Graph-Oriented AppLications Lab in CS@RIT

Advancing knowledge graphs, graph-based data systems, and data education.

Our Research

Knowledge Graph Analysis

Rule mining, link prediction, and graph-based analytics in large knowledge graphs.

Knowledge Graph Evaluation

Robust evaluation methods, information retrieval metrics, and estimation techniques.

Graph Systems and Education

Efficient (sub)graph processing, reasoning systems, and data science and AI education.

News

Apr 2026 - RIT Graduate Showcase
Beshani, Diba and Lydia presented posters at the RIT Graduate Showcase.
Feb 2026 - New poster in SIGCSE
A new poster was accepted at the ACM Technical Symposium on Computer Science Education: A Taste of Formal Methods for Computer Science Students using Jupyter Notebooks. Check also our repository to get a taste of formal methods in STEM.
Aug 2025 - Two papers in KDD (satellite events)
Beshani presented her PhD plans at the PhD Consortium: Towards a Unified Evaluation Protocol for Link Prediction Interpretation over Knowledge Graphs. Cara presented her undergrad research at the Undergraduate and Master's Consortium: Find the culprit: query-driven tracing of cybersecurity vulnerabilities using Python's PyPI dependencies.
Aug 2024 - Two new grants
Thanks to the NSF for supporting our research! Check out our CORE project and our FMiTF project.
March 2024 - Two papers in WWW
We had two papers accepted at The Web Conference: A Method for Assessing Inference Patterns Captured by Embedding Models in Knowledge Graphs and Using Model Calibration to Evaluate Link Prediction in Knowledge Graphs. We analyze inference patterns in knowledge graph embedding models and how calibration can be used to evaluate link prediction in knowledge graphs. Check out our publicly-available implementations here and here.
Jan 2024 - New paper in JSS
A new paper was accepted at the Journal of Systems and Software: Flexible control flow graph alignment for delivering data-driven feedback to novice programming learners. We propose a flexible, graph-based comparison of student programs and adapt a program repair technique to provide feedback to novice learners. Check out our publicly-available implementation.
Aug 2023 - New paper in CIKM
A new paper was accepted at the ACM International Conference on Information and Knowledge Management: A Model-Agnostic Method to Interpret Link Prediction Evaluation of Knowledge Graph Embeddings. We propose a new method to interpret predictions as a whole made by knowledge graph embeeding models that is agnostic to the underlying implementation of the model. Check out our publicly-available implementation.
Aug 2022 - Three papers in ITS
We had three papers accepted at the International Conference on Intelligent Tutoring Systems: Improving Program Matching to Automatically Repair Introductory Programs, Flexible Program Alignment to Deliver Data-Driven Feedback to Novice Programmers and Customizing Feedback for Introductory Programming Courses Using Semantic Clusters. We improve the flexibility of program repairs using graph-based matching to provide feedback to novice programmers. Check out our publicly-available implementation.
Jan 2021 - New paper in WWW
A new paper was accepted at The Web Conference: Revisiting the Evaluation Protocol of Knowledge Graph Completion Methods for Link Prediction. We revisit the evaluation protocol of knowledge graph completion algorithms, including splits, accuracy metrics and model selection. Check out our publicly-available implementation.
Dec 2020 - New poster in SIGCSE
A new poster was accepted at the ACM Technical Symposium on Computer Science Education: Learning to Recognize Semantically Similar Program Statements in Introductory Programming Assignments.
Jul 2020 - New paper in CIKM
A new paper was accepted at the ACM International Conference on Information and Knowledge Management: The Impact of Negative Triple Generation Strategies and Anomalies on Knowledge Graph Completion. We analyze how different strategies to generate negative triples impact the accuracy of knowledge graph completion algorithms. Check out our publicly-available implementation.
Nov 2019 - New papers in SAC
Two new papers were accepted at the ACM/SIGAPP Symposium on Applied Computing: Towards summarizing program statements in source code search. We detect program statements that are relevant to search for source code. Selecting suitable configurations for automated link discovery. We help link discovery techniques reduce the search space of possible configurations. Check out our publicly-available implementation.
Aug 2019 - New paper in KCAP
A new paper was accepted at the ACM International Conference on Knowledge Capture: Generating Rules to Filter Candidate Triples for their Correctness Checking by Knowledge Graph Completion Techniques. We filter triples that are not likely to be added as new knowledge in knowledge graphs. Check out our publicly-available implementation.
Aug 2019 - New paper in CIKM
A new paper was accepted at the ACM International Conference on Information and Knowledge Management: Clustering Recurrent and Semantically Cohesive Program Statements in Introductory Programming Assignments. We cluster program statements of interest using structural graph clustering for programming assignments. Check out our publicly-available implementation.
Jun 2019 - New award
We got the best resource paper award at ESWC'19! Check out the announcement.
May 2019 - New grant
Thanks to the NSF for supporting our research! Check out our project.
Mar 2019 - New paper in ESWC
A new paper was accepted at the Extended Semantic Web Conference: AYNEC: All You Need for Evaluating Completion Techniques in Knowledge Graphs. A Python framework to deal with knowledge graph completion. Check out our publicly-available implementation.
Aug 2018 - New paper in SWAN@FSE
A new paper was accepted at the ACM SIGSOFT International Workshop on Software Analytics: Towards a framework for generating program dependence graphs from source code. We devised a framework to build program dependence graphs directly from Java source code. Check out our publicly-available implementation.
Jul 2018 - ICFP Programming Contest
We participated in the organization of the ICFP Programming Contest. Matthew Fluet, congrats! Check some cool videos from participants: Nanovisu, Skobochka, Bot the Nanobot in the Race to the Bottom.
Aug 2018 - New paper in WWWJ
A new paper was accepted at the World Wide Web journal: Deep Web crawling: a survey. It presents a survey of techniques for perform crawling to extract data from the Deep Web.
Jul 2017 - New demo in FSE
A new demo was accepted at the ACM SIGSOFT Symposium on the Foundations of Software Engineering: ARCC: Assistant for Repetitive Code Comprehension. We used subgraph pattern matching against program dependence graphs to assist in program comprehension. Watch our screencast.
Jan 2017 - New paper in ICDE
A new paper was accepted at the IEEE International Conference on Data Engineering: Automated Personalized Feedback in Introductory Java Programming MOOCs. We developed a new framework to provide personalized feedback in introductory programming courses.
Jul 2016 - New paper in KAIS
A new paper was accepted at the Knowledge and Information Systems journal: Efficient and scalable labeled subgraph matching using SGMatch. It presents a new exact subgraph matching technique based on graphlets and minimum hub covers.
Feb 2016 - New paper in LDOW (WWW workshops)
A new paper was accepted at the Workshop on Linked Data on the Web (LDOW) co-located with the International World Wide Web Conference (WWW): Improving Link Specifications using Context-Aware Information. We developed a new framework to model data collected from a crowd-sensing platform using semantic-web technologies.
Jan 2016 - New paper in CoMoRea (PerCom workshops)
A new paper was accepted at the Workshop on Context and Activity Modeling and Recognition (CoMoRea)co-located with the IEEE International Conference on Pervasive Computing and Communication (PerCom): PLOMaR: An ontology framework for context modeling and reasoning on crowd-sensing platform. It presents a new approach to improve link discovery in the Web of Data by exploiting context information.

