Pratiba Irudayaraj Top [portable]

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| Metric | Value (as of April 2026) | |--------|--------------------------| | | 23,500+ | | h‑index | 47 | | i10‑index | 112 | | Top‑10 most cited papers | 1) HGNNs for Heterogeneous Graphs (KDD 2016) – 5,200 citations; 2) Counterfactual Explanations for Graph Models (FAT 2020) – 3,100 citations; 3) Low‑Resource Language Transfer (ACL 2019) – 2,800 citations | | Awards | • ACM SIGKDD Distinguished Paper (2016) • IEEE Fellow (2022) • MIT Technology Review “Innovators Under 35” (2018) • ACM SIGAI Outstanding Service Award (2024) | | Professional Service | • Area Chair, NeurIPS (2022‑2024) • Program Committee, KDD, ACL, AAAI, ICWSM • Advisory Board, AI4Good Initiative (UN‑DPPA) |

: She has extensively reviewed and contributed to the development of protein-based lateral flow assays. Her work focuses on addressing the "high limit of detection" (sensitivity issues) inherent in standard antigen tests by optimizing protein-protein interactions. ACS Publications 2. SARS-CoV-2 Viral Protein Research pratiba irudayaraj top

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If you are interested in exploring her specific research papers, I can help find the full text for: The article on magneto immunosensors The Frontiers in Virology review paper Pratiba Irudayaraj - Facebook If you are looking for a piece of

What sets Pratiba apart from a "coder" is her ability to align technical work with business goals. She asks the right questions before writing a single line of code, ensuring that the team works on the right problems, not just any problem.

(If you want exact titles, dates, or links for these works, tell me which domain—academia, arts, tech, public service—so I can give specifics.) SARS-CoV-2 Viral Protein Research When you search for

Advanced to active researcher role, focusing on DNA-based vaccines and immunotherapies. Why Her Research Matters for Global Health