Dr. Sameer Qadir, PhD
Associate Professor of Computer Science & AI Systems
Department of Computer Science & Engineering
National Institute of Computational Innovation (NICI)
San Diego, CA
sameerqadir.academi.site
sameer.qadir@nici.edu
321 654 7890
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
Research Interests & Stats
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
AI for social good and responsible innovation
Federated and embedded machine learning
Publication Stats
Journal Articles
24
Conference Papers
38
Book Chapters
5
Citations
1240+
Latest Publications (Highlights)
Research Projects
Active
Real-Time AI Infrastructure for Emergency Response (RAID)'
Developing a scalable AI platform to analyze live data streams (video, sensor, social media) for disaster management teams.
Funded by National Science Foundation (NSF), Portal Link
Planning
Robustness in Autonomous Systems
Investigating methods to make AI-driven systems (cars, drones) more resilient to unexpected real-world conditions and adversarial attacks.
Funded by Defense Advanced Research Projects Agency (DARPA), Portal Link
Completed
Low-Latency ML on Edge Devices
A project focused on optimizing machine learning models to run efficiently on low-power hardware for IoT applications.
Internal University Grant, Portal Link
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
Sept 2024 – Present
Postdoctoral Research Associate
Swarthmore NLP Lab - PA
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
June 2019 – May 2024
Graduate Research Assistant
Princeton University - NJÂ
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
Teaching Experience
Fall 2022 -
Spring 2023
Lecturer & Teaching Assistant
Swarthmore College
Artificial Intelligence (CS 65)
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
Spring 2021 -
Fall 2022
Guest Lecturer
Haverford College – Science Program
Computational Linguistics Seminar
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
Projects
Publication List
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...
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)
© 2025 Dr. Qadir. All Rights Reserved.