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
Undergrad
Caleb Nathan Elvis Mohan – Analyzing the Sustainability of LLMs - Funded by NSERC USRA
Undergrad
Molka Chkir – Profiling Transformer Layers in LLMs - Funded by Mitacs GRI
Undergrad
Muneeb Haroon – Profiling Transformer Layers in LLMs - Funded by Mitacs GRI
Undergrad
Salsabeel Fatima Zahra – Benchmarking Code Generation Performance of Large Language Models - Funded by Mitacs GRI

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.

Assessing the Sustainability of LLM Inference through Energy–Accuracy AnalysisAccepted at ACM e-Energy 2026
Efficient Federated LLM Framework for Intelligent IoMT ManagementAccepted at IEEE Transactions on Consumer Electronics 2026
FedHAT: Resource-Aware Hybrid Federated Adversarial Training for Generalized RobustnessSubmitted
Digital Payments on Infrastructure-less Networks: A Systematic Literature ReviewSubmitted
ARIES-6G: Aerial Resource Allocation and Trajectory Integration in RIS-UAV-Enabled ISAC for URLLC in Industrial 6G NetworksSubmitted
MERIT: UAV-Assisted MEC-Enabled Resource Integration and Trajectory Optimization for Energy-Efficient URLLC NetworksSubmitted
Generating Secure Workflow Designs from Requirements Goal Models Using PatternsER Conceptual Modelling Conference 2024 (Core A)
Blockchain for energy credits and certificates: a comprehensive reviewIEEE Transactions on Sustainable Computing 2024 (Work with Hydro-Quebec)
BlockEV: Efficient and secure charging station selection for electric vehiclesIEEE Transactions on Intelligent Transportation Systems 2021

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.