Jane Macfarlane

Job title:

Smart Cities Director

Department:

Lead Researcher

ITS Berkeley

Smart Cities Research Center

Lawrence Berkeley National Laboratory

Bio/CV:

Jane Macfarlane, PhD holds a joint appointment at the University of California at Berkeley and Lawrence Berkeley National Laboratory where she is the Director of the Smart Cities and Sustainable Mobility Center.

Dr. Macfarlane has over 30 years of experience in high performance computing, data analytics and geospatial mapping. Macfarlane has been responsible for directing industry research groups including: Head of Research for HERE – a leader in geospatial mapping, Vice President of Process Engineering at Imara – a lithium ion battery company, and Director of Advanced Technology Planning for OnStar at General Motors – the first at-scale, telematics solution. Her research focus is on semantic analytics, big data analytics and visualization, contextualization of data streams and spatially distributed computing. She holds 8 granted patents and currently has 14 patent applications, primarily in the domain of geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota.

Research interests:

High performance computing, data analytics and geospatial mapping, Smart Cities

Role:

Faculty/Lead Researcher

Leadership

Contact

janemacfarlane@berkeley.edu

107C McLaughlin Hall

https://eta.lbl.gov/people/jane-macfarlane

Publications

Beyond Centrality: Understanding Urban Street Network Typologies Through Intersection Patterns

Kuncheria, Anu; Joan Walker; Jane Macfarlane

Preprint, 2025

Matching Technique with Authority: A Study of How Local DOTs Can Narrow the Gap between their Network Management Authority and their Analytical Capacity

Herbert-Faulkner, Rowland; Jane Macfarlane; Karen Trapenberg Frick

Research Report, 2025

All publications

Jane Macfarlane

Contact

Publications

Beyond Centrality: Understanding Urban Street Network Typologies Through Intersection Patterns

Matching Technique with Authority: A Study of How Local DOTs Can Narrow the Gap between their Network Management Authority and their Analytical Capacity

Mobiliti—A New Tool to Guide Safer, More Equitable Traffic Management Strategies

Exploring Urban Typologies Using Comprehensive Analysis of Transportation Dynamics

Evaluating the Impacts of Major Transportation Disruptions – San Francisco Bay Area Case Study

Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks

HumanLight: Incentivizing Ridesharing via Human-Centric Deep Reinforcement Learning in Traffic Signal Control

Differential Privacy in Aggregated Mobility Networks: Balancing Privacy and Utility

Mobiliti: A Digital Twin for Regional Transportation Network Design and Evaluation

Graph Pyramid Autoformer for Long- Term Traffic Forecasting

Socially-aware Evaluation Framework for Transportation

A Machine Learning Method for Predicting Traffic Signal Timing from Probe Vehicle Data

Intersense: An XGBoost Model for Traffic Regulator Identification at Intersections Through Crowdsourced GPS Data

Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction

Simulating the Impact of Dynamic Rerouting on Metropolitan-scale Traffic Systems

Differentially Private Map Matching for Mobility Trajectories

A Data-Centric Weak Supervised Learning for Highway Traffic Incident Detection

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting

Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting

Urban Traffic Simulation: Network and Demand Representation Impacts on Congestion Metrics

Mobile Device Data Analytics for Next-Generation Traffic Management

A Traffic Demand Analysis Method for Urban Air Mobility

Quasi-Dynamic Traffic Assignment using High Performance Computing

Air Space Maps

Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting

Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting

The Transforming Transportation Ecosystem — A Call to Action

When Apps Rule the Road: The Proliferation of Navigation Apps is Causing Traffic Chaos. It's time to Restore Order

Your Navigation App Is Making Traffic Unmanageable - IEEE Spectrum

Data-Driven Energy Use Estimation in Large Scale Transportation Networks

Designing for Mode Shift Opportunity with Metropolitan Scale Simulation

Mobiliti: Scalable Transportation Simulation Using High-Performance Parallel Computing

Method and Apparatus for Next Token Prediction Based on Previously Observed Tokens

Temporal Sampling Constraints for GeoSpatial Path Reconstruction in a Transportation Network

Method and Apparatus for Providing Semantic-Free Traffic Prediction