Dr. Heiner Di Camillo
Software Solutions, Data Engineering and AI
I am happy to serve with my knowledge and experience
Data Driven Development
Test Driven Development
DevOps and CI/CD
Cross Platform Development
HTML, CSS, PHP
I have extensive experience with these frameworks
Spring, .NET, Firebase, NodeJS
MySQL, Postgres, MongoDB
Kafka, Druid, Firestore
Tensorflow, Keras, sklearn
Cloud & Deployment
Kubernetes, Grafana, AWS, GCP, Azure
Jenkins, Gitlab, Github
Frontend and SSR
React, NextJS, React-Native, Flutter, Hugo
Apple App Store, Google Play
I will create software for you and with you
Elevate Your Projects with Expert Development and Architecture
Experience the following advantages when collaborating with me:
- Streamlined Business Logic: Embrace the power of Test Driven Development for managing intricate business logic effectively.
- Robust Architecture: I provide sustainable architecture decisions accompanied by automated architecture tests, facilitating continuous feature development.
- Confident Deployment: Benefit from a stable CI/CD environment that empowers you to make informed business decisions.
Expertise and Communication
- Data Science and Software Development: Seamlessly integrate data science and software development within your team.
- Efficient Communication: Experience clear and relaxed communication alongside focused development skills, optimizing workflow efficiency.
Benefit from my Unparalleled Background and Methodology
Let’s redefine your project’s potential together.
Scientific foundation: I thoroughly analyze complex systems, yielding understandable and dependable solutions. I minimize regression risk for ultra-stable systems.
Agile Collaboration: Drawing from my expertise, I seamlessly collaborate with developers, product owners, and departments. Customizing workflows is my forte, ensuring seamless processes.
Bridging the Gap: I bridge the gap between requirements and practical implementation, enhancing communicative interfaces.
Insightful Enhancements: Anticipating project nuances, I offer cost-effective insights for supplementary features that enrich your project’s value.
Complete App Development
Looking to expand your business through smartphone or web applications?
Benefit from my extensive app development expertise, gained from customer projects and my reference project Ramadama.
I provide a comprehensive package:
- Feature Conceptualization and Design
- User Interface and User Experience Crafting
- Prototyping for Production Readiness
- Collaborative Development Engagement
- Simultaneous Multi-Platform Development (iOS, Android, Web, Windows, MacOS, Linux)
- App Store Publication
- Ongoing Operations and Technical Support
Together, let’s shape the vision and functionality of your app product. Choose between a Fixed Price or my (negotiable) Hourly Rate.
I have worked for customers on these topics
Realtime Anomaly Detection
- Designed and implemented realtime anomaly detection system
- Integrated anomaly notifications within the client's data mesh architecture
Duration: 7 Months and ongoing
Stack: Kafka, Druid, Spring, Java, Python, Kubernetes, Grafana, AWS
In the fast-paced news industry, quick reactions to real-time developments are crucial. Our client, a web publisher, operates within a complex publication structure. Having transitioned from traditional print to online publication, they manage a network of independently branded websites, fed by content from a central editorial office.
Editors require real-time insights into topics’ performance, to push high-performing topics and improve those that are declining. To support editorial decisions, I conceptualized a system to alert editors and relevant staff about anomalies in traffic patterns across different categories. Additionally, technical use cases were implemented to notify about anomalies in traffic sources.
Anomaly detection relied on real-time data from an Apache Druid instance. We employed algorithms that analyzed past data and compared them with forecast estimates. When an anomaly was identified, the report was streamed into a Kafka topic. Downstream services managed push notifications to end-users.
The solution seamlessly integrated into the client’s data mesh architecture. I followed an MVP approach: Product features were iteratively developed in collaboration with end-users. I designed the system for production readiness, incorporating monitoring and alerting through Grafana.
Reinforcement Learning For A Foosball Table Gaming Robot
·Factory Automation Company
- Applied Reinforcement Learning in Unity-Simulation
- Integrated trained AI-agent with hardware
Duration: 15 months
Stack: TensorFlow, Python, Unity, OpenCV, Docker
For a robotic foosball table demo, human players faced off against a robotic contestant. Equipped with industrial-grade motors and actuators, the robot used a camera to monitor the field. My team and I enhanced the robot’s control software using reinforcement learning.
