Christos Petridis profile photo

Christos Petridis

PhD student in CIS @ Temple

About Me

Hi there 👋

I am a 2nd year PhD student at Temple University in Philadelphia, PA. My PhD is in Computer and Information Sciences and my advisor is Prof. Zoran Obradovic. My research focuses on predictive modeling of imbalanced data. Current projects include 1) weather-related power outage prediction (in collaboration with Texas A&M) and 2) NBA lineup performance evaluation. I am also experimenting with LLMs on schema matching, attribute value extraction, and data harmonization.

Before my Ph.D., I got an Integrated Masters (5 years) in Electrical and Computer Engineering (ECE) from the University of Thessaly in Volos, Greece. I completed my thesis (and published a paper) in collaboration with Angelicoussis Group where I worked on estimating hull fouling* using machine learning and propulsion data. During my studies, I also interned at Angelicoussis Group (2023) and other software companies.

Currently, I am building Carlytics.

* Hull Fouling is the undesirable accumulation of marine organisms on submerged structures, increasing drag and fuel use.

Education

Temple University \br Center for Data Analytics and Biomedical Informatics (DABI) logo

Ph.D. in Computer and Information Sciences

Temple University
Center for Data Analytics and Biomedical Informatics (DABI)
Aug 2024 - PresentPhiladelphia, PA

Advisor: Dr. Zoran Obradovic

GPA: 3.93/4.00

Courses:
Neural ComputationMachine LearningData-Intensive and Cloud ComputingAnalysis and Modeling of Social and Information NetworksProgramming TechniquesPrinciples of Data ManagementGPU Architecture and ProgrammingKnowledge Discovery & Data Mining
Research Interests:
Applied Machine LearningGraph Neural NetworksKnowledge DiscoveryReal-world applications of machine learningKnowledge GraphsSports Analytics
University of Thessaly  logo

5-year Integrated Masters in Electrical and Computer Engineering (300 ECTS)

University of Thessaly
Sep 2019 - Jun 2024Volos, Greece

Thesis: "Detecting Hull Fouling using Machine Learning Algorithms trained on Ship Propulsion Data", advised by Dr. Michael Vassilakopoulos

GPA: 8.23/10.0 (Ranked 4th in my class, Top 10% of the academic year)

Courses:
Machine Learning for Data Science and AnalyticsNeuro-fuzzy ComputingApplied StatisticsDeep Learning and its ApplicationsData MiningAdvanced Data ManagementInformation RetrievalConcurrent ProgrammingOperating SystemsObject-Oriented ProgrammingNumerical AnalysisSignals and SystemsProbability TheoryDifferential EquationsLinear AlgebraDiscrete MathematicsComputer System Organization

Professional Experience

Temple University logo

Graduate Research Assistant

Temple University

Aug 2024 - PresentPhiladelphia, PA
  • UAV Navigation: Developing methods to predict the location and eventually the trajectory of UAVs (drones) in GPS-denied environments using visual features extracted from aerial imagery.
  • Power Outage Prediction: Working with spatiotemporal data to predict weather-related power outages and their duration.
Working with:
Dr. Zoran Obradovic
Carlytics logo

CTO & Co-Founder

Carlytics

Sep 2025 - PresentAthens, Greece
  • Building the technological infrastructure (including the backend API service, AWS cloud architecture, and database administration) for the smartest way to analyze used cars and interact with data through natural language, enabling comprehensive, data-driven insights and confident predictions for the (used) car market in Greece.
Angelicoussis Group logo

Data Science Intern

Angelicoussis Group

Jun 2023 - Sep 2023 (4 mo.)Athens, Greece
  • Developed a framework to extract text from company's documents and classify them into categories using NLP tecnhiques (fine tuned pre-trained language models like DistilBERT, XLNet etc.).
  • Performed fleet performance prediction & evaluation using data related to company's ships.
  • Performed exploratory data analysis to select the best anti-fouling hull paint examining different factors for the whole fleet.
  • Worked with the R&D team on estimation of added resistance for vessels, aiming to reduce environmental impact and improve fuel management (Integrated Master's thesis collaboration).

Software Engineer Intern

DevN (Psathas Neilos Christos Software Company)

Jul 2022 - Nov 2022 (5 mo.)Volos, Greece
  • Assisted in development of the front-end of two mobile (Android) applications using Java.
  • Collaborated with team members using version control systems such as Git to organize modifications and updates.
  • Worked with Google Firebase to manage user inputted data across the mobile applications.
  • Assisted in the backend development of a web app (API service) utilizing Node.js and Express.js.
Swollet Technologies Ltd. logo

Software Engineer Intern

Swollet Technologies Ltd.

