Dr. Bindu Verma

                                                           

Dr. Bindu Verma is a faculty member in the Department of Information Technology at Delhi Technological University( Formerly known as Delhi College of Engineering). She earned the Doctorate degree in Automated Intent Recognition using Hand Gesture and Face Expression Analysis from School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi. She has completed his M.Tech from Jawaharlal Nehru University in Computer Science in 2015.  Before joining Delhi Technological University, she has served as an Assistant Professor in the Department of CSE & IT, Jaypee Institute of Information Technology, Noida for more than three years. She has also worked as Software Engineer in Accenture India Pvt. Ltd. Banglore.

Dr. Bindu Verma is passionate to work in the area of computer vision, machine learning, human-computer interaction, intelligent systems, affective state monitoring. She had made substantial contributions to the field of human-computer interaction, emotion recognition, and intent recognition with many research articles published in reputative journals such as Elsevier, Springer including IEEE transaction. She also serve as a reviewer of many International Journals such as IET intelligent transport system, IEEE Transactions on Circuits and Systems for Video Technology, International Journal of Engineering Applications for Artificial Intelligence, Expert Systems, The Visual Computers, etc.

 

• Delhi Technological University, New Delhi, India  December 2020- Present  Assistant Professor
•  Jaypee Institute Of Information Technology, Noida August 2017- December 2020 Sr. Assistant Professor
• Accenture Private India Limited March 2013-– August 2013 Associate Software Engineer Worked as a Software Developer.

 

1. Programming Fundamentals

2. Computer Vision

3. Theory of Computation

4. Data Structures

5. Introduction to Mobile Application Development

6. Open Source Software Programming Lab

7. Software Development Fundamentals-1 & 2

8. Deep Learning

9. Advance Design Analysis

 

 

1. Member of IEEE Professional

2. Member of IEEE ITSS Society

3. ISTE Membership

4. CSI Membership

International Journals :

1. Agarwal, Lakshita, and Bindu Verma. "Enriching image description generation through multi-modal fusion of VGG16, scene graphs and BiGRU." The Visual Computer (2025): 1-21.
2. Tripathi, Reena, and Bindu Verma. "Tri-modal fusion for dynamic hand gesture recognition: Integrating RGB, depth, and skeleton data." Signal Processing: Image Communication (2025): 117440.
3. Nidhi, Verma, B.. "In-the-wild facial emotion recognition using relation-aware geometric features and CapsNet." Computers and Electrical Engineering 128 (2025): 110685.
4. Nidhi, Verma, B. A lightweight convolutional swin transformer with cutmix augmentation and CBAM attention for compound emotion recognition. Appl Intell (2024). https://doi.org/10.1007/s10489-024-05598-5 [SCI: IF 5.3]
5. Tripathi, R., Verma, B. Motion feature estimation using bi-directional GRU for skeleton-based dynamic hand gesture recognition. SIViP (2024). https://doi.org/10.1007/s11760-024-03153-w [SCIE: IF 2.6]
6. Agarwal, L., Verma, B. From methods to datasets: A survey on Image-Caption Generators. Multimedia Tools Appl 83, 28077–28123 (2024). https://doi.org/10.1007/s11042-023-16560-x [SCIE: IF 3.6]
7. Tripathi, R., Verma, B. Survey on vision-based dynamic hand gesture recognition. Vis Comput (2023). https://doi.org/10.1007/s00371-023-03160-x [SCIE: IF 3.5]
8. Nidhi, Verma, B. From methods to datasets: a detailed study on facial emotion recognition. Appl Intell 53, 30219–30249 (2023). https://doi.org/10.1007/s10489-023-05052-y [SCI: IF 5.3]
9. Sharma, P., Arya, R., Verma, R., Verma, B. Conv-CapsNet: capsule based network for COVID-19 detection through X-Ray scans. Multimed Tools Appl 82, 28521–28545 (2023). https://doi.org/10.1007/s11042-023-14353-w [SCIE: IF 3.6]
10. H. Mittal and B. Verma, "CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 9, pp. 9561-9570, Sept. 2023, doi: 10.1109/TITS.2023.3266113. [SCIE: IF 8.5]
11. Verma, B. (2022). A two stream convolutional neural network with bi-directional GRU model to classify dynamic hand gesture. Journal of Visual Communication and Image Representation, 87, 103554.[SCIE: IF 2.6]
12. Verma, B., Choudhary, A. Affective state recognition from hand gestures and facial expressions using Grassmann manifolds. Multimed Tools Appl 80, 14019–14040 (2021). https://doi.org/10.1007/s11042-020-10341-6 [SCIE: IF 3.6]
13. Verma, B., Choudhary, A. Grassmann manifold based dynamic hand gesture recognition using depth data. Multimed Tools Appl 79, 2213–2237 (2020). https://doi.org/10.1007/s11042-019-08266-w [SCIE: IF 3.6]
14. Verma, B., & Choudhary, A. (2018). Framework for dynamic hand gesture recognition using Grassmann manifold for intelligent vehicles. IET Intelligent Transport Systems, 12(7), 721-729. [SCIE: IF 3.2]

International Conferences:

1. Bindu Verma, and Ayesha Choudhary. “Unsupervised learning based static hand gesture recognition from RGB-D sensor.” In International Conference on Soft Computing and Pattern Recognition,pp. 304-314. Springer, Cham, 2016.
2. Bindu Verma, and Ayesha Choudhary. “Deep Learning Based Real-Time Driver Emotion Monitoring.” In IEEE International Conference on Vehicular Electronics and Safety (ICVES), pp.1-6., 2018.
3. Bindu Verma, and Ayesha Choudhary, “A Framework for Driver Emotion Recognition using Deep Learning and Grassmann Manifolds”, In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 1421-1426, 2018.
4. Gupta I, Garg N, Aggarwal A, Nepalia N, Verma B. Real-time driver's drowsiness monitoring based on dynamically varying threshold. In2018 Eleventh International Conference on Contemporary Computing (IC3) 2018 Aug 2 (pp. 1-6). IEEE.
5. Bindu Verma, and Ayesha Choudhary, Dynamic Hand Gesture Recognition using Convolutional Neural Network with RGB-D Fusion. InProceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing 2018 Dec 18 (pp. 1-8).

•  Coomendable Research Excellence Award DTU 2025 

•  Premier Research Excellence Award DTU 2024 

• Coomendable Research Excellence Award DTU  2022, 2023

• Cleared UGC- Net in December 2013 and June 2014, December 2014 and June 2015. Certificate No: 141023605

• 2013: Cleared GATE Examination with 98.9 Percentile.

• Awarded Junior Research Fellowship and Senior Research Fellowship from UGC in 2015. Award No: F./2014-15/NFO-2014-15-OBC-UTT-6082 /(SA-III/Website)

• Awarded an Financial Assistance, International Travel Support(ITS) from Science and Engineering Research Board (SERB), File No: File Number: ITS/2018/003824

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