Sahil Anchal

About

I am a doctoral research scholar(PhD) at the Indian Institute of Technology (IIT) Delhi. My doctoral work is majorly focussed on human identification via gait analysis, its an intersection of signal processing, machine learning and representation learning.
I am Co-founder and the Director of Suxma Systems Pvt. Ltd., an IIT Delhi incubated startup. It develops IoT enabled dairy and biomedical equipment, it also venturing into providing solutions for smart buildings, offices and campus premises etc.
My research interests include embedded systems, signal processing, and machine learning.

Employment

Employment history is unavailable.

Education

• Indian Institute of Technology Delhi PhD
  2018 - 2024
• Indian Institute of Technology Delhi MS Research
  2015 - 2018
• University of Delhi MSc Electronics
  2010 - 2012
• University of Delhi BSc (Hons.) Electronics
  2007 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• DeepStep: A Deep Learning-Based Indoor Person Identification Framework Using Footstep-Induced Structural Vibration Signals
  IEEE Transactions on Instrumentation and Measurement 2025 DOI: 10.1109/TIM.2025.3643033
  +Save
• GajGamini: Mitigating Man–Animal Conflict by Detecting Moving Elephants Using Ground Vibration-Based Seismic Sensor
  IEEE Sensors Letters 2024 DOI: 10.1109/LSENS.2024.3442830
  +Save
• Person Identification and Imposter Detection Using Footstep Generated Seismic Signals
  IEEE Transactions on Instrumentation and Measurement 2021 DOI: 10.1109/TIM.2020.3022486
  +Save
• Person Identification using Structural Vibrations via Footfalls for Smart Home Applications
  IEEE Internet of Things Journal 2021 DOI: 10.1109/JIOT.2021.3066448
  +Save
• GMM-UBM based person verification using footfall signatures for smart home applications
  GlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings 2019 DOI: 10.1109/GlobalSIP45357.2019.8969215
  +Save
• Person Identification and Imposter Detection using Footfall based Biometric System
  Proceedings of IEEE Sensors 2019 DOI: 10.1109/SENSORS43011.2019.8956722
  +Save
• UREDT: Unsupervised Learning Based Real-Time Footfall Event Detection Technique in Seismic Signal
  IEEE Sensors Letters 2018 DOI: 10.1109/LSENS.2017.2787611
  +Save
• Detection of an intruder and prediction of his state of motion by using seismic sensor
  IEEE Sensors Journal 2018 DOI: 10.1109/JSEN.2017.2776127
  +Save
• Person Identification using Seismic Signals generated from Footfalls
  arXiv 2018
  +Save
• Predicting gender from footfalls using a seismic sensor
  2017 9th International Conference on Communication Systems and Networks, COMSNETS 2017 2017 DOI: 10.1109/COMSNETS.2017.7945357
  +Save