Graphene-Based Sensor Data Analytics
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Course Overview
Program Syllabus
Module 1
About This Course
This workshop focuses on advanced data analytics techniques for graphene-based Surface Acoustic Wave (SAW) gas sensors. Participants will learn signal preprocessing methods like noise filtering and drift correction, followed by anomaly detection using autoencoders for identifying sensor faults. The workshop also covers transfer learning for adapting models to new gas analytes, providing hands-on experience in enhancing sensor performance and developing real-time, adaptive sensor systems for various applications.
Module 2
Aim
The workshop aims to teach advanced data analytics for graphene-based SAW gas sensors, focusing on signal preprocessing, anomaly detection with autoencoders, and transfer learning for adapting models to new gas analytes.
Module 3
Workshop Structure
Module 4
📅 Day 1 – Signal Preprocessing for SAW Gas Sensors
- Overview of Surface Acoustic Wave (SAW) Gas Sensors
- Signal characteristics of graphene-based sensing devices
- Preprocessing needs: Noise filtering, drift correction, baseline alignment
- Algorithms for signal smoothing, peak alignment, and normalization
- Discussion on preprocessing pipelines in current sensor research
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Limited SeatsClosing Soon
Graphene-Based Sensor Data Analytics
Professional Certification Program
🎥
FormatLive + Recorded
📅
Duration8 Weeks
📜
CertificationVerified
Module 5
📅 Day 2 – Anomaly Detection Using Autoencoders
- Introduction to unsupervised anomaly detection in sensor systems
- Autoencoders: Concept, architecture, and training workflow
- Sensor-specific anomaly types: drift, spikes, signal loss
- Research trends: Denoising autoencoders, reconstruction error analysis
- Application of autoencoders in fault detection and early warning systems
Module 6
📅 Day 3 – Hands-On: Transfer Learning & Adaptation to New Analytes
- Quick recap of signal preprocessing and autoencoder workflow
- Introduction to transfer learning for cross-analyte generalization
- ⚙️ Hands-On Activities:
- Load and visualize preprocessed SAW sensor data
- Use a pretrained autoencoder for anomaly detection
- Fine-tune model on data from a new gas analyte
- Evaluate model adaptation performance
Module 7
Who Should Enrol?
This workshop is intended for researchers, engineers, and students in sensor technology, data science, and materials science. It is ideal for those interested in gas sensor systems, signal processing, and machine learning applications. A basic understanding of machine learning concepts and programming is recommended but not required.
Module 8
Important Dates
Module 9
Registration Ends
09/28/2025
IST 8 PM
Module 10
Workshop Dates
09/28/2025 – 09/30/2025
IST 9 PM
Module 11
Workshop Outcomes
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Expertise in signal preprocessing and anomaly detection.
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Hands-on experience with autoencoders and transfer learning.
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Proficiency in enhancing sensor performance through data analytics.
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Readiness for careers in sensor technology, data science, and machine learning.
Module 12
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Meet Your Mentor(s)
Mr. Indra Neel Pulidindi
Scientific consultant
Jesus’ Scientific Consultancy for Industrial and Academic Research (JSCIAR)
Dr. Indra Neel Pulidindi works as an assistant professor at Saveetha Medical College and Hospital (SMCH) & Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, India. He serves as a Scientific Consultant at JSCIAR, India. He has also been rendering his services as a . . .
Module 13
Fee Structure
Module 14
Student Fee
₹1999 | $60
Module 15
Ph.D. Scholar / Researcher Fee
₹2999 | $70
Module 16
Academician / Faculty Fee
₹3999 | $80
Module 17
Industry Professional Fee
₹5999 | $100
Module 18
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Module 19
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Module 20
Publication Opportunity
Get published in a prestigious open-access journal.
Module 21
Centre of Excellence
Become part of an elite research community.
Module 22
Networking & Learning
Connect with global researchers and mentors.
Module 23
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
Module 24
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