We precisely replicated the foosball table in a Unity simulation. The AI trained itself through continuous self-play in Unity, leveraging the SpinningUp reinforcement learning framework. Our self-developed hardware drivers bridged the gap between AI and real robot table. The AI’s dynamic gameplay even astonished us developers.
I maintained AI complexity with Test Driven Development, using test suites as feature documentation. This approach facilitated smooth onboarding for temporary team members on multiple occasions.
MLOps for Computer Vision in Cloud And Edge Devices
- Developed and deployed Machine Learning Pipelines
- Trained, quantized, and accelerated Deep Learning Computer Vision models
Duration: 12 months
Stack: Python, TensorFlow, Tensorflow Lite, Android, Docker, AWS
A security infrastructure provider created an IoT platform for security cameras, allowing AI models for scene recognition to function as apps. I worked in an interdisciplinary team, researching and developing demo apps for common use cases.
Cloud-based model training and deployment (Python, TensorFlow, Terraform, Docker) laid the foundation. I contributed to the data-driven architecture, crafting scalable machine learning pipelines for inference and re-training feedback loops.
We honed models with quantization for mobile devices’ hardware acceleration (e.g. Qualcomm Hexagon). Quantized (MobileNet) and unquantized models, plus server-side models (e.g. ResNet), underwent performance comparisons.
Deployment occurred within Android-based cameras, acting as the app shell.
Classification Of Anonymized Person Movement Data
- Developed machine learning pipelines for behavior classification
- Employed clustering techniques on multivariate timeseries data
Duration: 3 months
Stack: Python, Scikit-learn
Analyzing anonymized personal movement data from supermarket cameras posed two challenges: data cleaning and behavior classification.
We calculated person movement similarity using dynamic time warping (DTW). For behavior clusters, we applied k-medoids and hierarchical agglomerative clustering on multivariate data. Using cluster centroids as classifier archetypes, our AI prototype accurately classified customer entering and exiting, validated against manual counts.
Our deliverable was a containerizable software suite assessing algorithmic strategy performance.
Assistant AI For A Packaging System
·Supply Chain Manager
- Analyzed and engineered requirements for assistant AI for user input suggestions
- Developed machine learning model for multi-label prediction
Duration: 6 months
Stack: Python, Scikit-learn, SQL
To streamline industrial deliveries, users of the customer system grappled with a complex web-interface. Creating a packaging strategy required numerous repetitive manual steps due to years of feature accumulation that increased software power but sacrificed usability.
My team scrutinized requirements, delivering an AI prototype. We collaborated extensively with various departments, fostering enhanced communication within the customer organization.
Accessing sensitive production data for AI training required a secure pattern involving remote desktop connections and VPN. Our AI employed a random forest classifier with multi-label output. This algorithm learned packaging strategies from past deliveries, suggesting them to users.
The successful AI-POC spurred a production-ready order.
Fullstack and DevOps
Interactive Geopolitical Publications
- Streamlined and expanded service architecture
- Led frontend development and maintained geodata pipeline
Duration: 7 months and ongoing
Stack: React, NextJS, TypeScript, Kubernetes, AWS
My client’s team of data journalists aims to deliver engaging data experiences to readers, especially in mobile browsers. Their goals include providing real-time data on German regional elections and presenting an interactive geopolitical map of Ukraine.
In the dynamic news field, speed to production is paramount. To meet this demand, I merged two artifacts – a create-react-app frontend and a Node.js API—into a single NextJS application. This unified solution serves both React client code and essential data APIs, integrating seamlessly with the higher-level CMS of affiliated news sites.
I introduced a CMS-like feature, enabling editors to publish and embed new data visualizations without developer intervention. This approach reduces costs and organizational complexity.
Some data structures extended from the backend into the frontend, so I created decoupling points to enhance maintainability and extensibility. The streamlined architecture empowers junior developers to add new features with reduced complexity.
