BS Computer Science (Graduation with Merit / Cum Laude)
Relevant Coursework: Networks and Systems, Data Structures/Algorithms, Software Engineering, Operating Systems, Databases, AI & ML, Natural Language Processing.
Computer Science Researcher | Systems, Networks, HCI & AI
Karachi, Pakistan
Download CVComputer Science researcher and LUMS alumnus specializing in the intersection of Systems, Networks, Human-Computer Interaction, and Artificial Intelligence. Sole author of an IEEE-published paper on transport-layer scheduling and a comprehensive preprint on MLSys and decentralized consensus. Proven ability to engineer low-level protocols (C++, ns-3) and architect scalable, rigorous AI evaluation pipelines (Python, DSPy). Currently utilizing a gap year in enterprise cybersecurity to study the practical constraints, threat models, and operational bottlenecks of large-scale distributed systems. Eager to bring this blend of theoretical rigor and real-world systems perspective to complex, cross-cutting problems in a top-tier graduate research group.
Computer Networks, Distributed Systems Architecture, Systems Programming, Human-Computer Interaction, and Artificial Intelligence.
Relevant Coursework: Networks and Systems, Data Structures/Algorithms, Software Engineering, Operating Systems, Databases, AI & ML, Natural Language Processing.
S. M. A. Rizvi. “The Cognitive Penalty: Ablating System 1 and System 2 Reasoning in Edge-Native SLMs for Decentralized Consensus.” Working Paper.
S. M. A. Rizvi. “A Case for CATS: A Conductor-driven Asymmetric Transport Scheme for Semantic Prioritization.” Proceedings of the 6th International Conference on Innovative Computing (ICIC 2025). Published in IEEE Xplore.
S. M. A. Rizvi. “A Literature Review of Keyword Spotting Technologies for Urdu.” Technical Report.
S. M. A. Rizvi. “Interactive Semantic Video Seeking—ISVS: A Proposed Architecture and Research Roadmap for Non-Linear Media Navigation” Working Paper.
Conducting independent, cross-layer computer science research involving Distributed Systems, Computer Networks, HCI, and AI. Focused on empirical benchmarking, low-level protocol optimization, and publishing findings.