George Chacko
George Chacko
  • Research Associate Professor
2130 Siebel Center for Comp Sci

For More Information

Resident Instruction

  • CS 598: Computational Scientometrics

Research Statement

 

My scientific interests are centered around novelty in science, impact, peer review, knowledge diffusion, and research community structure. A related interest is the social interactions that drive scientific recognition and achievement. Emphasis is placed on value to at least one of four stakeholders: (i) research funders, who want to know what their support has achieved and what it might in future, (ii) research institutions who ask the same questions as funders but are recipients of funds and must strategize to sustain their existing support and/or augment it, (iii) providers of research analytical services who think beyond the confines of commonplace global metrics such as the h-index and its well documented limitations, and (iv) the evaluation community.

I am presently working on the identification and characterization of research communities that form around scientific questions. The techniques used in my studies build upon work in scientometrics, sociology, science history, and computer science. The work I do is presently supported by a grant in 2022 from the Insper:Illinois collaboration as well as a research award from the Oracle Corporation.  Our first manuscript from the collaboration with Insper, Well-Connected Communities in Real-World Networks (2023) Park et al. will be published in the proceedings of Complex Networks 2023 (a preprint is available https://arxiv.org/abs/2303.02813). A second manuscript describing a parallelized code for enforcing well-connected communities has been submitted. We have funding for a PhD student to work on this project, which has many interesting dimensions. Interested PhD students are encouraged to reach out.

Most recently, Vikram Ramavarapu, Vidya Kamath Pailodi and Hossein Mohasel Arjomandi have joined my group. Vikram developed a parallelized code to enforce connectivity in clusters. Vikram was just selected to spend a semester at the National Institute of Informatics in Tokyo under the aegis of the Japan NII Onsite Internship programs so congratulations to him. Vidya is developing a community search strategy and  was announced as one of five 2024 Siebel Scholars so congratulations to her. Hossein is developing a distance-based measure for citation data. Laxmi Vijayan and Haadi Elsaawy from the iCAN program took a CS 597 course with me in summer 20203 and made great progress. Other students I have worked with are: Undergraduate. Hemank Kohli and Franklin Moy (ECE), Akhil Jakatdar, Isabella Nisperos, Trisha Manna (CS) Graduate: Elaina Wittmer, Sid Ahuja, Deep Kotadia (CS). Through collaboration with Tandy Warnow: Eleanor Wedell, Minhyuk Park, Baqiao Liu, Yasamin Tabatabaee (CS). João Alfredo Cardos Lamy from Insper made a brief visit this summer and will continue working with us with local guidance from Fabio Ayres. 

CS 597 offerings: I am willing to offer CS 597 courses for current PhD or MS students at UIUC who are looking for potential thesis topics. The research I can advise on is presently focused on clustering, community detection. community search with application to the real world problems of science mapping, research evaluation, and scientometrics. A key part of the group experience is developing the ability to critically interpret the literature relevant to our interests. Students are required to develop verbal and written communications skills.

Selected Articles in Journals

Refereed Conference Papers and Presentations

  • Well-Connected Communities in Real-World Networks (2023) Minhyuk Park, Yasamin Tabatabaee, Baqiao Liu, Vidya Kamath Pailodi, Vikram Ramavarapu, Rajiv Ramachandran, Dmitriy Korobskiy, Fabio Ayres, George Chacko, Tandy Warnow. (2023) Complex Networks 2023.

Invited Lectures

Other Scholarly Activities

  • Program Committee, International Society for Scientometrics and Informetrics (ISSI) 2023

Recent Courses Taught

  • CS 598 GGC - Computational Scientometrics

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