Connected Vehicle App
- Architected app's demo mode for millions of users
- Led team and harmonized processes with nearshore colleagues (Romania, Germany)
Duration: 19 months
Stack: Flutter, iOS, Android, TypeScript, .NET, NestJS, Docker, Terraform, REST, Jenkins
Enhancing a Flutter app with a demo mode to showcase its benefits to potential users was our task. Requirements included ensuring features behaved “as if connected to a real vehicle”. However, fragmented feature development led to a lack of a complete development scope. We quickly overcame this by analyzing production UI and existing code.
With a newly-formed team split between Romania and our parent company, communication was vital. My nearshoring expertise facilitated seamless interaction. Building trust through clear architecture documentation bolstered our customer relationships.
As an architect, I restructured the app, allowing parallel development of demo features by individual developers. This loose coupling promoted scalability. Our successful demo mode launch led to us handling more core features. With team growth, I trained new developers, maintained high code quality, and architected new functionalities.
Tariff Ordering System
- Refactored microservice backend architecture and documentation
Duration: 9 months
We assisted the customer in refining the front end’s logic, now backed by testing. This refinement extended to the legacy PHP backend. Through clear architecture and transparent inter-team communication, we relocated misplaced logic to intended services.
Our fully remote team included members from Germany, Hungary, and Egypt. Meanwhile, the customer organization transitioned to SAFe. As a Scrum Master, I guided the team through new processes, helping shape them and emphasizing the significance of CI/CD.
Quality Assurance Framework
- Developed intuitive React-Redux frontend with Material UI
- Designed API and built JavaEE backend
Duration: 12 months
Stack: React, Redux, TypeScript, MaterialUI, Java, JavaEE, JBoss, Gerrit
Operating within the customer’s SAFe framework, our multi-provider team embarked on standardizing a quality management process (9S), featuring a complex status model. To deliver an intuitive user experience, we harnessed Material-UI as the component library of choice.
Our outcome? A functionally-driven React frontend supported by a JavaEE backend. This backend, meticulously designed, retained full test coverage, facilitating agile responses to evolving requirements and streamlined logic patch releases. The beauty? Frontend remained free from business logic, while backend thrived. Our efforts helped navigate change and deliver seamless solutions.
These may serve you as a reference of my app development services
Ramadama - Concept
Let's make some room!
That’s what Ramadama! means in Bavarian.
My app helps you reclaim space at home and find room to breathe.
Whether it’s cherished old armchairs or quirky cacti, “Ramadama” lets you mark items that obstruct and assess your attachment to them. It’s motivation to keep going. As you part with things, you’ll discover: Less is often more!
Even when getting new shoes, use Ramadama to mark an older pair to leave your home. This ensures there’s space for you and your life.
Sharing space means shared responsibility: Ramadama aids here too. Invite household users to identify problem items on the clean-up map and resolve conflicts. Everyone gains more space!
Let Ramadama Inspire You
Get the app for iOS or Android and embark on your first clean-up challenge!
Ramadama - Stack
- Multiplayer mode
- Localization (German, English, Italian)
- Material Design
- Reactive UI with BLoC and realtime updates
- Custom theme with dark mode
- Visual Corporate Identity
- NoSQL data base (Firestore)
- Serverless Cloud Functions
- Push-Notifications for user actions and engagements
- Dynamic Links for intra-App-Actions
- Scalability to millions of users
Software Architect, Developer, Consultant
Freelancer / Self employed
I push my boundaries in the pursuit of creating value for customers. I learn new technologies and design techniques with my own app, Ramadama.
Zielpuls GmbH – Part of Accenture
Here I found my love for Flutter and got involved in product design. A company with a great personal touch, yet powerful with international range.
Software Consultant· Munich
TNG Technology Consulting GmbH
This engagement laid the foundation for my professional career in software engineering. An exceptionally profound and efficient organisation, always keen on learning and improving.
PhD in Physics/Meteorology· Munich
I handled massive amounts of forecast and observation data with custom statistical software and high performance computing together with the German and Dutch Weather Service. My work led to a significant improvement of the operational weather forecast in Germany.