WELCOME TO

S3 LAB

Sustainable, Smart, and Efficient Systems Laboratory

@ Algoma University

Introduction

My research group investigates efficiency, scalability, and sustainability in modern computing and cyber-physical systems. By developing rigorous methodologies to quantify and reduce energy consumption and carbon footprint, our work aims to enable sustainable system operation and support the transition toward net-zero emissions by 2050.

Principal Investigator

Syed Muhammad Danish

Syed Muhammad Danish is an Assistant Professor at Algoma University. Previously, he was a postdoctoral researcher and lecturer at York University under the supervision of Prof. Sotirios Liaskos. He received his Ph.D. from ETS Montreal in August 2022, advised by Prof. Kaiwen Zhang and co-advised by Prof. Hans-Arno Jacobsen. Prior to joining ETS Montreal, he served as a research assistant at Frederick University, Cyprus, under the Erasmus+ project. His research focuses on sustainable and intelligent systems, spanning green energy, blockchain technologies, and energy-efficient AI.

Current Students

MSc Thesis
Oussema Kirmani – Analyzing the Sustainability of LLMs
MSc Thesis
Sabiya Banu Masthan Ali – Benchmarking the Energy Consumption of LLMs

Former Students

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Shadikur Rahman – Research Assistant
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Umme Aiman Koana – Research Assistant
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Humza Ashraf – Research Assistant
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Muhammad Kaleem Ullah Khan – Research Assistant

Research Publications

For a complete list of my research output, please visit my Google Scholar profile. A selection of recent publications is listed below.

FedHAT: Resource-Aware Hybrid Federated Adversarial Training for Generalized Robustness — Submitted
Assessing the Sustainability of LLM Inference through Energy–Accuracy Analysis — Submitted
Efficient Federated LLM Framework for Intelligent IoMT Management — Submitted
Digital Payments on Infrastructure-less Networks: A Systematic Literature Review — Submitted
ARIES-6G: Aerial Resource Allocation and Trajectory Integration in RIS-UAV-Enabled ISAC for URLLC in Industrial 6G Networks — Submitted
RefactorCoderQA: Benchmarking LLMs for Multi-Domain Coding Question Solutions in Cloud and Edge Deployment — Submitted
Aligning Pre-Trained LLMs for Enhanced UAV Power Consumption Forecasting — Accepted at IEEE Globecom 2025
Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming — IEEE FLLM 2025
Toward Green Code: Prompting Small Language Models for Energy-Efficient Code Generation — IEEE FLLM 2025
Automated Research Article Classification and Recommendation Using NLP and ML — IEEE FLLM 2025
Scaling Smart: A Rigorous Framework for Selecting Optimal Layer 2 Blockchain Solutions — IEEE Brains 2025
Privacy-Preserving Energy Trading: A TEE-Based Blockchain Solution Using Secret Network — ACM BSCI 2025
Zero SolarWing: A net-Zero Solar Wind-Powered UAV-Enabled RIS System for URLLC Services in 6G Compute First Networks — IEEE Transactions on Consumer Electronics 2025
Block-FeST: Blockchain-Enhanced Federated Sparse Transformers for Privacy-Preserving RES Forecasting in Internet of Vehicles Systems — IEEE Internet of Things Journal 2025
Blockchain-as-a-Service: Architecture, Opportunities and Challenges — IEEE Internet of Things Magazine 2024
Generating Secure Workflow Designs from Requirements Goal Models Using Patterns — ER Conceptual Modelling Conference 2024 (Core A)
A Blockchain-Based Privacy-Preserving Charging Station Reservation and Payment Scheme for Electric Vehicles — ACM Distributed Ledger Technologies Journal
Block-FeDL: Electric vehicle charging load forecasting using federated learning and blockchain — IEEE Transactions on Vehicular Technology 2024
Blockchain for energy credits and certificates: a comprehensive review — IEEE Transactions on Sustainable Computing 2024 (Work with Hydro-Quebec)
BlockAIM: a neural network-based intelligent middleware for large-scale IoT data placement decisions — IEEE Transactions on Mobile Computing 2022
BlockEV: Efficient and secure charging station selection for electric vehicles — IEEE Transactions on Intelligent Transportation Systems 2021
BlockAM: An adaptive middleware for intelligent data storage selection for Internet of Things — IEEE DAPPS 2020 (Best Paper Award)
Network intrusion detection system for jamming attack in lorawan join procedure — IEEE ICC 2018

View all papers on Google Scholar →

Teaching

Graduate

• COSC5806: Data Analysis with Python

• COSC5856: Intro to Cybersecurity

• COSC5437: Neural Networks & Deep Learning

Undergraduate

• COSC1047: Computer Science II

• COSC3796: IT Security & Privacy

• COSC2956: Internet Tools

Prospective Students

If you are interested, please send an email with your CV and Transcript to syed.danish@algomau.ca

Visit my YouTube Channel for Web3 & Blockchain tutorials.