Parsa Kamalipour is a thesis-based Master of Computer Science student at Concordia University, in the Department of Computer Science and Software Engineering at the Gina Cody School of Engineering and Computer Science. He works in the Algorithms & Complexity Lab under the supervision of Professor Hovhannes Harutyunyan.

Research

Parsa’s research is on community detection in social and complex networks. His thesis, Geodesic-Compact Community Detection and Quality Assessment in Social Networks (expected 2027), asks how to find and evaluate communities from shortest-path (geodesic) structure alone, without ground-truth labels. The underlying idea is that the members of a good community are close to one another compared with the rest of the network.

In this line of work he introduced the weighted-average Geodesic Distance Modularity (wGDM), a partition-level measure of community quality, and carried out the first systematic study of Metric Backbone sparsification as preprocessing for the Leiden algorithm. He presented this first-author paper at IEEE SNAMS 2025 in Vienna. He also designed Spider, a near-linear algorithm that grows communities from seed vertices by geodesic expansion, refines them with modularity, and merges them by greedy matching; it was published in Computers (MDPI) in 2026.

Earlier research

As an undergraduate at Vali-e-Asr University of Rafsanjan, Parsa worked with Dr. Fahimeh Dabaghi-Zarandi on CRLG, a randomized community detection framework that combines local and global network information. This B.Sc. thesis work was published in the Journal of Network and Computer Applications (Elsevier) in 2022.

He then joined the Formal Methods and Tools group at the University of Twente as a remote Research Assistant with Dr. Iman Hemati Moghadam. There he built the Kotlin code parser used to extend the RefDetect refactoring detector to Kotlin and helped build validated refactoring datasets (IEEE SANER 2024). He also contributed to the first version of a pipeline that detects refactorings across programming languages using LLM-based code translation.

Interests

His background is in theoretical computer science: design and analysis of algorithms, graph theory, discrete mathematics, data structures, and complexity theory. His research interests include graph algorithms, graph mining, social network analysis, combinatorial optimization, approximation and randomized algorithms, and online algorithms.

Teaching

Parsa has been a teaching assistant for more than 15 courses and 1650+ hours, at Concordia and at Vali-e-Asr University. The courses range from theory (Design and Analysis of Algorithms, Combinatorics, Introduction to Theoretical Computer Science, Discrete Mathematics, Data Structures, Probability and Statistics) to programming and systems (Fundamentals of Programming, Object-Oriented Programming, Principles of Programming Languages, Computer Organization, Microprocessor-Based Systems, Operating Systems) and data, software and AI (Database, Data Systems for Software Engineers, Data Mining, Information Retrieval, Software Engineering, Artificial Intelligence). At Vali-e-Asr he led a team of ten TAs for Design and Analysis of Algorithms. In May 2026 he received the Dean’s Excellence Award for Excellence in Teaching by a Teaching Assistant from the Gina Cody School.

His long-term goal is to become a professor and to keep doing both research and teaching.