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 # Hi there!
 
-I am a fourth year Ph.D. student under the supervision of [Dr. Huan Liu](https://www.public.asu.edu/~huanliu/) at the [Data Mining and Machine Learning Lab](https://dmml.asu.edu/home) at the School of CS & AI, Arizona State University. My current research primarily focuses on: (i) leveraging large language models (LLMs) for human-intensive tasks in a machine learning pipeline, (ii) robust detection of AI-generated content, and (iii) NLP applications in domain adaptation and domain generalization. During the summer of 2022, I interned at [Nokia Bell Labs](https://www.bell-labs.com/#gref) as a Software Systems Research Intern, under the guidance of Buvaneswari Ramanan and Thomas Woo, where I worked on problems in the realm of continual learning and low-resource learning in real-world use-cases. 
+I am a final year Ph.D. student under the supervision of [Dr. Huan Liu](https://www.public.asu.edu/~huanliu/) at the [Data Mining and Machine Learning Lab](https://dmml.asu.edu/home) at the School of CS & AI, Arizona State University. My current research primarily focuses on: (i) leveraging large language models (LLMs) for human-intensive tasks in a machine learning pipeline, (ii) robust detection of AI-generated content, and (iii) NLP applications in domain adaptation and domain generalization. During the summer of 2024, I was an Applied Research Intern at NVIDIA NeMo Guardrails, working with Christopher Parisien and Shaona Ghosh, on inference-time safety steering of large language models(LLMs). During the summer of 2022, I interned at [Nokia Bell Labs](https://www.bell-labs.com/#gref) as a Software Systems Research Intern, under the guidance of Buvaneswari Ramanan and Thomas Woo, where I worked on problems in the realm of continual learning and low-resource learning in real-world use-cases. 
 When I'm not working, I enjoy traveling, hiking, kayaking, camping and chilling with my cat Luna!
 
+**<span style="color:red">I'm current on the industry job market, looking for Applied Scientist, Research Scientist or related roles, preferably around LLM research + product. Please reach out!</span>.**
+
 # 📢 News
 
+\[Sep 2024\] Two papers accepted at EMNLP 2024 Main Track: (1) [Defending Against Social Engineering Attacks in the Age of LLMs](https://arxiv.org/abs/2406.12263), (2) [Large Language Models for Data Annotation: A Survey](https://arxiv.org/abs/2402.13446).
+
+\[Sep 2024\] Delivered an in-person tutorial on "Defending Against Generative AI Threats in NLP" at SBP-BRiMS 2024, Pittsburgh, PA, USA. [Tutorial Resources](https://github.com/AmritaBh/sbp24-llm-attack-defense-tutorial).
+
+\[Sep 2024\] Received the SBP-BRiMS 2024 Student Travel Award!
+
+\[Sep 2024\] Invited to be a Program Committee Member for SDM 2025.
+
+\[Jun 2024\] Received the SIGIR 2024 NSF Travel Award!
+
+\[Jun 2024\] Invited to be a Program Committee Member for AAAI 2025.
+
+\[May 2024\] Invited to be a Program Committee Member for SBP-BRiMS 2024.
+
+\[May 2024\] My chat with ScienceNewsExplores(SNE) got featured in this [SNE news story](https://www.snexplores.org/article/a-new-test-could-help-weed-out-ai-generated-text).
+
+\[Apr 2024\] Our paper "Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales" got accepted to NNACL WOAH 2024!
+
 \[Apr 2024\] Gave an invited talk at the ASU Cronkite School of Journalism for an AI in Journalism course for Masters students in Investigative Journalism, on **Large Lnaguage Models: Opportunites and Threats in Journalism**. [Slides](https://drive.google.com/file/d/1qmG6btQ0CSf03iGNOzaX7LMmh5yyDb8N/view?usp=sharing)
 
 \[Mar 2024\] Our demo paper "ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement" has been accepted at SIGIR 2024! [Paper Link](https://arxiv.org/abs/2402.06221)

diff --git a/_pages/cv.md b/_pages/cv.md
@@ -9,7 +9,7 @@ redirect_from:
 
 {% include base_path %}
 
-Here's my [Résumé](https://drive.google.com/file/d/1baxNZXJvn9dxw_XDG3kJ4nzWwQ_cro5D/view?usp=sharing).
+Here's my [Résumé](https://drive.google.com/file/d/14vqXDpdMIVPpkq-ErZdZEdX3tjEOoPw0/view?usp=sharing). Please reach out at abhatt43 at asu dot edu !
 
