Anik’s Curriculum Vitae

📄 Download CV (PDF)

Professional Summary

Passionate and detail-oriented NLP researcher with expertise in large language models (LLMs), misinformation detection, and retrieval-augmented generation (RAG). Currently serving as a Graduate Research Assistant at the University of North Texas, contributing to peer-reviewed papers accepted at EMNLP, COLM, ISCRAM, and CLEF. Skilled at developing context-aware, interpretable, and socially responsible AI systems for applications in public health, crisis communication, and digital literacy. Aspiring Ph.D. candidate aiming to advance human-aligned AI models that foster trust, transparency, and effective decision-making.

Research Interests

• Core Technical Areas: Retrieval-Augmented Generation (RAG), Health Misinformation Detection, Fact-Grounded Communication, Reinforcement Learning with Human Feedback (RLHF), Explainable AI.
• Applied Domains: Public Health Communication, Crisis Response, Educational Technology, Human-AI Collaboration.
• Methodologies: Multi-Agent Systems, Context-Aware Text Generation, Real-Time Data Integration, Knowledge-Augmented Language Models, Model Evaluation Frameworks.

Professional Experience

Data Insights Analyst (Internship)

SEES Group, Franklin, TN (Remote) — Aug 2025 – Present

• Supporting data insights and analytics projects with focus on data quality, reporting, and visualization.
• Building dashboards and reports in Power BI and Excel, leveraging Microsoft Fabric for scalable data integration and analytics.
• Collaborating with cross-functional teams to optimize workflows, manage data pipelines, and ensure data integrity.

Graduate Research Assistant

University of North Texas, Denton, TX — May 2025 – Present
Advisor: Dr. Lingzi Hong, Assistant Professor

• Conducting research on how AI and Large Language Models (LLMs) can provide contextually relevant responses to users.
• Leading a project that develops AI-driven solutions for crisis situations, generating recommendations tailored to user needs.
• Designing and evaluating evidence-based counter-speech generation models to combat health misinformation using multi-agent LLM frameworks.

Graduate Teaching Assistant

University of North Texas, Denton, TX — Aug 2024 – May 2025

• Assisted in Data Visualization (Tableau, Power BI, Python) and Introduction to Data Science (R, ML, data visualization).
• Conducted office hours to address student queries, explain complex topics, and provide guidance on assignments and projects.
• Evaluated coursework and provided constructive feedback to improve student learning outcomes.

Research Assistant – KI Research Lab

American International University-Bangladesh (AIUB), Dhaka, Bangladesh — May 2022 – Dec 2022
Advisor: Md. Kishor Morol, Assistant Professor

• Researched deep learning applications for medical diagnostics, focusing on improving accuracy in disease detection.
• Developed and tested neural network models to enhance diagnostic precision.
• Guided undergraduate students in research methodology, technical writing, and project design.

Teaching Assistant

American International University-Bangladesh (AIUB), Dhaka, Bangladesh — Sep 2021 – Dec 2021

• Supported the Introduction to Database course, assisting students with SQL queries, schema design, and database troubleshooting.
• Provided academic assistance to improve understanding of database concepts and implementation.

Intern – Enterprise Applications Department, Microfinance

BRAC, Dhaka, Bangladesh — Mar 2022 – May 2022

• Collaborated with the development team to test and debug software, ensuring compliance with User Acceptance Testing (UAT) standards.
• Collected and documented feedback from 5+ microfinance branches via site visits and interviews to guide software improvements.
• Proposed and documented feature enhancements to improve usability and efficiency in branch operations.

Publications

(Full list available on Google Scholar)

1. Anik, A. S., Song, X., Wang, E., Wang, B., Yarimbas, B., & Hong, L. (2025).
   Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation.
   Conference on Language Modeling (COLM 2025).
   arXiv:2507.07307

2. Song, X., Anik, A. S., Blanco, E., Frías-Martínez, V., & Hong, L. (2025).
   A Dynamic Fusion Model for Consistent Crisis Response.
   Empirical Methods in Natural Language Processing (EMNLP 2025 Findings). (Accepted)

3. Song, X., Anik, A. S., Blanco, E., Luo, P., Ding, J., & Hong, L. (2025).
   Speaking at the Right Level: Literacy-Controlled Counterspeech Generation with RAG-RL.
   Empirical Methods in Natural Language Processing (EMNLP 2025 Findings). (Accepted)

4. Song, X., Anik, A. S., Frías-Martínez, V., & Hong, L. (2025).
   Dynamic Fusion of Large Language Models for Crisis Communication.
   International Conference on Information Systems for Crisis Response and Management (ISCRAM 2025).
   DOI: 10.59297/nqysjq45

5. Arman, M., Prottush, N., Rusho, M. A., Datta, A., Anik, A. S., Dohan, D. M., Sajid, M. A. U. I., Sheikh, I. A., & Jahna, M. K. (2025).
   A Hybrid Attention-Guided Fusion Network with Grad-CAM for MPox Skin Lesion Classification.
   4th International Conference on Computing and Machine Intelligence (ICMI 2025). (Accepted)

6. Anik, A. S., Chowdhury, M. F. K., Wyckoff, A., & Choudhury, S. R. (2025).
   ClaimIQ at CheckThat! 2025: Comparing Prompted and Fine-Tuned Language Models for Verifying Numerical Claims.
   Conference and Labs of the Evaluation Forum (CLEF 2025). (Notebook Paper, Accepted)

7. Das, S. S., Anik, A. S., Morol, M. K., & Mahmood, M. S. (2024).
   Outcome-Based Education: Evaluating Students’ Perspectives Using Transformer.
   27th International Conference on Computer and Information Technology (ICCIT 2024).
   DOI: 10.1109/ICCIT64611.2024.11021724

8. Das, S. S., Anik, A. S., Hossain, M. M., Morol, M. K., Jahan, F., & Al-Jubair, M. A. (2023).
   A Study on Future Lockdown Predictions Using ANN.
   International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM 2023).
   DOI: 10.1109/NCIM59001.2023.10212686

9. Anik, A. S., Chakraborty, K., Datta, B., Kader, A., & Morol, M. K. (2022).
   A Comparative Analysis for the Detection of COVID-19 from Chest X-ray Dataset.
   International Conference on Recent Progresses in Science, Engineering and Technology (ICRPSET 2022).
   DOI: 10.1109/ICRPSET57982.2022.10188570