People

Carlos R. Rivero

Carlos R. Rivero

Associate Professor in CS@RIT

Email: crr

Beshani Weralupitiya

Beshani Weralupitiya

PhD student (2023)

Email: bw4052

Diba Masihi

Diba Masihi

PhD student (2025)

Email: dm6541

Lydia Klecan

Lydia Klecan

BS/MS student (2025)

Email: lek7518

Alumni

Iti Bansal

Iti Bansal

Angel Cambero

Angel Cambero

Andrea Cimmino

Andrea Cimmino

Md Towhidul Chowdhury

Md Towhidul Chowdhury

Maheen Riaz Contractor

Maheen Riaz Contractor

Bhaskar Krishna Gangadhar

Bhaskar Krishna Gangadhar

Mayur Jawalkar

Mayur Jawalkar

Yusra Khalid

Yusra Khalid

Narayanan Asuri Krishnan

Narayanan Asuri Krishnan

Victor J. Marin

Victor J. Marin

Wilberto Z. Nunez

Wilberto Z. Nunez

Michael Peechatt

Michael Peechatt

Tobin Pereira

Tobin Pereira

Aishwarya Rao

Aishwarya Rao

Srinivas Sridharan

Srinivas Sridharan

Cara Stievater

Cara Stievater

Sudhanshu Tiwari

Sudhanshu Tiwari

Gabriella Wolf

Gabriella Wolf

Upcoming ImagineRIT exhibit

Coming soon!

Knowledge graphs 101: Facts, links and more!

Join us for an interactive session where our lab members will showcase how knowledge graphs, data science, and AI work behind the scenes in real-world applications. Learn about predicting facts, discovering patterns, and how these techniques are shaping technology today!

This event is designed for all ages. No technical background required. Come with curiosity and leave with a better understanding of how complex data can be analyzed and visualized.

Date: Saturday, April 25, 2026
Time: 10:00 AM - 5:00 PM
Location: GCCIS, RIT