 <!-- <embed src="https://github.com/sbhambr1/sbhambr1.github.io/raw/main/files/R%C3%A9sum%C3%A9.pdf"" type="application/pdf" width="800px" height="2100px" /> -->
 

diff --git a/_pages/publications.md b/_pages/publications.md
@@ -6,25 +6,41 @@ author_profile: true
 ---
 
 
-You can also find my articles on <u><a href="https://scholar.google.com/citations?user=hdXXMPwAAAAJ&hl=en">my Google Scholar profile</a>.</u>
+You can find all my articles at <u><a href="https://scholar.google.com/citations?user=hdXXMPwAAAAJ&hl=en">my Google Scholar profile</a>.</u>
 
 
 ## Recent Preprints!
 
 1. **EAGLE: A Domain Generalization Framework for AI-generated Text Detection.** _Amrita Bhattacharjee_, Raha Moraffah, Joshua Garland, Huan Liu. [paper link](https://arxiv.org/abs/2403.15690)
 
-2. **Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales.** Ayushi Nirmal\*, _Amrita Bhattacharjee_\*, Paras Sheth, Huan Liu. (* Equal contribution) [paper link](https://arxiv.org/abs/2403.12403)
-
-3. **Large Language Models for Data Annotation: A Survey.** Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, _Amrita Bhattacharjee_, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu. [paper link](https://arxiv.org/abs/2402.13446)
+2. **Zero-shot LLM-guided Counterfactual Generation for Text.** _Amrita Bhattacharjee_, Raha Moraffah, Joshua Garland, Huan Liu. [paper link](https://arxiv.org/abs/2405.04793)
 
 _____
 
-## Accepted Publications
+## Selected Accepted Publications
+
+
+1. **Defending Against Social Engineering Attacks in the Age of LLMs.** Lin Ai\*, Tharindu Kumarage\*, Amrita Bhattacharjee\*, Zizhou Liu, Zheng Hui, Michael Davinroy, James Cook, Laura Cassani, Kirill Trapeznikov, Matthias Kirchner, Arslan Basharat, Anthony Hoogs, Joshua Garland, Huan Liu, Julia Hirschberg. **\[EMNLP 2024\]**
+
+2. **Large Language Models for Data Annotation: A Survey.** Zhen Tan*, Dawei Li*, Song Wang*, Alimohammad Beigi, Bohan Jiang, _Amrita Bhattacharjee_, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu. [paper link](https://arxiv.org/abs/2402.13446) **\[EMNLP 2024\]**
+
+3. **Towards LLM-guided Causal Explainability for Black-box Text Classifiers.**  _Amrita Bhattacharjee_, Raha Moraffah, Joshua Garland, Huan Liu. [paper link](https://www.researchgate.net/profile/Amrita-Bhattacharjee-3/publication/378142099_Towards_LLM-guided_Causal_Explainability_for_Black-box_Text_Classifiers/links/65c988bd1bed776ae341441d/Towards-LLM-guided-Causal-Explainability-for-Black-box-Text-Classifiers.pdf) **\[AAAI ReLM 2024\]**
+
+4. **Adversarial Text Purification: A Large Language Model Approach for Defense.**     Raha Moraffah, Shubh Khandelwal, _Amrita Bhattacharjee_, Huan Liu. [paper link](https://link.springer.com/chapter/10.1007/978-981-97-2262-4_6) **\[PAKDD 2024\]**
+
+5. **🏆<span style="color:red">\[Outstanding Paper Award\]</span>🏆 ConDA: Contrastive Domain Adaptation for AI-generated Text Detection.** _Amrita Bhattacharjee_, Tharindu Kumarage, Raha Moraffah, Huan Liu [paper link](https://aclanthology.org/2023.ijcnlp-main.40.pdf) **\[IJCNLP-AACL 2023\]**
+
+6. **Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales.** Ayushi Nirmal\*, _Amrita Bhattacharjee_\*, Paras Sheth, Huan Liu. (* Equal contribution) [paper link](https://arxiv.org/abs/2403.12403) **\[NAACL WOAH 2024\]**
+
+7. **J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News.** Tharindu Kumarage, _Amrita Bhattacharjee_, Djordje Padejski, Kristy Roschke, Dan Gillmor, Scott Ruston, Huan Liu, Joshua Garland. [paper link](https://aclanthology.org/2023.ijcnlp-main.32.pdf) **\[IJCNLP-AACL 2023\]**
+
+8. **Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?** _Amrita Bhattacharjee_, Huan Liu. [paper link](https://dl.acm.org/doi/abs/10.1145/3655103.3655106) **\[ACM SIGKDD Explorations,Vol. 25, No. 2\]**
+
+7. **Harnessing Artificial Intelligence to Combat Online Hate: Exploring the Challenges and Opportunities of Large Language Models in Hate Speech Detection.** Tharindu Kumarage\*, _Amrita Bhattacharjee_\*, Joshua Garland. **\[Book Chapter\]**
 
