Founding Advisor
Aaditya R M — Founding Advisor of SINC
SINC — Society for Innovation, Network & Collaboration · Machine learning and deep learning, computer vision
Aaditya R M is the Founding Advisor of SINC (Society for Innovation, Network & Collaboration), providing strategic guidance, advice and support, and direction for the organisation.
About Aaditya
Aaditya is an M.Tech Computer Science and Engineering student at Amrita Vishwa Vidyapeetham, Chennai, specialising in machine learning and deep learning. His hands-on work covers computer vision, transformer architectures and medical image analysis.
He works in Python on data preprocessing, model training and performance evaluation, using TensorFlow, PyTorch, scikit-learn and OpenCV. Before his postgraduate studies he completed a B.Tech in Information Technology at PSG College of Technology, Coimbatore.
As SINC’s Founding Advisor, he provides strategic guidance, advice and support, and direction for the organisation.
Role at SINC
- Strategic guidance
- Advice and support
- Direction for the organisation
Education
- M.Tech, Computer Science and EngineeringAmrita Vishwa Vidyapeetham, Chennai2025 – 2027
- B.Tech, Information TechnologyPSG College of Technology, Coimbatore2022 – 2025
- Diploma in Information TechnologyPSG Polytechnic College, Coimbatore2019 – 2022
Experience
- Project Intern – Automation EngineerJK Automations, CoimbatoreApr – Jun 2024
Developed and enhanced industrial automation tools with Siemens SCADA WinCC and C++, working on CNC machine data integration, sensor monitoring and real-time data acquisition for manufacturing systems. Implemented new features and resolved more than 40 software bugs to improve system stability.
Projects
Automated Brain Tumor Segmentation using MRI Images
A medical image segmentation system built with convolutional neural networks and transformer-based architectures at Amrita Vishwa Vidyapeetham, with image preprocessing, augmentation and model optimisation. It reached 93% accuracy and an improved Dice coefficient for tumour boundary detection, evaluated on accuracy, precision, recall, F1-score and confusion matrices.
Schizophrenia Classification using Vision Transformer Models
Deep learning pipelines for MRI image classification at PSG College of Technology, implementing ViT, CvT, Swin Transformer and DeiT models and comparing them on accuracy and F1-score. The transformer models improved classification reliability over baseline CNN models.
Face Mask and Social Distance Detection System
A real-time computer vision system in Python and OpenCV with face detection, mask classification and distance estimation, and a JavaScript front end for monitoring alerts and visualisation.
Skills
- Python
- C++
- JavaScript
- SQL
- Deep learning
- Supervised and unsupervised learning
- CNNs
- Vision Transformers (ViT)
- Swin Transformer
- Feature engineering
- Model evaluation
- TensorFlow
- PyTorch
- scikit-learn
- OpenCV
- NumPy
- Pandas
- Matplotlib
- Git
- Siemens SCADA WinCC
- HTML
- CSS
- WordPress
Certifications
- C++ Programming (100 hours), E Box
Achievements
- Second place, CRYPTO GATHERERS, Kumaraguru College of Technology
Leadership and activities
- Inter-college cricket tournament, PSG College of Technology
- Volunteer, ICOISCIS conference
- Executive member, CAP and Nature Club