About
I am a Ph.D. candidate in Computer Science at the New Jersey Institute of Technology (NJIT), with 4+ years of research experience in machine learning and artificial intelligence. My work spans federated learning, large language models, LLM fine-tuning, and combinatorial optimization algorithms. I have published at top-tier venues including ICLR and AAAI.
Education
Selected Publications
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[1]
FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous EnvironmentsICLR 2026 International Conference on Learning Representations, 2026📄 PDF
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[2]
Spark: Smart Building Fire Prediction and Risk AnalysisIEEE NCA 2025 IEEE International Symposium on Network Computing and Applications, 2025📄 PDF
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[3]
Equity Promotion in Public TransportationAAAI 2023 AAAI Conference on Artificial Intelligence, 2023📄 PDF
Selected Projects
NL2SQL Using LLMs
Text-to-SQL system resolving database and query ambiguity by decomposing SQL generation into subtasks. Deployed on GPU-based HPC with open-source LLMs (Qwen-7B, OSS-20B, OSS-120B) via Hugging Face Transformers; uses custom prompt engineering and model fine-tuning.
Federated Learning in Heterogeneous Environments
Clustered FL pipeline in PyTorch with non-IID data; incorporates SVD-based feature extraction, entropy-optimized MLP, dual-encoder with cross-cluster representation sharing, hierarchical clustering with adaptive thresholds, and a novel federated-aware evaluation metric.
Transportation Equity Optimization
Budget-allocation optimizer using LP-based rounding and bipartite matching to maximize equity across 5 demographic groups in Chicago; integrates ride-hailing and bus-line programs (17,875 households, 649 bus stops, 20 candidate routes).
Smart Building Fire Risk Analytics
Sensor-driven graph-diffusion framework combining static, dynamic (drone), and human sensor streams with weighted multimodal fusion; builds room adjacency graphs modeling structural and HVAC connectivity; applies k-means for real-time risk-zone classification.