About Me

A selfie of Emily

Hi there! I'm Emily F. Gorcenski, and this is my personal website. Before going further, please note that I am highly opinionated, but those strong opinions belong only to me and I am not speaking for my employer or any other organization unless stated otherwise. I am a data scientist by profession, a mathematician and engineer by training, and an activist by passion. I am somewhat of a digital nomad, though I am from Charlottesville, and the events of 2017 in Charlottesville have strongly informed my activism. On this page, you'll find a brief CV, bio, and other information that you might care about or need.

Contact Information

Short Autobiography

I find it difficult sometimes to write about myself, because even after all this time I don’t know what identity is. Certainly, there are many ways I can identify, because there are many things that I am. I am a data scientist, by profession. I am an engineer, by training. I am an activist, by passion. I am a mathematician, by degree. I am a queer transgender woman, by existence. I am an immigrant, by necessity. In the end, though, those are words and labels to describe what I do, and I try to live in such a way that the things that I do are more interesting than the things that I am. Perhaps I should discuss that.

I work as a data scientist, presently for ThoughtWorks Deutschland (don’t bother complaining to them if you don’t like my opinions, as the opinions I share here are mine alone). As a data scientist and consultant, I advise and educate clients on ways to make use of data in ways that bring value. I build data-driven systems. And I try to build them ethically, seeking problems worth solving to make the world better. If you’d like to see some of my work on technology ethics, see the conference link below, or just follow this blog.

My background in data science comes from perhaps an ununsual place. I am an engineer by training. I studied Aeronautical and Mechanical engineering at Rensselaer (though my degree is in Applied and Computation Mathematics). I worked for almost a decade as a research engineer, working in signal processing and control theory. Yes, much of this work was funded by the Department of Defense, a fact I neither hide nor take pride in. I no longer work for Defense-funded projects and have not in some time.

It used to be hard to be educated in the aerospace industry and not work in defense. But my actual degree, for reasons I will not belabor here, is in Mathematics. Specifically, I’ve studied uncertainty quantification and dynamical systems. I loved math more than I loved engineering, and so switched my degree at the last minute to finish while I still had some student aid. I deeply love mathematics, so much that I have tattoos of abstract mathematical ideas (ask me sometime about FizzBuzz).

I’m also, however, a researcher. My particular skillset is what is sometimes called technology transition, which is the awkward space between fundamental research and production engineering, a space which requires one to understand and speak many technical languages. It’s my skills as a researcher that have made me effective at data science. It’s also what’s made me effective as an activist.

When neo-Nazis and white supremacists came to my home of Charlottesville, Virginia in 2017, I knew I could not sit by and watch them bring their violence and hate to those streets unopposed. I needed to fight back, and the best way I know how to fight is to use information and truth as a weapon. So I did just that, first by trying to shut the rally down, then by showing the unfiltered truth of their hate, and then by holding them accountable to their violence by exposing them, tracking their crimes, and shining sunlight on their bigotry.

This work has continued in a quasi-professional context. I sit on the advisory boards of the Prosecution Project at Miami University in Ohio, and on the Youth Equity and Sexuality Laboratory at Suffolk University, two research labs studying extremist violence. I have co-written a book chapter on lessons that can be learned from activism in the technology space and vice-versa. I have been consulted as an expert on several issues regarding far-right violence internationally.

That work has not been without a cost. As a transgender woman, my identity makes me vulnerable to bigotry. And as someone who has metaphorically punched their movement in the face (quite hard, I’d like to think), this has made me a target. I experience regular threats, and my home has been threatened enough that I made the decision, for personal safety and mental health reasons, to emigrate to Berlin, Germany, where I now live.

Berlin has given me the space to find my creative energy once again. I poured some of that energy into First Vigil, a database of recent and ongoing court-cases involving right-wing extremist violence and hate crimes. For that work, I’ve been given accolades; among them, I was named as one of 2018’s most influential feminists by Bitch Magazine.

