# Christos Alexopoulos > ai/ml @ Meta | scs ’24 @ Carnegie Mellon Location: San Francisco, California, United States Profile: https://flows.cv/christos email: calexopo@alumni.cmu.edu ## Work Experience ### AI/ML engineer @ Meta Jan 2026 – Present | San Francisco, CA Foundational AI ### Software Engineer @ Meta Jan 2024 – Present | San Francisco, California, United States Optimizing the AI/ML Analytics experience for Creators on Facebook and Instagram ### MBAn @ Massachusetts Institute of Technology Jan 2024 – Jan 2024 Declined offer of admission to the MBAn program to work at Meta ### Investment Analyst Intern @ Catalio Capital Management Jan 2024 – Jan 2024 | New York, United States Built financial models and assessed companies for potential investments ### Director of Operations @ Nucleate Jan 2024 – Jan 2024 | Pittsburgh, Pennsylvania, United States • Oversaw Nucleate’s ”Activator” incubator program and was responsible for assessing the feasibility and practicality of new ideas in life sciences (focus on LLM’s, Bioimaging, and Drug Discovery) • Tested and fine-tuned LLM’s for a potential use case in evaluating and comparing different projects • Worked with the Carnegie Mellon and UPitt Tech Transfer offices to spin off research projects ### AI/ML Intern @ Pfizer Jan 2023 – Jan 2024 | New York, New York, United States • Led a team of interns performing further analysis on the previous year’s models resulting in a first-author paper publication (https://academic.oup.com/bjd/article-abstract/190/Supplement_2/ii22/7601641) • Researched a heuristic procedure for sleep detection (SleepPy) and a PCA to extract 36 features about scratching (ScratchPy) using wearable accelerometer data from Eczema Patients and Healthy Controls (N=140) • Investigated a random forest classifier on hand gesture scratch vs. non-scratch movement detection (accuracy: 82%) ### Research Assistant at the CMU Comp Bio & Automation Lab (Dr. Kangas) @ Carnegie Mellon University Jan 2022 – Jan 2022 | Pittsburgh, Pennsylvania, United States • Developed an algorithm for predicting C. Elegans worm thrashing (moving) rate based on wet lab videos and was a lead presenter at the ”Pittsburgh Rust Belt Microbiome (RBM) Conference” • Performed multiple wet lab experiments in different bacterial environments and analyzed GO annotations of their gene expressions to figure out significant features that lead to differential thrashing • Raised Parkinson’s disease worms in predicted ”nutrient rich” environments and captured movement improvements ### Data Science Intern @ Pfizer Jan 2022 – Jan 2022 | Boston, Massachusetts, United States • Analyzed raw ground truth data (Polysomnography, Videography) and generated novel algorithmic models for testing the relationship between scratching and sleep disturbances in patients with Eczema vs. Healthy Controls (N=140) • Yielded statistically significant results leveraging a zero-inflated Poisson regression and presented to Pfizer Digital Medicine and Translational Imaging (DMTI). Got approved for a paper publication ### Data Science Intern @ intelligencia.ai Jan 2021 – Jan 2021 | New York, United States • Examined research data to match pharmaceutical drugs with chemical structures (smile and amino acid structures) • Implemented a novel string manipulation technique for creating synonyms resulting in 60% more drug matches • Explored Neural Network Techniques for predicting drug response and synergy to implement Machine Learning Models ### Data Science Volunteer @ Ministry of Digital Governance of Greece Jan 2020 – Jan 2021 | Athens, Attiki, Greece • Directed a 5-member team to track the effectiveness of the COVID-19 vaccination campaign in Greece by analyzing nationwide data and researching areas of concern, progress, and coverage (https://emvolio.gov.gr/vaccinationtracker) • Proposed strategy modifications for optimized website traffic and new data representations to increase user engagement (increased website rating by 1.5 points on a scale of 5) ### ML Engineer Intern @ DeepSea Technologies Jan 2020 – Jan 2020 | Athens, Attiki, Greece • Analyzed raw data leveraging Python (pandas, numpy, matplotlib.pyplot, seaborn) to gain familiarity with visualizing data (box plot, distribution plot, scatterplot) • Handled missing values by learning when to use dropna() and when fillna() functions based on each client’s requirements • Examined 5 prototype models based on clients' needs (linear regression, decision trees, SVM, random forest, k-means) ### Research Assistant at the Astrolavos Networking Lab (Dr. Antonakakis) @ Georgia Institute of Technology Jan 2020 – Jan 2020 | Atlanta, Georgia • Worked on expanding IP addresses from given datasets and web scraping to specify features of given IP addresses (Data Analytics / Networking team) • Gained familiarity with working on a VM VirtualBox(ssh), the concept of virtual environments(venv, pipenv), linux, terminal, and linux text editors(vim, emacs) ## Education ### Bachelor of Science - BS in School of Computer Science Carnegie Mellon University ### Bachelor of Science - BS in School of Computer Science Georgia Institute of Technology ### Doctor of Medicine - MD in Medicine National Kapodistrian University of Athens ### High School Diploma The Moraitis School ### Elementary School / Middle School / High School Hellenic American Educational Foundation Athens College - Psychico College ## Contact & Social - LinkedIn: https://linkedin.com/in/ca7 --- Source: https://flows.cv/christos JSON Resume: https://flows.cv/christos/resume.json Last updated: 2026-03-29