Andre Ehrlich

About

𝔸ndre 𝔼hrlich

PhD Candidate in Statistics, Athens University of Economics & Business (AUEB), exp. 2028. MSc Statistics, AUEB, 2024. Previously, I was Data Scientist & Technical Product Manager for team of 5 at maritime shipping technology company, The Signal Group, 2019-2023. BSc in Computer Science from Northwestern University, 2019.

PhD

PhD Candidate — Athens University of Economics & Business (AUEB)

Sep 2024 – Present · Athens, Greece

  • Thesis, "On the Analysis of Biomedical Data via Functional Distributions"

  • Assess statistical and computational efficiency and extrapolation accuracy of Gaussian Processes & Neural Diffusion Processes and Gaussian Processes to model two distinct biomedical estimation tasks: Epidemic Forecasting & Survival Extrapolation.

  • Advised by Dr. Nikolaos Demiris & Dr. Petros Dellaportas.

Project 1: Time-Varying Transmission and Epidemic Viral Load Measurements

We investigate how might viral load measurements from PCR tests be used towards inferring time-varying transmissability.

  • Assess the predictive ability of age-stratified viral load data on the disease reproduction number and related transmission dynamics.
  • Assess the inclusion of PCR viral load measurements towards large-scale surveillance.
  • Model the time-varying transmission with a latent log-Gaussian Process prior within a hierarchical stochastic epidemic model.
  • Evaluate viral load data from Brazil, which has the world's largest government-run public health system serving 200M+ people.

Poster

Experience

Technical Product Manager, Advanced Algorithms — The Signal Group

Apr 2022 – Sep 2023 · Athens, Greece

  • Led a team of 5 in data-science product development; direct report to CSO & SVP.
  • Built core NLP systems for unstructured maritime data (position lists, cargo ads, fixtures, S&P, vessel specs) powering multiple tier‑1 products; 100k+ docs/day.
  • Managed 3 DSs in model building, fine‑tuning, hardening models.
  • Designed global port congestion forecasting: latent port processing speed, adaptive now/forecast wait times; supervised 2 engineers to ship API updating 4×/day (10k ports, 100k ships).
  • Client‑facing research, technical sales, onboarding with shipbrokers, hedge funds, and PMs.

Data Scientist, Natural Language Processing

Oct 2019 – Mar 2022

  • Developed explainable ML for maritime NLP (entity extraction, document parsing).
  • Scaled market‑data coverage ~1000×; real‑time inference < 5s.
  • Supported DS sprints, visited/shadowed users; contributed to product launches & OKRs.

Tech: Python, R, Linux, Vim, shell, functional programming, C++, MongoDB, Docker, Kubernetes, FastAPI.

Research Assistant — Northwestern University (AquaLab)

Jan 2019 – Jun 2019 · Greater Chicago Area, USA

Studied planetary‑scale networks & web QoE. Explored automatic webpage resource reduction (prefetching, lazy‑loading, edge caching) and evaluated integrity via MTurk and QoE metrics (PLT, TTFB, Speed Index).

  • Scaled web scraping to stratified WWW samples; AWS EC2/S3 pipelines.
  • Computed multimodal features: language, DOM structure, imagery; scaled experiments 100×.

Software Engineer Intern — Plume Design, Inc.

Jun 2018 – May 2019 · Palo Alto, CA, USA

Joined <100‑person team shortly after surpassing 1M homes. Plume applies numerical optimization, probabilistic programming, and RL to manage home Wi‑Fi.

  • IoT security ML on millions of DNS events (partially‑labeled non‑parametric methods).
  • API: security features, TDD, OOP refactors for multi‑region customers.
  • UI: diagnostics visualization; auth flows; support site redesign.

Tech: Python, R, Spark, NoSQL, Node.js, MongoDB, Mocha/Chai, Angular, D3.js, Highcharts.

Software Contributor — Texas A&M Inst of Genome Science & Society

Jul 2016 – Sep 2016 · College Station–Bryan, TX, USA

Developed gQTL, a web UI for genetic researchers to explore data and send jobs for computation of Quantiative Trait Locus (QTL) mapping on Collaborative Cross mice (DOQTL‑based).