Despite the high stakes of the work I’ve done, I feel privileged nevertheless as it has allowed me to understand my purpose and what drives me. I want to create a world where I can be at peace, and to create that world with the talents I have, I see two things that I can do: by helping make technology good, and by helping to make white supremacy and bigotry untenable with every fiber of my being. And in the end, I hope I can tell a good story from it all.

Thanks for reading. May we move ever foward, together.

Technical Conference Bio

Emily has over ten years of experience in scientific computing and engineering research and development. She has a background in mathematical analysis, with a focus on probability theory and numerical analysis. She is currently working in Python, though she has a background that includes C#/.Net, Unity3D, SQL, and MATLAB. In addition, she has experience in statistics and experimental design, and has served as Principal Investigator in clinical research projects. Emily was also named as one of 2018’s most influential feminists by Bitch Magazine for her data activism shining a light on far-right violence with her First Vigil project.

Curriculum Vitae


Lead Consultant, Data Scientist: ThoughtWorks Deutschland GmbH, Berlin, Germany
August 2018 — Present

ThoughtWorks is a global technology consultancy that helps its clients excel at software development. With offices in 14 countries and over 5,500 employees, ThoughtWorks is a recognized leader in software engineering, Agile, and other technology best practices.

Emily is a Lead Consultant and Data Scientist. In her role, she advises clients in a variety of technology development efforts in the data science space. These efforts can include: designing effective data platforms to empower faster data analytics and data science, data research and exploration, and implementing agile workflows and continuous delivery for machine learning applications. Emily’s unique experience in technology transition means she is well-suited for both advisory and delivery roles in the data science space. Some of her accomplishments with [Redacted] include:

  • Designing and building a location analytics platform for land use analysis;
  • Designing workshops for teaching continuous delivery and agile development methodologies in a data science space;
  • Training project and product managers on effective ways to utilize data and data scientists on cross-functional teams.

Senior Data Scientist: Simple, Portland, USA
September 2016 — May 2017

Simple Financial Technical Corporation is a personal finance company acting as a technology-first organization. The core product is a consumer checking account with an app-first design. The company offered web, iOS, Android, and mobile-web apps to allow customers to manage finances, interact with support, and plan budgets. The company operated no physical branches.

Emily worked as Senior Data Scientist, where she analyzed customer behavior, including app usage spending/saving behavior, customer satisfaction, and fraud detection and mitigation. Additionally, she served as mentor for six other data scientists with varying levels of experience and skills. Key accomplishments include:

  • Building a generalized genetic algorithm framework for optimizing risk models;
  • Implementing and maintaining a knowledge repository for insight documentation;
  • Developing and implementing an improved fraud-detection model with rapid deployment needs;
  • Designing experiments to quantify customer behavior and assess feature feasibility.

Research Engineer: Barron Associates, Inc., Charlottesville, USA
April 2008 — May 2016

Barron Associates, Inc. is a small research engineering firm specializing in real-time control systems, simulation, and mathematical modeling in the aerospace, automotive, and biotechnology fields. Predominantly working in technology transition—the complex space between core research and technology implementation—Barron Associates helped move technologies and methodologies from university laboratories to production environments within industry and government.

Emily served Barron Associates as a Research Engineer. Using her background in computational mathematics, she worked on interdisciplinary teams with world-class domain experts to help demonstrate and prove complex algorithms and ideas in real-world environments. In addition, she wrote winning grant proposals for new work, led multi-center teams, and presented the company’s work and vision before industry and academic professionals. A sample of her projects is presented below.

Intelligent Prognostics for Vehicle Maintenance Planning

Objective: Using engine, powertrain, and vehicle telemetry, dynamically detect degraded performance to schedule preventative maintenance and allow for greater variability in maintenance schedules.

Approach: Using MATLAB and Simulink, developed a high-fidelity model of engine and vehicle dynamics. Applied modeling approach to large-scale real-world datasets to identify performance and detect failures. Used inverse methods to correct for sensor bias and noise. Applied Kalman filtering techniques for fault detection.

