Dr. Sameer Qadir, PhD
Associate Professor of Computer Science & AI Systems
Department of Computer Science & Engineering
sameerqadir.academi.site
sameer.qadir@nici.edu
San Diego, CA
National Institute of Computational Innovation (NICI)
About Me
I am a computer science researcher and educator with a focus on Artificial Intelligence, Distributed Systems, and Human-AI Interaction. My research combines machine learning, real-time systems, and socially aware computing to design AI that is reliable, scalable, and ethically grounded.I direct the Responsive Intelligence & Systems Lab (RISLab) at NICI, where we develop open-source AI tools, real-time sensing systems, and embedded intelligence frameworks for use in public services, healthcare, and critical infrastructure.
Keywords:
Artificial Intelligence · Real-Time Systems · Human-AI Interaction · Explainable AI · Edge Computing · System Reliability
Education
PhD in Computer Science
2010–2015
Georgia Institute of Technology
Scalable Architectures for Real-Time Context-Aware AI
MSc in Software Engineering
2008–2010
University of Toronto
Model Checking in Distributed Middleware Systems
BSc in Computer Science
2004–2008
Lahore University of Management Sciences (LUMS)
Hybrid Algorithms for Smart Grids
15
Journals
11
Proceedings
30
Conferences
Research Interests
Robust and real-time AI for dynamic systems
Privacy-aware learning and ethical AI systems
Distributed computing at the edge (IoT/Smart Cities)
Human-in-the-loop system optimization
Federated and embedded machine learning
AI for social good and responsible innovation
Latest Publications (Highlights)
1. Qadir, S., et al. (2024). “Human-AI Dialogue in Dynamic Disaster Response Systems.” IEEE Transactions on Human-Machine Systems.
2. Qadir, S., Zhen, H., et al. (2023). “Edge-AI Models for Privacy-Preserving Healthcare Monitoring.” ACM Transactions on Embedded Computing Systems.
3. Qadir, S., Ali, T., & Campos, J. (2022). “Interpretable Machine Learning for Public Safety Applications.” AAAI Conference on AI Ethics & Society.
Research Projects (Ongoing)
Title: 'Real-Time AI Infrastructure for Emergency Response (RAID)'
Funded by NSF & Department of Homeland Security ($1.8M, 2023–2026)
Goal: Build adaptive, distributed AI frameworks for real-time emergency decision-making.
Title: 'Real-Time AI Infrastructure for Emergency Response (RAID)'
Funded by NSF & Department of Homeland Security ($1.8M, 2023–2026)
Goal: Build adaptive, distributed AI frameworks for real-time emergency decision-making.
Research Experience
Postdoctoral Research Associate
Princeton University - NJ
Sept 2024 – Present
Investigating bias mitigation in large language models using causal inference and adversarial training
Collaborating with social scientists to assess real-world impact of AI-generated content on public discourse
Published 2 papers in ACL and FAccT; awarded Best Paper Honorable Mention at FAccT 2025
Graduate Research Assistant
Swarthmore NLP Lab - PA
June 2019 – May 2024
Developed lightweight transformer architectures for low-resource language understanding
Introduced a novel data augmentation technique using backtranslation and syntactic perturbation, improving model accuracy by 18% on underrepresented dialects
Advised 3 undergraduate researchers; co-supervised 1 senior thesis project
Published in top-tier venues: ACL 2023, EMNLP 2022, NAACL 2021
Undergraduate Research Intern
MIT CSAIL- Cambridge, MA
May 2017 – Aug 2017
Built a prototype voice assistant for non-native English speakers using phonetic error modelingg
Collected and annotated a dataset of 5,000 utterances across 8 language backgrounds
Results presented at Interspeech 2017 (co-author)
Publications
Peer-Reviewed Conferences
Kim, J., Thompson, R. (2023). Efficient Adaptation of Pretrained Language Models via Gradient Pruning. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023). Read Here...
Kim, J., Liu, Z., Patel, A. (2022). Cross-Lingual Transfer Learning with Syntactic Guidance. In Empirical Methods in Natural Language Processing (EMNLP 2022). Read Here...
Kim, J., et al. (2021). Few-Shot Intent Detection Using Semantic Priors. In North American Chapter of the ACL (NAACL 2021). Read Here...
Workshops & Posters
Kim, J. (2022). Ethical Challenges in Deploying Multilingual Chatbots. ACL Ethics in NLP Workshop. Read Here...
Kim, J., Chen, L. (2020). Modeling Code-Switching in Bilingual Conversations. Workshop on Computational Modeling of Multilingualism. Read Here...
Teaching Experience
Lecturer & Teaching Assistant
Swarthmore College
Artificial Intelligence (CS 65)
Fall 2021, Spring 2023
Led weekly discussion sections, designed homework assignments and lab exercises on search, logic, and probabilistic reasoning
Mentored 6 final projects on topics including NLP for mental health and AI ethics
Guest Lecturer
Haverford College – Science Program
Computational Linguistics Seminar
Spring 2022
Delivered lecture on “Neural Approaches to Morphology and Syntax”
Facilitated student discussion on recent papers from TACL and CL
Projects
LowResourceNLP Toolkit
Jan 2021 – Present
Open-source Python library for training NLP models on datasets with fewer than 1,000 labeled examples
Integrated with Hugging Face Transformers; adopted by researchers in 12+ countries
BiasBench
Aug 2023 – Dec 2023
Benchmark suite for evaluating gender and racial bias in language generation models
Supported 15+ models including Llama-2, Mistral, and GPT-NeoX
Used in academic studies and industry audits
Additional
Grants & Awards: NSF Graduate Research Fellowship (2020), Swarthmore AI Research Grant (2022), ACL Best Demo Paper Nominee (2023)
Skills: Python, PyTorch, Hugging Face, LaTeX, Git, AWS/GCP, SPSS, R
Languages: English (native), Korean (professional proficiency), Spanish (basic)
Professional Service: Reviewer for ACL, EMNLP, TACL; Mentor in Women in NLP program
Affiliations: ACM, AAAI, Association for Computational Linguistics (ACL)
*References available upon request.
Dr. Rebecca Thompson
Professor of Computer Science
Swarthmore College
P: (123) 456-7890
E: rthompson@swarthmore.edu
Prof. David Wu
Department of Linguistics
Stanford University
P: (123) 456-7890
E: dwu@stanford.edu
Dr. Anna Patel
Senior Research Scientist
Allen Institute for AI (AI2)
P: (123) 456-7890
E: anna.patel@allenai.org