Christos Petridis profile photo

Christos Petridis

PhD student in CIS @ Temple

About Me

I am a 3rd 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 whether Large Language Models (LLMs) can interpret real-world environmental data, such as weather conditions, well enough to serve as reliable components in predictive pipelines compared to machine learning. In the same area, I assess how LLMs perceive verbal probability expressions such as "possibly" and "unlikely" compared to human baselines. On the data management side, I work with Prof. Eduard Dragut on dataset cartography, making the diagnostics from data maps cheap enough to be practical at scale.

📌 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 (thesis collaboration 2023) and other software companies.

📌 I've been fortunate to collaborate with Prof. Konstantinos Pelechrinis (Pitt) and Prof. Mladen Kezunovic (Texas A&M).

* 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 - Present•Philadelphia, PA

Advisor: Dr. Zoran Obradovic

GPA: 3.93/4.00

University of Thessaly  logo

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

University of Thessaly
Sep 2019 - Jun 2024•Volos, 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)

Professional Experience

Temple University logo

Graduate Research & Teaching Assistant

Temple University

Aug 2024 - Present•Philadelphia, PA
Working with:
Dr. Zoran Obradovic
Angelicoussis Group logo

Data Science Research Intern

Angelicoussis Group

Jun 2023 - Sep 2023 (4 mo.)•Athens, Greece
👨‍💻

Software Engineer Intern

DevN (Psathas Neilos Christos Software Company)

Jul 2022 - Nov 2022 (5 mo.)•Volos, Greece
Swollet Technologies Ltd. logo

Software Engineer Intern

Swollet Technologies Ltd.

Feb 2022 - Apr 2022 (3 mo.)•Dublin, Ireland

Research Papers (first author)

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

Evaluating Large Language Models for Forced Outage Risk Prediction: Benefits and Comparison to Machine Learning

Authors: Christos Petridis, Zoran Obradovic, Mladen Kezunovic

Venue: (in press) 60th Hawaii International Conference on System Sciences, (HICSS 2027)

Forced Outage PredictionLarge Language ModelsZero-Shot ClassificationWeather-Driven OutagesDistribution Grid Management

How Unlikely Is "Unlikely"? Assessing Verbal Probability Perception Across Large Language Models

Authors: Christos Petridis, Konstantinos Pelechrinis, Zoran Obradovic

Venue: arXiv

Probability PerceptionLarge Language Models

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

Authors: Christos Petridis, Konstantinos Pelechrinis, Zoran Obradovic

Venue: under review

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: 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

CIS 2109 Database Management Systems

Teaching Assistant•Temple University (USA)•Fall 2026

ECE 311 Database Systems I

Teaching Assistant•University of Thessaly (Greece)•Fall 2023

ECE 326 Object Oriented Programming

Teaching Assistant•University of Thessaly (Greece)•Spring 2023

News & Updates

Paper accepted at HICSS

Aug 2026

Publication

Excited to share that our paper "Evaluating Large Language Models for Forced Outage Risk Prediction: Benefits and Comparison to Machine Learning" has been accepted at the 60th Hawaii International Conference on System Sciences (HICSS).

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).