PhD in Computer Science, University of Missouri-Kansas City, 2024
B.Sc. in Computer Science and Engineering, Bangladesh University of Engineering and Technology, 2017 (CGPA: 3.81/4, Rank: 17/131)
HSC in Science, Viqarunnisa Noon College, 2011 (GPA: 5/5)
SSC in Science, Viqarunnisa Noon School, 2009 (GPA: 5/5)
Sunday and Tuesday: 1:30-2:30 pm
Tuesday: 6-9 pm
Thursday: 11-1 pm
Monday and Wednesday: 1:00-2:30 pm
Biography
Dr. Sumaiya Tabassum Nimi is a computer science researcher and educator with deep expertise in machine learning, deep learning for resource-constrained environments, and few-shot/generalization-oriented learning. She earned her PhD in Computer Science from the University of Missouri–Kansas City, where her research led to several high-impact publications on neural network optimization, out-of-distribution (OOD) detection, and edge–cloud collaborative AI systems.
In 2026, she serves as a WiDS (Women in Data Science) Ambassador with Stanford University, contributing to global leadership, outreach, and advocacy efforts that promote inclusive excellence in data science research and education. Her current research agenda is centered on quantum machine learning, with a focus on hybrid classical–quantum models and quantum-enhanced representation learning. She actively collaborates with the QC3 Lab, where her work explores theoretically grounded and application-driven quantum-inspired and quantum-assisted learning frameworks that bridge foundational quantum principles with real-world AI systems. She also maintains ongoing research collaborations with the Bangladesh University of Engineering and Technology (BUET), fostering interdisciplinary work and mentoring student-led research initiatives.
With over seven years of university teaching experience, including her current role as an Assistant Professor at North South University, Dr. Nimi integrates theoretical rigor with applied research and real-world impact. Her scholarly interests increasingly lie at the intersection of computation and physics, reflecting a strong commitment to interdisciplinary and future-forward AI research.
She is the founder and lead of the QuICK (Quantum-mechanics-guided Intelligent Computation for Knowledge-based systems) Research Group, where she advocates for research-driven learning and mentorship. She has taught and supervised advanced topics in statistical learning, big data analytics, and intelligent systems, and brings a distinctive blend of academic leadership, applied machine learning expertise, and curiosity-driven innovation to her work.
Research Group: https://sumtamnimi.wixsite.com/questlab
LinkedIn Research Group: https://www.linkedin.com/groups/14619021/
Research Areas
Research Interests
Quantum Machine Learning
Molecular Machine Learning
Edge Computing
Computer Vision
Recommender Systems
Teaching
Research Projects & Grants
| Organization | Title of consultancy/ research project | Amount Received, if any (BDT) | Year |
| CTRG NSU 2026-27 |
Split Federated Learning with UAV-Assisted Hybrid Classical-Quantum Neural Networks for Medical Imaging
|
6, 27, 300 | 2026 |
| IAR UIU |
Quantum-Assisted Deep Learning: Addressing the Generalization and Adaptation Challenges associated with Dynamic Model Deployment
|
5,00,000 | 2025
|
| UMKC Women’s Council | Towards Intelligent deep learning model synthesis for dynamic domain-constrained deployment scenario | 250,000 | 2023 |
| School of Graduate Studies, UMKC | Towards making Edge Devices Intelligent through Deployable Model Synthesis | 800,000 | 2022 |
| UMKC Women’s Council | Towards developing deployable multi-tasking deep learning model generation for device-edge collaborative inference | 300,000 | 2022 |
| UMKC Women’s Council | Towards deep learning model synthesis for Activity recognition using Smartwatches | 150,000 | 2021 |