Feb 2022 - Apr 2022 (3 mo.)Dublin, Ireland
  • Assisted in development of the front-end of two mobile (Android) applications using Java.
  • Collaborated with team members using version control systems such as Git to organize modifications and updates.
  • Worked with Google Firebase to manage user inputted data across the mobile applications.
  • Assisted in the backend development of a web app (API service) utilizing Node.js and Express.js.

Research Papers (first author)

Papers are presented in chronological order (with the most recent appearing first).

From Prior Beliefs to Lineup Truths: Bayesian Inference for Lineup Performance

Authors: Christos Petridis, Konstantinos Pelechrinis, Zoran Obradovic

Venue: under review (preprint from Research Square)

Sports AnalyticsBasketball Lineup RatingsBayesian InferenceUncertainty Quantification

A Cost-Aware Evaluation of Duration Predictions for Weather-Induced Forced Power Outages

Authors: Christos Petridis, Zoran Obradovic, Rashid Baembitov, Mladen Kezunovic

Venue: (in press) 22nd International Conference on Artificial Intelligence Applications and Innovations (AIAI 2026)

Cost-aware evaluationOrdinal classificationPower outagesResilience analyticsWeather-induced events

Lineup Regularized Adjusted Plus-Minus (L-RAPM): Basketball Lineup Ratings with Informed Priors

Authors: Christos Petridis, Konstantinos Pelechrinis

Venue: arXiv

Sports AnalyticsBasketball Lineup RatingsInformed PriorsBayesian Inference

PixelPath: Predicting UAV Trajectories in GPS-Restricted Environments Using Image Feature Extraction and Machine Learning

Authors: Christos Petridis, Abhudaya Shrivastava, Marijana Vacic, Zoran Obradovic

Venue: 21st International Conference on Artificial Intelligence Applications and Innovations (AIAI 2025)

Drone's TrajectoryFeature ExtractionMachine LearningGPS Restricted Environments

Detecting Hull Fouling using Machine Learning Algorithms trained on Ship Propulsion Data to Improve Resource Management and Increase Environmental Benefits

Won the Best Paper award in Smart Green category

Authors: Christos Petridis, Michael Vassilakopoulos

Venue: 8th International Conference on Smart Data and Smart Cities (SDSC 2024)

Ship Performance MonitoringMachine LearningHull FoulingNaval Empirical RulesEnvironment-Friendly SolutionsIntelligent Transport Systems

Teaching Experience

ECE311 Database Systems I

Teaching AssistantUniversity of Thessaly (Greece)Fall 2023

ECE326 Object Oriented Programming

Teaching AssistantUniversity of Thessaly (Greece)Spring 2023

News & Updates

Attended the North East AI Agents Day 2026 @ Jane Street's Headquaters in NYC

May 2026

Conference

The goal of this workshop is to offer a comprehensive overview of AI agents, bring ML, Systems, and HCI research communities together to share progress, discuss common problems and evaluation setups, and identify opportunities for collaboration.

Attended the North East Database Day 2026 @ UMass Boston

January 2026

Conference

The North East Database Day (NEDB Day) is an annual one-day academic and industry conference focused on database systems, data management, analytics, and related areas of data-intensive computing.

Successfully passed my PhD Qualifying Exam

January 2026

Achievement

The Qualifying Examination tests the student on the fundamentals of Computer and Information Science and the knowledge required to do research in the field. It consists of a written exam on theory and algorithms, systems, and track-specific material.

Virtually presented three papers at AIAI 2025

June 2025

Conference
  • PixelPath: Predicting UAV Trajectories in GPS-Restricted Environments Using Image Feature Extraction and Machine Learning
  • Spatiotemporal Multiplex Network Model for Predicting Forced Outage Severity in Distribution Grids
  • Autonomous Navigation in Swarm of UAVs Using Spatio Temporal Data and Constrained-Reinforcement Learning

Best Paper Award at SDSC 2024

July 2024

Award

Our paper entitled 'Detecting Hull Fouling using Machine Learning Algorithms trained on Ship Propulsion Data to Improve Resource Management and Increase Environmental Benefits' won the Best Paper Award in the Smart Green category at the 8th International Conference on Smart Data and Smart Cities (SDSC 2024).