Faculty Member
- Qualification
PhD, M. Tech, B. Tech
- Designation
Assistant Professor
- Thrust Area
Image Processing for IoT/ Wearable sensors, Artificial Intelligence, Holographic image coding
- Address
114, Mirzahadipura, Mau Nath Bhanjan, Mau, UP, India-275101
- Mobile
- Email
mohdtausif@zhcet.ac.in
- Time Table
Mohd Tausif holds a Postdoctoral research experience from the Cloud Computing Competence Center, University of Beira Interior, Covilha, Portugal in the field of Holography. He received his PhD degree from the Department of Electronics Engineering, Aligarh Muslim University, Aligarh, India in 2019. The PhD research work was focused on developing low-memory and low-complexity image coders (algorithms and architectures) for low-cost visual sensor nodes used in Wireless Multimedia Sensor Networks/ Internet of Things/ Wearable devices. He has published twelve papers in referred journals and conferences. His research area includes Signal processing, Image processing for resource-constrained platforms, Holography, Identification codes, and wearable devices.
- D. Joshi, A. Kumar, M. Tausif and E. Khan, "Low-Cost Smart Braille Learning Kit for Visually Impaired People," IEEE Sensors Journal, vol. 26, no. 4, pp. 5646-5653, 15 Feb.15, 2026, doi: 10.1109/JSEN.2025.3648398.
This article addresses the critical issue of
restricted access to information and educational materials
for visually impaired individuals. Traditional Braille displays
have struggled to meet the needs of this population, contributing
to low Braille literacy rates. Our work introduces
a novel interactive Braille device that revolutionizes Braille
reading and writing by incorporating several key innovations.
Our device features audio support, document reading
capabilities, Braille-to-text conversion, and bilingual language
support. A standout feature of our design is the
solenoid-based approach, which reduces power consumption,
ensuring that the device is affordable, reliable, and portable. The impact of our device is far-reaching, empowering
visually impaired individuals in classrooms, libraries, and public spaces. Promoting Braille literacy encourages inclusivity
and equal access to information. In addition, our use of Raspberry Pi in developing a low-cost Braille learning
device underscores our commitment to making this technology accessible to diverse settings. Our device demonstrates
the transformative potential of technology and innovation in enriching the lives of people with disabilities, promoting
literacy, and advancing societal inclusivity toward a more equitable future.
- M. Tausif, E. Khan, and A. Pinheiro, “Computationally efficient wavelet-based low memory image coder for WMSNs/IoT”, Multidimensional Systems and Signal Processing, May 2023. Download PDF
- M. Tausif, A. Jain, E. