration with The Law Lab at Harvard University

Contextual Advertising

  • Developed software architecture and information retrieval algorithms to match relevant ads from a database to words in a network-based text visualization (see above)

Consumer Decision-Making

  • Co-developed simulation of how US seniors choose a private health-insurance plan, to help insurance companies drive plan design by predicted market share
  • Implemented evolutionary algorithms to calibrate model parameters using historic data
  • Resulting tool sold to large US health-insurance company (Humana)

Professional Accomplishments

  • Over fifteen peer-reviewed publications, including ones that were nominated for and received Best Paper awards; continued to publish while working in the industry
  • Generated Intellectual Property material that was patented in the US and Europe
  • Co-organizing the Data Science for Social Good talk series
  • Volunteering with the BC Sustainable Energy Association
  • Competed in and won awards at various algorithmic and programming competitions (e.g. ACM, Topcoder), and was awarded multiple merit scholarships during academic studies (complete list available upon request)
  • Developed and delivered technical tutorials at conferences, and invited talks for various groups or events (see News page for recent activities, complete list available upon request)
  • Actively reviewing for journals and conferences
  • Served as Local Chair for the 2014 Genetic and Evolutionary Computation Conference, held in Vancouver, BC, Canada
  • Actively continuing self-education on both technical topics and soft skills through online courses (e.g. on Coursera), conference attendance, professional associations and local professional meetup groups



PhD in Computer Science, 2006 (GPA 3.95; Dissertation: An Analysis of Two-Population Coevolutionary Computation; Advisor: Kenneth De Jong)

AL. I. CUZA UNIVERSITY – Iasi, Romania

MS in Computer Science, 2000 (GPA 3.66; Thesis: A Social Mutation Operator for Genetic Algorithms; Advisor: Henri Luchian)

BS in Computer Science, 1999 (GPA 3.97; Thesis: Unsupervised Matrix Cross-clustering Using Genetic Algorithms; Advisor: Henri Luchian)

Other Professional Experience

2002–2006 (except Fall 2003), Research Assistant

EVOLUTIONARY COMPUTATION LAB, Computer Science Department, George Mason University – Fairfax, VA, USA

ADAPTIVE SYSTEMS LABORATORY, Krasnow Institute for Advanced Study, George Mason University – Fairfax, VA, USA

  • Conducted research and development of various agent-based modeling and evolutionary computation techniques; applications included: finding the most damaging release point for hazardous materials in a given environment (optimization around a computational fluid dynamics simulation), modeling network intrusion and counter-measures, modeling spread of disease through the human body

2003, Software Engineer R&D


  • Developed protocol specifications and UI components for the company's software product, one of the first media players with copyrighted-content protection

2003, Computer Instructor


  • Taught a one-month intensive introductory course to Java programming

2001–2002, Teaching Assistant

COMPUTER SCIENCE DEPARTMENT, George Mason University – Fairfax, VA, USA

  • Held student office hours and graded homework for the graduate level Artificial Intelligence class

2000–2001, Research Assistant

LEARNING AGENTS LAB, George Mason University – Fairfax, VA, USA

  • Developed modules within the lab's software platform, an ontology-based learning agent called Disciple. Used Lisp and Java

1999–2000, Software Developer

ARTINFO SRL – Iasi, Romania

  • Contributed to the development of the company's main software product, IdealeNT, an enterprise resource-management tool with a client-server architecture and a back-end database with over 700 tables. Used C++ and SQL Server