Welcome to my homepage.
I am currently working as an Associate Professor at Vidyashilp University, Bangalore.

Prior to this, I served as an Associate Professor in the School of Computer Science and Engineering (SoCSE) at RV University, Bangalore. Before transitioning to academia, I worked in industry as a Senior Machine Learning Scientist at Lytx Inc., and earlier as a Technical Lead in Computer Vision and Machine Learning at PathPartner Technologies, Bangalore.

I received my Ph.D. from the Indian Institute of Information Technology (IIIT) Sri City, India.
My research interests include Machine Learning, Computer Vision, Deep Learning, Transfer Learning, Neural Network Compression, and Neural Architecture Search.
Currently, I am focused on research in Active Learning, Model Compression, and Multi-task Learning.

Updates:

• Secured another consultancy project on building computer vision models for sports analytics.

• "Impact of Fully Connected Layers on the Performance of CNN for Image Classification" paper crossed 500 citations.

• Secured a consultancy project on model compression from Perforated AI, USA.

• "PRF: Deep Neural Network Compression by Systematic Pruning of Redundant Filters" paper accepted for publication in Neural Computing and Applications journal (Springer), Impact Factor: 4.5. [Paper][Code]

• A research work on "Inclement Weather Detection" is published in US Patent , June 2024. (link)

• TASCNet paper accepted for publication in Multimedia Systems journal (Impact factor: 3.9) 

• "Deep Model Compression based on Traning History" paper accepted for publication in Neurocomputing Journal (Impact Factor: 6).

• Taken Short-Term Training Program (STTP) on A Research Perspective on Deep Learning Applications, Vardhaman College of Engineering, Hyderbad, Dec-2023. 

• Delivered a talk on "Active Learning for Maximizing Deep Learning Model Performance with a Tight Budget" at IIIT Sri City, 2023.

• Submitted a patent on Deep Active Learning to the US patent office.

• AdaInject paper accepted for publication in IEEE Transactions on Artificial Intelligence.

• Action Recognition paper accepted for publication in Multimedia Tools & Applications Journal, Springer (IF: 2.75)

• Hybrid Filter Pruning paper accepted for presentation at ICASSP-2022.

• HRel Filter Pruning paper accepted for publication in Neural Networks journal Elsevier (IF: 8.05).

• A patent on Neural Network compression is submitted to the Indian Patent office.

• Semester-long research internship position: contact: shabbeer.sh@pathapartnertech.com (Closed)

• 24th Jun 2021:    Delivered a hands-on session on Transfer Learning - Reusing the Learned Knowledge, ATAL-sponsored FDP organized by University of Mysore. 

• 22nd Feb 2021:   Taken Expert Lecture on Deep Learning frameworks - a hands-on session in WADLA-2021 at IIIT Sri City.

• 07th Dec 2020:   Taken a Hands-on session on Implementing deep neural networks for PG Students at IIIT Sri City. 

• 09th Dec 2020:   AutoTune paper has been selected for presentation at the VISION INDIA session at ICVGIP-2020.

• 17th Nov 2020:   AutoFCL paper got accepted for publication in Neural Computing and Applications Springer (IF: 4.77).

• 16th Oct 2020:   AutoTune paper got accepted for publication in Neural Networks journal Elsevier (IF: 8.05).

• 20th Nov 2019:   Impact of Fully Connected Layers paper accepted in Neurocomputing Journal Elsevier (IF: 4.07).

• 30th Aug 2018:   RCCNet paper accepted in ICARCV - 2018, Singapore.

• Qualified in  APSET - 2016.

• Secured a 94.07 percentile in GATE-2010.

Workshops Attended:

• Pattern Analysis and Applications organized by CVPR Unit, ISI Kolkata - 2018.

• Deep Learning: with hands-on organized by Department of Mathematics & Computer Science, SSSIHL - 2017.

• Outcome Based Learning organized by Department of Computer Science, BITS Pilani, Hyderabad - 2015.