Editing Ponnurangam Kumaraguru

{{Infobox Professor
| education = Ph.D
| occupation = Professor
| Institute = IIIT-H
| specialization = NLP and Applied Machine Learning
}}

== Ponnurangam Kumaraguru ==
'''Prof. Ponnurangam Kumaraguru''' is a Professor of Computer Science at [[IIIT-H]]. He is an Associate [[Researcher]] at Robert Bosch Centre for Data Science & AI - [[IIT Madras]], and an Adjunct faculty at IIIT Delhi. PK was inducted an ACM Distinguished Member in 2021. PK is an ACM India Council Member, and Chair of the Research Facilitation Committee of ACM India. PK is a TEDx and an ACM Distinguished & ACM India Eminent Speaker.<ref>{{Cite web |title=Ponnurangam details rbcdsai |url=https://rbcdsai.iitm.ac.in/blogs/p-k/}}</ref><ref>{{Cite web |title=Faculty profile details |url=https://precog.iiit.ac.in/index.html}}</ref>

== Education ==
PK completed his [[B.E]] at [[University of Madras]] in 1998. He received his [[Ph.D.]] from the School of Computer Science at [[Carnegie Mellon University]] (CMU). His Ph.D. thesis work on anti-phishing research at CMU contributed in creating an award-winning startup - Wombat Security Technologies.<ref>{{Cite web |title=Centre of Responsible AI profile |url=https://cerai.iitm.ac.in/people/pk/}}</ref>

==Research & Publications==
His area of interests are [[Natural Language Processing]], Applied Machine Learning.<ref>{{Cite web |title=ACM Ponnurangam profile details |url=https://india.acm.org/education/learning/esp/ponnurangam-kumaraguru}}</ref>

# The wmdp benchmark: Measuring and reducing malicious use with unlearning in 2024.<ref>{{Cite web |title=The wmdp benchmark: Measuring and reducing malicious use with unlearning |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:DrR-2ekChdkC}}</ref>
# Leveraging intra and inter modality relationship for multimodal fake news detection in 2022.<ref>{{Cite web |title=Leveraging intra and inter modality relationship for multimodal fake news detection |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:MpfHP-DdYjUC}}</ref>
# Stress classification using brain signals based on LSTM network in 2022.<ref>{{Cite web |title=Stress classification using brain signals based on LSTM network |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:LdasjJ6CEcoC}}</ref>
# “Subverting the Jewtocracy”: Online antisemitism detection using multimodal deep learning in 2021.<ref>{{Cite web |title=“Subverting the Jewtocracy”: Online antisemitism detection using multimodal deep learning |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:ZzlSgRqYykMC}}</ref>
# Automating fake news detection system using multi-level voting model in 2020.<ref>{{Cite web |title=Automating fake news detection system using multi-level voting model |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&citation_for_view=MfzQyP8AAAAJ:9pM33mqn1YgC}}</ref>
# Mind your language: Abuse and offense detection for code-switched languages in 2019.<ref>{{Cite web |title=Mind your language: Abuse and offense detection for code-switched languages |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:BwyfMAYsbu0C}}</ref>
# Collective classification of spam campaigners on Twitter: A hierarchical meta-path based approach in 2018.<ref>{{Cite web |title=Collective classification of spam campaigners on Twitter: A hierarchical meta-path based approach |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:nrtMV_XWKgEC}}</ref>
# A social media based index of mental well-being in college campuses in 2017.<ref>{{Cite web |title=A social media based index of mental well-being in college campuses |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:9vf0nzSNQJEC}}</ref>
# Analyzing social and stylometric features to identify spear phishing emails in 2014.<ref>{{Cite web |title=Analyzing social and stylometric features to identify spear phishing emails |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&cstart=20&pagesize=80&citation_for_view=MfzQyP8AAAAJ:D03iK_w7-QYC}}</ref>
# Who falls for phish? A demographic analysis of phishing susceptibility and effectiveness of interventions in 2010.<ref>{{Cite web |title=Who falls for phish? A demographic analysis of phishing susceptibility and effectiveness of interventions |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=MfzQyP8AAAAJ&citation_for_view=MfzQyP8AAAAJ:Tyk-4Ss8FVUC}}</ref><br />
== References ==

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