-1. **Harnessing Artificial Intelligence to Combat Online Hate: Exploring the Challenges and Opportunities of Large Language Models in Hate Speech Detection.** Tharindu Kumarage\*, _Amrita Bhattacharjee_\*, Joshua Garland.
+10. **Text Transformations in Contrastive Self-Supervised Learning: A Review.** Amrita Bhattacharjee, Mansooreh Karami, Huan Liu. [paper link](https://www.ijcai.org/proceedings/2022/0757.pdf) **\[IJCAI 2022 (Survey)\]** 
 
 
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diff --git a/_pages/teaching&service.md b/_pages/teaching&service.md
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 ### Current Mentees:
 
+1. Saurabh Bhausaheb Zinjad (MS CS) [LinkedIN](https://www.linkedin.com/in/saurabhzinjad/)
+2. Aryan Vinod Keluskar (FURI Undergrad) [LinkedIN](https://www.linkedin.com/in/aryankeluskar/)
+
+
+### Past Mentees:
+
 1. Ayushi Nirmal (MS CS) [LinkedIN](https://www.linkedin.com/in/ayushi-nirmal/)
-2. Saurabh Bhausaheb Zinjad (MS CS) [LinkedIN](https://www.linkedin.com/in/saurabhzinjad/)
-3. Baixi Jiao (Undergrad)
-4. Punit Sai Arani (Undergrad - Honors thesis)
-5. Neha Balamurugan (Undergrad - Honors thesis)
+4. Punit Sai Arani (Undergrad - Honors thesis) [LinkedIN](https://www.linkedin.com/in/punitarani/)
+5. Neha Balamurugan (Undergrad - Honors thesis) [LinkedIN](https://www.linkedin.com/in/neha-balamurugan-8455981b1/)
 
-### Past mentoring
+Others:
 
-Mentored 3 women for pursuing a research career in Computer Science via Women in Machine Learning (WiML) (Fall 2022)
+- Mentored 3 women for pursuing a research career in Computer Science via Women in Machine Learning (WiML) (Fall 2022)
 
 ## Teaching
 
+### Fall 2024: Project Coordinator and Guest Lecturer: CSE 472 - Social Media Mining
+
+I am currently serving as the Project Coordinator and a Guest Lecturer for the course CSE 472: Social Media Mining, offered by my Ph.D advisor Dr. Huan Liu, in Fall 2024. Guest lectures: (1) Data Mining, (2) Introduction to Large Language Models: The Good, Bad and the Ugly [Slides](https://docs.google.com/presentation/d/1w-ZHnCWK4SdOFzwwzuNWrPF2aKz3T-ldNSniVL-6nGQ/edit?usp=sharing).
+As project coordinnator: I am in charge of leading how course projects are designed, as well as designing two specific course project, mentoring and assisting students, and grading the final projects.
+
+
+
 ### Fall 2023: Project Coordinator and Mentor: Barrett Honors College
 
 I served as the Project Coordinator whereby I designed and developed a project for the Barrett Honors college with the topic **Political Bias and Strategic Influence Operations in Large Language Models**. I also had the opportunity of mentoring 4 undergraduate students working on this interesting project.
@@ -54,10 +65,10 @@ I was appointed as the TA for the undergraduate course Principles of Programming
 ## Reviewing & Conference Duties
 
 
-1. Program Committee Member for **AAAI 2023, AAAI 2024, IJCAI 2024 (Survey), SBP-BRiMS 2023**
+1. Program Committee Member for **SDM 2025, AAAI 2025, AAAI 2024, AAAI 2023, IJCAI 2024 (Survey), SBP-BRiMS 2024, SBP-BRiMS 2023**
 
 
-2. Reviewer for SNAM: Social Network Analysis and Mining, JNCA: Journal of Network and Computer Applications, IPM: Information Processing and Management, CogSys: Cognitive Systems Research, AAAI 2023, SBP-BRiMS 2023, AAAI 2024
+2. External reviewer for SNAM: Social Network Analysis and Mining, JNCA: Journal of Network and Computer Applications, IPM: Information Processing and Management, CogSys: Cognitive Systems Research, Behavior and Information Technology, MINT workshop at NeuRIPS 2024.
 
 3. Sub-reviewer for CIKM 2020, ASONAM 2020