Departments

PERMANENT FACULTY
Dr. Jaya Gera
Dr. Akanksha Bansal Chopra (Teacher In-charge)
Dr. Anuradha Singhal
Mansi Sood
Sonia Kumari
Dr. Manish Kumar Singh
Seema Rani
Pratibha Yadav
Dr. Shweta Tyagi
Savita Devi
Luvkush Gupta

AD-HOC FACULTY
Geeta Arneja

Basic Details

Full Name	Dr. Anuradha Singhal
Department	Computer Science
Email	anuradha.singhal@spm.du.ac.in
Phone Number	11 25224499
Address	Shyama Prasad Mukherji College for Women, University of Delhi
Resume	View Resume

Undergraduate Degree: B.E

Undergraduate University: Rajasthan University

Undergraduate Year: 2006

Postgraduate Degree: MS

Postgraduate University: BITS Pilani

Postgraduate Year: 2010

PhD Degree: Computer Science

PhD University: Department of Computer Science, University of Delhi

PhD Year: 2022

Other Qualifications: Qualified UGC Net

Designation: Assistant Professor

Institution Name: Shyama Prasad Mukherji College for Women, University of Delhi

Years of Experience: 13

Subjects Taught: Operating Systems, Machine Learning, Data Analysis and Visualization, C++, Android Programming, DBMS, Digital Empowerment

Assigned Courses: B.Sc (Hons) Comp Sc, B.Tech (Computer Science), BA (Prog), SEC, VAC

Journal Publications:

Singhal, A., & Bedi, P. (2021). Multi-class blind steganalysis using deep residual networks. Multimedia Tools and Applications, 80(9), 13931–13956. https://doi.org/10.1007/s11042-020-10353-2 (Publisher Springer, Impact Factor: 2.57, Scopus: Indexed)
Bedi, P., & Singhal, A. (2022). Estimating cover image for Universal payload region detection in Stego Images. Journal of King Saud University - Computer and Information Sciences. https://doi.org/10.1016/J.JKSUCI.2022.01.010 (Publisher Elsevier, Impact Factor: 8.839, Scopus: Indexed)
Bedi, P., Singhal, A. & Bhasin, V. (2023) Deep learning based active image steganalysis: a review. International Journal of System Assurance Engineering and Management. https://doi.org/10.1007/s13198-023-02203-9 (Publisher Springer, Impact Factor: 2.0, Scopus: Indexed)
Singhal A.& Bedi P. (2024) USteg-DSE: Universal Quantitative Steganalysis framework using DenseNet merged with Squeeze & Excitation Net. Signal Processing: Image Communication. https://doi.org/10.1016/j.image.2024.117171 (Publisher Elsevier, Impact Factor: 3.4, Scopus: Indexed).

Conference Papers:

Singhal, A., & Bedi, P. (2022). Universal Quantitative Steganalysis Using Deep Residual Networks. International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, 465–475. https://doi.org/10.1007/978-981-16-3071-2_37 (Scopus Indexed)
Singhal, A., & Bedi, P. (2020). Blind Quantitative Steganalysis Using CNN–Long Short-Term Memory Architecture. Strategic System Assurance and Business Analytics. Asset Analytics (Performance and Safety Management). , 175–186. https://doi.org/10.1007/978-981-15-3647-2_14 (Scopus Indexed)
Singhal, A., & Bedi, P. (2018). Blind Quantitative Steganalysis using SVD Features. 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018, 369–374. https://doi.org/10.1109/ICACCI.2018.8554947 (Scopus Indexed)