Sai Tejeswar Reddy CHINTHA
AI & Data Science at MCS Data Labs GmbH
Berlin, Germany
M.Sc. International Mechatronics, Leibniz University Hannover
M.Sc. Intelligent Systems – Information Technology and Computer Science, St. Petersburg
B.Tech. Mechanical Engineering, NIT Warangal, India
I am an AI Engineer at MCS Data Labs GmbH. I lead projects in AI-powered e-health solutions. I develop AI-based solutions for smart wearables, architect data pipelines, and write proposals to win the funded projects (EU and DE).
From autonomous vehicles to healthcare applications, I've designed and deployed AI solutions across multiple domains. I bridge research and production—whether it's implementing GANs, building data pipelines, or deploying models on edge devices.
Off the clock, I'm either wandering new places, binge-watching movies, or out on the pitch playing cricket.
Feel free to ask my AI-powered chatbot to know about me!
Projects
Lane Change Decision-Making for Autonomous Vehicles
- Conceptualized and developed a knowledge-based decision-making neural network, designing system architecture with UML and state flow diagrams for robust functionality.
- Integrated the neural network into a fully operational web application using Python, FLASK, HTML, and CSS, alongside a GUI in C#, and evaluated its performance with recorded camera data.
- Packaged the project into a user-friendly web application, enabling easy interaction and user feedback for iterative model refinement and continuous optimization.
Aerodynamic Part Feeding System Simulation
- Designed and implemented a digital twin for an aerodynamic part feeding system, utilizing Blender for 3D modelling and Python for simulation scripting.
- Crafted a digital twin for an aerodynamic part feeding module using Blender, seamlessly integrating it with Python scripts to facilitate experimentation and parameterization.
- Conducted comprehensive evaluations of the digital twin through rigorous testing with hardware setups, demonstrating proficiency in simulation modelling and validation methodologies.
Traffic Sign Recognition using CNNs
Implemented a CNN with a ResNet backbone and increased the accuracy of the model by 2% through additional pre-processing of images using OpenCV.
CycleGAN for Image-to-Image Translation
- Implemented CycleGAN architecture in PyTorch for unpaired image-to-image translation tasks
- Developed training pipeline with cycle consistency loss and adversarial training mechanisms
- Applied model to various domain transfer tasks including style transfer and image enhancement
Data Anonymization Framework
- Developed a comprehensive data anonymization framework for privacy-preserving data processing
- Implemented various anonymization techniques including k-anonymity, l-diversity, and differential privacy
- Created pipelines for handling sensitive data in compliance with GDPR and data protection regulations
Featured posts
RELEVIUM Project - Digital Cancer Care Solutions
Featured in European Parliament discussion on improving cancer care through digital health solutions. MCS Data Labs develops innovative nutritional and digital health approaches for pancreatic cancer patients.
KupferDigital2 - MaterialDigital Initiative
Contributing to digital transformation in materials technology, developing user-friendly interfaces for structured, interoperable data sharing between companies and research institutions.
Healthcare 4.0 & 6G Technologies Training
Participated in advanced training on Healthcare 4.0 and 6G enabling technologies at Amsterdam UMC, collaborating with industry leaders and academic experts on cutting-edge communication technologies for healthcare.
Wind Energy Adhesives Prediction using Deep Learning
Published research on using image-based numerical modeling and generative deep learning for predicting mechanical behavior in wind energy adhesives at the 43rd Risoe International Symposium on Materials Science.
Professional Experience
AI Engineer
MCS Data Labs GmbH, Berlin | Oct, 2024 - Present
- Led development and deployment of ML models for e-health applications, including neural networks for pain measurement and non-invasive glucose monitoring on wearable devices
- Conducted scientific research on wrist-wearable health monitoring systems and AI methodologies for e-health applications
- Designed and maintained robust data pipelines for time-series data processing and analysis
- Architected and deployed federated dataspaces using Kubernetes, Terraform, and Azure infrastructure
- Secured funding by writing and acquiring EU and national research project proposals
- Collaborated with cross-functional teams to deliver scalable, data-driven solutions
Master thesis — Computer Vision, AI/ML
IAV GmbH, Gifhorn | Jun, 2023 - Feb, 2024
- Built an automated pipeline for virtual validation of autonomous vehicles including automated 3D scene generation from open-source datasets using 3D deep learning and sensor fusion
- Developed and deployed 3D vision models for lane detection and LIDAR point cloud semantic segmentation using Python and Matlab
- Fine-tuned LLMs for automotive applications, delivering Generative AI-based solutions to European and Asian clients
Junior AI Consultant - Working Student
Capgemini Engineering GmbH, Wolfsburg | Oct, 2022 - Apr, 2023
- Developed automated pipelines for image annotation, enhancing object detection datasets for computer vision tasks in an agile team environment
- Built and deployed GAN models for synthetic data generation, managing model deployment via Docker on Linux-based systems
Scientific Research Assistant – AI Developer
Institute for Wind Energy Systems, Leibniz University, Hannover | Sep, 2022 - Apr, 2023
- Researched and developed surrogate deep learning models (GANs, diffusion models) for synthetic data generation in structural and finite element analysis
- Implemented generative adversarial networks, diffusion models, and vision-language models for image generation with automated continuous training using Linux shell scripts
- Deployed models on cluster computers with parallel GPU computing using PyTorch and TensorFlow, and developed a minimalistic CI/CD pipeline for continuous data flow and model parameterization
- Built a streamlined application interface using Streamlit for model deployment and interaction
Graduate Engineer Trainee - Project Buyer
ZF WABCO India, Chennai | Jul, 2019 - Jan, 2020
- Managed procurement and supply chain analytics to optimize vendor performance and part acquisition
Technical Skills
Programming Languages
- Python
- MATLAB
- C++
- Java
- SQL
ML & AI
- TensorFlow & PyTorch
- TinyML & Embedded AI
- GANs & Diffusion Models
- Computer Vision
- NLP & LLMs
- MLFlow & Keras
Data Engineering
- Pandas & NumPy
- Signal Processing
- Time-Series Analysis
- Data Visualization
- Statistical Analysis
DevOps & Cloud
- Docker & Kubernetes
- Azure Cloud
- Terraform
- Git & CI/CD
- Flask & REST APIs
- Cluster Computing
Certifications
Get In Touch
Contact information
- chinthasaitejeswar@gmail.com
- +49xxxxxxxxxxx
- Berlin, Germany