Portia Murray
Senior Data And Operations Research Scientist
304-738 E 29th Ave. Vancouver
Summary
Senior Data and Operations Research Scientist, with a PhD in operations research from ETH Zurich. On Professional Services Innovation team helping a variety of businesses across different industries develop AI models to streamline their operations. Specialist in mathematical optimization, algorithms, machine learning, and I have experience in computer vision, edge computing, cloud computing, MLops, devops, data engineering, and developing ML and OR based based SaaS solutions. I am passionate about building ML pipelines as efficiently and accurately as possible. I am also passionate about clean code and good documentation.
Overview
4
4
years of professional experience
Work History
Senior Data and Operations Research Scientist
Fujitsu Intelligence Technologies Limited
9 2021 - Current
- 3 years of experience working on global SaaS offerings based on ML and optimization/operations research focused projects for business clients (e.g., Bayer, Lowes, Canon, etc.)
- Reached the level of Fujitsu Distinguished Engineer in 2024 being the youngest female in the company to receive this designation
- Specialist in computer vision algorithms for processing behavior and action detection via Fujitsu's actlyzer software.
- Specialist in algorithms, mathematical optimization including quadratic programming, binary quadratic programming, combinatorial optimization, and heuristic optimization methods
- Responsible for developing ML and optimization based Proof of Value projects for business clients in supply chain, transportation, health care, security, agriculture, field service management, and smart manufacturing industries
- Product owner and lead developer for transforming two PoC solutions into global offering beta software products. Senior developer for two additional global offerings
Data Analysis Engineer
CLEMAP AG
07.2020 - 08.2021
- Responsible for reliably delivering real time data analytics and statistical processing of real-time 24/7 high resolution (12 Hz) electricity sensor data for hundreds of customers using PyTorch, scikit-learn, Nvidia jetson, raspberry pis, Kafka, and MongoDB/NoSQL
- Machine learning algorithms for disaggregation of electrical appliances using state- of-the-art non-intrusive load monitoring techniques
- Predictive maintenance for industrial applications, anomaly detection, and demand forecasting using LSTMs (this was in 2020)
Education
Doctor of Science - Mechanical And Process Engineering
ETH Zürich
Zurich, Switzerland 04.2016 - 2020.03
Master of Science - Mechanical Engineering
Queen's University
Kingston, ON 09.2013 - 2014.12
Bachelor of Science - Mechanical Engineering
Queen's University
Kingston, ON 09.2008 - 2013.05
Skills
Operations research/mathematical optimization/graph theory
Gurobi and CPLEX (with pyomo, PuLP, gurobipy, OR-tools, networkx, OPTuna) and Fujitsu's proprietary digital annealer optimizatyion designed to run Quadratic unconstrained binary optimization
Machine learning (PyTorch, tenserflow, Keras, , hugging face, OpenCV, scikit-learn, huggingface)
Agile Project Management (Azure DevOps, Azure cloud, AWS, Linux, Docker, RestAPIs, Pipelines, Jira, etc)
Python and object oriented programming (10 years), C (6 years), R (4 years)
Verbal and communication skills (6 journal publications and 10 conference presentations)
Cloud computing (AWS, Azure, 7 years experience)
Edge computing (Nvidia jetson, Nvidia deepstream, cuda, raspberry pis)
Data processing and cleaning (7 years)
Databases (Hadoop, Databricks, SQL, NoSQL, Parquet, etc)
Computer Vision (OpenCV, yolo, pose detection, behaviour detection, Fujitsu's proprietary actlyzer)
Languages
English
Excellent
German
Very Good
Hobbies
- Formally Lead Mechanical Engineer for the Queen's Solar Design Team in the 2013 U.S. Department of Energy Solar Decathlon which won the engineering competition
- Building my own computer vision applications at home
- Sewing and reading non-fiction science
- Avid long-distance hiker/backpacker, skiier, and runner
- I am a breast cancer survivor (in remission as of last year) and am active for fundraising in that community.
Selected publications
P. Murray, J. Carmeliet, and K. Orehounig, “Multi-Objective Optimisation of Power-to-Mobility in Decentralised Multi-Energy Systems,” Energy, vol. 205, p. 117792, Aug. 2020, doi: 10.1016/j.energy.2020.117792.
2020-03 P. Murray, “The Role of Power-to-X Technologies in Decentralised Multi-Energy Systems,” Doctoral Thesis, ETH Zurich, 2020. URL: https://www.research-
collection.ethz.ch/handle/20.500.11850/403923
2020-01 P. Murray, J. Marquant, M. Niffeler, G. Mavromatidis, and K. Orehounig, “Optimal transformation strategies for buildings, neighbourhoods and districts to reach CO2 emission reduction targets,” Energy Build., vol. 207, p. 109569, Jan. 2020, doi:
10.1016/j.enbuild.2019.109569.
2018-12 P. Murray, K. Orehounig, D. Grosspietsch, and J. Carmeliet. 2018. “A Comparison of Storage Systems in Neighbourhood Decentralised Energy System Applications from 2015 to 2050.” Applied Energy 231 (December): 1285–1306.
https://doi.org/10.1016/j.apenergy.2018.08.106
Timeline
Data Analysis Engineer
CLEMAP AG
07.2020 - 08.2021
Doctor of Science - Mechanical And Process Engineering
ETH Zürich
04.2016 - 2020.03
Master of Science - Mechanical Engineering
Queen's University
09.2013 - 2014.12
Bachelor of Science - Mechanical Engineering
Queen's University
09.2008 - 2013.05
Senior Data and Operations Research Scientist
Fujitsu Intelligence Technologies Limited
9 2021 - Current
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