Muhammad Ammar
Data Analytics Researcher @ Siemens | MSc Electromobility-ACES @ FAU | BSc Mechanical Engineer @ NUST
About
Pursuing an MSc in Electromobility-ACES at Friedrich-Alexander-Universität Erlangen-Nürnberg, I am currently working as a working student in Data Analytics Research at Siemens. My current work revolves around utilizing GenAI to measure software ecosystem health via graph analytics. More specifically, I am building applications that allow the user to conduct graph analytics just by providing queries in natural language.
Work Experience
Siemens AGErlangenHybrid
Data Analytics Researcher - Working Student
NeuroOceans AIRemote
Machine Learning Engineer
Learners.aiRemote
Solution Analyst
Undergraduate Researcher
Education
Friedrich-Alexander-Universität Erlangen-Nürnberg
National University of Sciences and Technology
Skills
Projects
Autonomous Mobile Robot
A Chain-Driven Live Roller Mechanism for Loading and Unloading Packages on Autonomous Mobile Robots in Warehouses
Image2Audio app
Users upload an image, the app generates a caption for the image, creates a short story based on the caption, and then converts the story into audio format.
Q&A Chatbot on private data
Blogpost on Retrieval Augmented Generation (RAG) using ChromaDB, GPT wrapped around LangChain, and private data.
Scene Classification
Finetuned ViT pre-trained on ImageNet for Kaggle Intel Classification Challenge.
Podcast Summarizer
Converts podcast audio to text using whisper, uses GPT-3.5 to generate a summary, and uses wikipedia API to display additional information.
Transfer Learning with PyTorch
Scene classification by fine-tuning pre-trained Vision Transformers (ViT) guide.
Courses
Machine Learning Specialization by DeepLearning.AI
Introduces foundational ML concepts. Covers everything from data analytics using pandas to classification using Neural Nets.
Natural Language Processing Specialization by DeepLearning.AI
Deep Dive into NLP. Starts from Classification and Vector spaces, coverts probabilistic models, and eventually moves on to Deep Neural Nets.
PyTorch for Deep Learning by Zero-to-Mastery
Complete guide to PyTorch from the fundamentals. Covers everything from the basics to building a Vision Transformer from scratch.
Generative AI with Large Language Models by DeepLearning.AI
Covers LLMs for text generation, from pre-training to instruction fine-tuning to RLHF.
Robotics: Aerial Robotics by UPenn
Mechanics of flight and design of quadrotors flying robots. Control and Planning for three dimensional flights.
ROS2 For Beginners (ROS Foxy, Humble - 2024)
Programming fundamentals of Robot Operating System 2 (ROS2) in Python.
Press ⌘J to open the command menu