Arslaan Hamza M. Email and Phone Number

Developed multitask models to extract various features such as body pose, furniture segmentation, face detection, and body action recognition. Additionally, I designed and implemented pipelines to streamline the data labeling and training processes.Developed multitask deep learning models to extract features from images and videos, including:Body Pose Estimation: Identifying and analysing human body positions.Furniture Segmentation: Segmenting and distinguishing furniture from other objects.Face Detection: Detecting and localizing faces in images or video streams.Body Action Recognition: Recognizing and interpreting human actions and movements.Designed pipelines to efficiently manage data workflows, from initial collection to final model training.Implemented systems to send data to be labelled by third-party contractors and in-house tools, accelerating the labeling process.Automated the training process, ensuring models are updated regularly with new data.Utilized various tools and technologies to support these processes, including:PostgreSQL for data storage and management.FastAPI for building efficient APIs to handle data processing and integration.Label Studio for data labeling and annotation.Kafka for managing and processing data streams through events.

Managed hardware provisioning in hospitals, including installation and setup of IT equipment.Integrated new hardware into existing hospital systems and networks, ensuring compatibility.Coordinated with hospital IT teams to implement secure connections for IT devices.Oversaw inventory management of IT and medical hardware, ensuring compliance.Implemented and maintained security protocols to protect patient data.Provided technical support and troubleshooting for hardware-related issues.Liaised with vendors to procure equipment and services, ensuring timely delivery.Documented hardware configurations and operational procedures for record-keeping.

I managed all aspects of the engineering organization, including mentoring, hiring, architectural design, and technical support.Contributions:Led the development of an end-to-end pipeline from scratch, capable of processing 250 million events per month related to patient care.Collaborated on the pipeline design and built initial versions of edge applications using Nvidia DeepStream.Developed applications that connected standard IP cameras, decoded video streams, and efficiently ran multiple deep learning models.Implemented a system to publish features extracted by these models to the cloud, where lightweight models performed real-time inferences.Technologies and Tools Used:Nvidia DeepStream SDK for edge applications.Pytorch for Deep Learning.PostgresqlKafka events (Azure EventsHub) for processing and inference.

I developed various deep learning predictors to analyze human facial features such as gender, emotion, and age. These models provide valuable metrics for various hotels to enhance their customer experience and operational efficiency.Contributions:Built and trained deep learning models to accurately analyze and predict facial features including gender, emotion, and age.Utilized technologies such as Python3, TensorFlow, Keras, and NumPy to develop and optimize these predictors.Generated metrics that assist hotels in understanding and responding to customer demographics and emotional states.Technologies and Tools Used:Python3 for programming.TensorFlow and Keras for developing and training deep learning models.NumPy for numerical computations.FastAPI for REST api development

Used React to build dynamic user interfaces, D3 to create data visualizations, and RxJS to manage asynchronous data streams.Configured the Continuous Integration (CI) environment to automate builds and run end-to-end (e2e) tests.Developed Kubernetes configurations to deploy custom Docker containers with Nginx-based setups.This version is tailored to present your contributions and technical skills effectively in the first person.

I worked in various roles including Firmware Technician, Assistant Electronic Engineer, and Senior Programmer. Below are some of the key projects I contributed to during this time:Affectivo Band Firmware (Horizon 2020 Grant)I dedicated a significant portion of my time to the Horizon 2020 project, focusing on the development of firmware for a smart wristband. This wristband used four sensors (temperature, Electrodermal Activity (EDA), motion and photoplethysmography) to infer the emotional state and stress levels of the user. The collected data is transmitted via Bluetooth Low Energy (BLE) to a mobile device and then to the cloud, where machine learning and deep learning techniques are applied to analyze the emotional state of the user.Key Contributions:Designed and implemented a Bluetooth communication protocol to transmit real-time sensor data from the wristband to a mobile device using BLE.Developed a system to store sensor data in internal FLASH memory when the mobile device was not present.Handled the capture of sensor signals on the wristband using i2c and SPI protocols.Created Linux scripts to automate weekly firmware compilation on a server, generating .txt files as the source code repositories were updated.Integrated Unity for firmware development to follow best practices like Test-Driven Development (TDD).Technologies Used:C LanguageCode Composer StudioGit (version control)Jenkins (server task manager)

Developed an Android native Java SDK to communicate a wearable Band through a BLE interface with an in house communication protocol. For this project I used mainly Java 8 (through rotrolambda), RXJava core libraries, Dagger 2, Junit and Mockito for testing.

· Developed firmware for a wearable capable of detecting human emotions (based in pure C). Unit tested with Unity framework for embedded devices.· Create communication framework in Android for a BLE device using reactive programming (RX Java), dependency injection (Dagger2) and unit tests with Robolectric.

Developing a complete Android app for 3-7 years old students. Used clean architecture methodologies like MVP, dependency injection with Dagger, reactive programming (RX Java), unit testing with Robolectric, Espresso and mocks with Mockito.

• Building a continuous integration system to test Android apps in order to check if there were using correctly the tools provided by Infantium. For this project I used Python, Django, Virtual Machines as Genymotion in the backend, ReactJS and Flux Architecture for the frontend

Creating a public and private API to manage air high volume shipments using Ruby on Rails. My tasks were to decode FFM/FSU messages and parse them in the db. Also decoding SSIM messages to create flights schedules and finally create and connect different models to be able route shipments through different countries

As an Ironhack student, I am formally learning a full suite of frontend development tools, programming methodologies (mostly TDD) and testing tools. After 8 weeks of intensive training and practical exercises, we will be using HTML5, CSS3 alongside Javascript (including JQuery). Our back-end code is built cleanly using Git, Ruby on Rails and Test Driven Development. After becoming familiar with the principles of pair programming, we will produce a real web product.

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2 weeks at Argo program where i learnt how a bussiness works and i accquired the basics skills to start my " Java and QR codes " project.