Neural Networks for Low-Resolution Image Classification

Objective: Develop a method for identifying humans in variable sea-state conditions using low-resolution radar images.

Approach: With the requirements of running on real-time embedded hardware, developed a feature extraction pipeline based on Hough Transformations to extract image data. Built a multiclass classification algorithm using polynomial neural networks. Trained and validated data in a real-world environment using a functional radar platform.

Wearable Health Tracker for Lower-Limb Amputees

Objective: Develop a wearable IoT health monitor for lower-Limb combat amputees capable of assessing physical health in people with complex medical needs.

Approach: Designed algorithms for a photoplethysmography-based health monitor capable of being embedded within gel prosthetics linings. Ensured algorithms would be functional in atypical conditions e.g. tissue ossification, where commercial health trackers generally fail.

Image Analysis for Automated Corrosion Mapping

Objective: Develop software capable of identifying corrosion pits in laser profilometry scans of nickel-based superalloys corroded at high temperature with sulfur-based salts.

Approach: Used regularization methods to detect pits while preserving surface geometries where convolutional methods would typically fail. Built algorithms for automating volumetric measurement and classifying inclusions to detect conditions that would lead to adverse stress concentrations. Designed software package to output results to commercially-available failure prediction tools.

  • Programming: Python, C#, MATLAB, FORTRAN, C, SQL
  • Python-specific Competencies: Python 3.x, jupyter, pandas, numpy/scipy, keras
  • Cloud Competencies: Azure (AKS, Storage), AWS (Elastic Beanstalk, Route53, S3, Redshift, Lambda), Google Cloud (Firebase, Cloud Storage, Load Balancer, Kubernetes Engine, Compute Engine, Cloud Functions)
  • Tools: Visual Studio .NET/VSCode, Anaconda, git, Jira, Trac, Trello, Chartio, Tableau
  • English: Native Fluency (American)
  • German: Learning (approximately A2)
  • Spanish: Reading/writing competency, some conversational
  • Thai: Learning
  • Turkish: Learning
  • BS Mathematics (applied and computational), 2007, Rensselaer Polytechnic Institute, Troy, NY.
  • MA (In Progress) Mathematics (analysis), University of Virginia, Charlottesville, VA.
Selected Conferences (forthcoming events in italics)
  • Øredev 2019, “Revisiting the Ethics of the Consumer IoT,” November 2019, Malmö
  • XConf EU 2019, “When Data Meets Device: Looking forward to a data-driven physical world,” July 2019, Manchester & Barcelona
  • GOTO Amsterdam, “Continuous Intelligence: Data Science, Hypothesis Driven Development, and Continuous Delivery,” workshop, with Emma Grasmeder (ThoughtWorks), June 2019, Amsterdam
  • MiXiT Conf, Beyond Ethics (keynote) May 2019, Lyon
  • Strata, “Continuous Intelligence: Keeping your AI Application in Production,” with Arif Wider (ThoughtWorks), May 2019, London
  • “Facing White Supremacy after Brexit: Politics as Usual?,” panel hosted by the Mile End Institute, April 2019, London
  • SRECon EMEA 2018, “SRE for Good: Engineering Intersections between Operations and Social Activism” (keynote), with Liz Fong-Jones (Google), August 2018, Düsseldorf
  • Mozfest 2017, “Debunking Fake News and Fake Science” (keynote), with Sarah Jeong (New York Times), October 2017, London https://www.youtube.com/watch?v=TXL4SfXH5zM
  • Open Source Bridge 2017, “Fake Science: Sad!” (keynote), June 2017, Portland
  • PyData Berlin 2018, “Going Full Stack with Data Science,” July 2018, Berlin https://www.youtube.com/watch?v=huqpXMNFD54
  • PyData Berlin 2017, “Polynomial Chaos, a Technique for Modeling Uncertainty,” July 2017, Berlin https://www.youtube.com/watch?v=Z-Qio-n6yPc
  • JSConfEU 2017, “The Ethics of the Internet of Things,” May 2017, Berlin https://www.youtube.com/watch?v=xLL7Fo_em2E