Portfolio
HELLO MY NAME IS
MOAZ.
AND I AM AN AI ENGINEER.
ABOUT ME
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I am a Computer Science graduate from Riphah International University, deeply passionate about leveraging technology to create impactful solutions. With a strong foundation in computer science, I have developed a keen interest in emerging technologies and innovative problem-solving. My journey in tech has been defined by a relentless curiosity and a commitment to continuous growth. Known for my eagerness to learn and adaptability, I thrive in fast-paced environments where I can quickly assimilate new concepts and apply them effectively. My hands-on experience spans diverse projects, from developing intelligent systems to optimizing real-time applications
SKILLS
Core AI & Machine Learning Skills
✅ Machine Learning (ML): Supervised, unsupervised, reinforcement learning ✅ Deep Learning (DL): CNNs, RNNs, LSTMs, Transformers (e.g., GPT, BERT) ✅ Natural Language Processing (NLP): Tokenization, embeddings, LLMs, chatbots
✅ Computer Vision: Object detection, image segmentation, GANs, image-to-3D
✅ Recommendation Systems: Collaborative filtering, content-based filtering
Programming & Software Engineering
✅ Python: TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas
✅ SQL & NoSQL Databases: PostgreSQL, MongoDB, Redis, vector databases (e.g., FAISS)
✅ Software Development Practices: Git, CI/CD, containerization (Docker, Kubernetes)
Data Engineering & Cloud Computing
✅ Big Data Frameworks: Databricks – Expertise in Apache Spark, PySpark, and ETL pipelines for large-scale data processing.
✅ Cloud Platforms: AWS & Azure ML – Experience in deploying AI/ML models using AWS SageMaker, Azure ML, and cloud-based MLOps.
✅ Feature Engineering: Data Preprocessing & Dimensionality Reduction – Skilled in data cleaning, transformation, PCA, and t-SNE for optimized model performance.
Generative AI & Advanced AI Models
✅ LLMs & Multi-Modal AI: GPT-4, Llama, Stable Diffusion, Audio & Video models
✅ Autonomous Agents & AI Agents: LangChain
✅ Prompt Engineering: Optimizing LLM interactions
✅ Synthetic Data Generation: GANs, Diffusion models
Riphah International University
Embarking on a four-year Computer Science program offers students an in-depth exploration of core concepts, advanced theories, and emerging technologies.
BS - Computer Sciences
Oct 2020 - Jul 2024
EDUCATION & EXPERIENCE
In my role as an AI Engineer, I am responsible for developing projects involving Large Language Models (LLMs), RAG’’S, Computer Vision, and Big Data. A key highlight of my work includes the AI automation of renewable energy data utilizing Azure Databricks
AI Engineer - Megasight.ai
Aug 2024 - Current
Mikrostar Tech
Worked as a Data Scientist for more than a year, developed AI models for IOT and Computer Vision data.
Apr 2022-Jun 2024
Data Scientist
1 year of experience in the embedded system engineering, writing embedded C\C++ code for MCU’s & SOC’s.
Embedded Software Engineer
PROJECTS
Clonatomy
Scope: Generative AI
Description
Clonatomy is an advanced AI-powered digital twin technology that transforms human photos into lifelike AI avatars and clones voices with precision. By integrating deep learning, generative AI, and speech synthesis, Clonatomy creates interactive, talkative avatars capable of real-time communication. These AI humans can engage in conversations, express emotions, and adapt their responses based on context.
Impact
Clonatomy enhances digital interaction by providing hyper-realistic AI avatars that personalize communication and engagement. It redefines virtual assistants, making them more intuitive and human-like, improving accessibility,
Time by DRH
Scope: MedTech
Description
We are developing a secure MedTech solution that records and encrypts doctor-patient consultations, ensuring data privacy. Advanced speech-to-text technology transcribes conversations, and LLMs generate structured medical notes. These records are securely stored for documentation, follow-ups, and compliance. The solution streamlines medical documentation, allowing doctors to focus on patient care.
Impact
This solution enhances patient care by reducing administrative burdens on doctors, allowing them to focus more on patients. It improves medical documentation accuracy, ensures compliance, and strengthens data security, leading to better healthcare outcomes and efficiency.
Scope: Data Engineering
Renewable Energy Analytics
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Description
I was working on a big data project for renewable energy, including solar, wind, and reverse osmosis water systems. We receive parquet files, process them in Databricks, and perform visualizations to extract insights. Additionally, we apply machine learning to detect clogged or clean inverters and identify errors causing energy losses. This helps optimize energy production and system efficiency.
Impact
The project enhances renewable energy efficiency by identifying faults and preventing energy losses. It improves system reliability, reduces maintenance costs, and supports sustainable energy generation.
Palarum
Scope: MedTech
Description
I worked on Palarum's AI model, which utilizes smart socks embedded with pressure sensors and accelerometers. We received sensor data in Excel files and developed an AI model to determine whether a person is standing or sitting based on the collected data. The model processes and analyzes real-time pressure and motion patterns to classify postures accurately. This project involved data preprocessing, feature engineering, and training machine learning algorithms to enhance detection accuracy.
Impact
The AI model improves patient monitoring and mobility assessment, particularly in healthcare settings. It enhances fall prevention strategies, assists in rehabilitation, and provides valuable insights for caregivers and medical professionals.