Sardar.
Kanvis
Sardar Ali Maqsood

Sardar Ali Maqsood

MS AI | Research Assistant at 7BOT | Expert in Edge AI, RAG & Time-Series Forecasting
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Overview

Research Assistant and MS AI candidate with a background in Electrical Engineering, specializing in the intersection of AI and hardware. Proven track record in deploying high-accuracy (97-98%) models on edge devices (ESP32) and developing intelligent optimization systems that reduce energy costs by up to 40%. Experienced in building offline RAG pipelines with Llama 3.2 and conducting advanced research in time-series forecasting and low-resource NLP.
Rawalpindi, Pakistan

Experience

Feb 2025

WORK

Independent Researcher

Self-Directed Research
Developing an intelligent home energy management system that combines forecasting and optimization for cost-aware scheduling. Designing time-series forecasting workflows for load and price prediction using LSTM and GRU-based models. Conducting low-resource NLP experiments, including transformer-based Akkadian-to-English translation. Building reproducible research pipelines in Python and PyTorch for preprocessing, training, evaluation, and ablation analysis.
•Developing an intelligent home energy management system that combines forecasting and optimization for cost-aware scheduling.
•Designing time-series forecasting workflows for load and price prediction using LSTM and GRU-based models.
•Conducting low-resource NLP experiments, including transformer-based Akkadian-to-English translation.
•Building reproducible research pipelines in Python and PyTorch for preprocessing, training, evaluation, and ablation analysis.

Key Achievements

→Reduced household electricity costs by 30-40% through intelligent appliance scheduling and peak-power optimization.
→Achieved a high prediction accuracy with an R-squared (R²) score of 0.94 using LSTM-based forecasting models for load and price prediction.
→Achieved a BLEU score of 38% on an Akkadian-to-English translation task using a dataset of 12,000 samples (8,000 training, 4,000 test) in a Kaggle competition.
PythonPyTorchLSTMGRUTransformersNLP

Feb 2024 – Mar 2025

WORK

Research Assistant

7BOT Technologies – NSTP
Developed a smart health monitoring watch for elderly care with real-time sensor processing and alert logic. Designed an intelligent air purifier with automated air-quality detection and adaptive control. Deployed an object classification model on edge devices for real-time inference.
•Developed a smart health monitoring watch for elderly care with real-time sensor processing and alert logic.
•Designed an intelligent air purifier with automated air-quality detection and adaptive control.
•Deployed an object classification model on edge devices for real-time inference.

Key Achievements

→Achieved 97-98% accuracy (within 2-3% of medical-grade appliances) for health monitoring metrics like BP and temperature through rigorous sensor calibration.
→Successfully deployed classification models on ESP32 microcontrollers using infrared MEMS sensors for real-time health monitoring.
ESP32MEMS SensorsInfrared SensorsEdge DevicesObject ClassificationSensor Processing

Mar 2023 – Feb 2024

WORK

Computer Science Teacher

College
Taught computing fundamentals, networking, software engineering, databases, and programming. Guided students through Python-based projects, basic data analysis, and problem-solving exercises.
•Taught computing fundamentals, networking, software engineering, databases, and programming.
•Guided students through Python-based projects, basic data analysis, and problem-solving exercises.

Key Achievements

→Successfully taught C, C++, and Python programming to intermediate-level students, adapting complex technical concepts for early learners.
→Developed a personalized teaching methodology, tailoring explanations and project difficulty to individual student learning styles and paces.
→Simplified abstract concepts like recursion and control structures (if-else, loops) through real-world analogies and iterative examples, helping students overcome common logic hurdles.
C++CPythonMentoringCurriculum Delivery

Project Portfolio

PERSONAL

Present

Offline Secure RAG System

Lead Developer

Developed a fully offline Retrieval-Augmented Generation (RAG) pipeline using Llama 3.2 (1B) and LangChain for privacy-sensitive environments. Integrated ChromaDB for efficient document retrieval, ensuring high reliability and authenticity by grounding model responses in local data.
Llama 3.2 1BLangChainChromaDBPython

Education

2024 – 2026

MS in Artificial Intelligence

Air University, IslamabadSpecialization in Artificial Intelligence
Thesis: Intelligent HEMS Optimization: Integrating Advanced Deep Learning Models with Adaptive Scheduling

Relevant Coursework

Machine LearningDeep LearningComputer VisionNLPLLMsRAG

2018 – 2023

BS in Electrical Engineering

COMSATS University IslamabadSpecialization in Electrical Engineering

Relevant Coursework

Signal processingcontrolprogrammingembedded systemsapplied machine learning

Skills & Interests

NLP

Time-Series Forecasting

Machine Learning

Python

PyTorch

NumPy

Pandas

Retrieval-Augmented Generation

Optimization

Agentic AI

Model Evaluation

Data Preprocessing

LLM Fine-Tuning

Scikit-learn

Prompt Engineering

Transformers

Matplotlib

Jupyter

Information Retrieval

Keras

Git

Semantic Search

TensorFlow

C++

Flask

Areas of Expertise

Learning Speed

Experimentation

Implementation Ability

Communication

Working across multiple languages, enabling global collaboration and clear technical outreach.

Urdu
English

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