Ashwin Ganesan's Homepage

Ashwin Ganesan
Mumbai, Maharashtra, India
Phone: +91 - 98694 55961
Email: ashwin.ganesan@gmail.com

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About Me | Research | Publications | Teaching | Talks | Biography |  Curriculum Vitae (PDF)

I am a computer science researcher and academic leader with over 20 years of experience spanning research, teaching, curriculum development, and industry engagement. My research develops algorithms and graph AI methods for entity resolution, financial crime detection, and network optimization, with sole-authored publications in top-tier venues such as IEEE/ACM Transactions on Networking and IEEE Transactions on Information Theory.  I currently lead research on GNN expressivity and graph-based fraud detection at IIT Madras CyStar, teach at BITS Pilani and IIIT Surat, and have designed rigorous curricula aligned with international standards for academic programs at multiple institutions.

Current Affiliations

• Indian Institute of Technology, Madras, India.  Project Consultant, Centre for Cybersecurity, Trust and Reliability (CyStar), Department of Computer Science and Engineering, December 2024 - Present.  Research on GNN expressivity and graph-based financial crime detection, funded by a Dun & Bradstreet CSR grant on master data management.

• BITS Pilani (Work Integrated Learning Programmes), Mumbai, India.  Adjunct Faculty, Department of Computer Science and Information Systems, March 2025 - Present.

• Indian Institute of Information Technology, Surat, Gujarat, India. Professor of Practice, October 2024 - Present.

News

• March 2026: New preprint — "A Tight Expressivity Hierarchy for GNN-Based Entity Resolution in Master Data Management," 48 pages, March 2026. [ arXiv:2603.27154 ]

• January 2026: Co-delivered workshop "Graph Neural Networks for Cyber Forensics: Advanced Pattern Detection in Transaction Networks" at ISEA International Conference on Security and Privacy (ISEA-ISAP 2026), IIT Madras

• December 2025: Invited lecture, "A Combinatorial Approach to Detecting Financial Crimes in Blockchain Networks," Winter School on Decentralized Trust and Blockchains, CyStar, IIT Madras.

• March 2025: Joined BITS Pilani WILP as Adjunct Faculty.

• March 2025: Co-authored funded proposal: "Secure and Scalable Master Data Management: Integrating Blockchain, Byzantine Fault Tolerance, and Graph-Based Analytics," Dun & Bradstreet CSR Grant.

• January 2025: Paper published in IEEE Transactions on Mobile Computing: "The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems." [ doi, preprint ]

Research Areas

• • Graph neural networks

  • Graph analytics for financial crime detection

  • Distributed algorithms

  • Graphs and algorithms in communication networks

  • Discrete mathematics and graph theory

  • Applied combinatorics

Selected Recent Papers

• • A. Ganesan,
    "A Tight Expressivity Hierarchy for GNN-Based Entity Resolution in Master Data Management,"
    Technical Report, 48 pages, March 2026. [ arXiv:2603.27154 ]

  • A. Ganesan,
    "The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems,"
    IEEE Transactions on Mobile Computing, vol. 24, no. 1, pp. 150-164, January 2025. [ doi, preprint ]

  • A. Ganesan,
    "Performance analysis of distance-1 distributed algorithms for admission control under the 2-hop interference model,"
    Theoretical Computer Science,  Vol. 947, Article 113718, 16 pages, 20 February 2023. [ doi ]

  • A. Ganesan,
    "On some distributed scheduling algorithms for wireless networks with hypergraph interference models,"
    IEEE Transactions on Information Theory, vol. 67, no. 5, pp. 2952-2957, May 2021. [ preprint , doi ]

  • A. Ganesan,
    "Performance guarantees of distributed algorithms for QoS in wireless ad hoc networks,"
    IEEE/ACM Transactions on Networking, vol. 28, pp. 182-195, February 2020. [ doi, PDF, preprint ] 

Publications Summary

30+ publications in journals and conferences (most are sole-authored), including 5 in IEEE Transactions / IEEE-ACM Transactions, and 1 invited book chapter.  For more publications, see the Publications page.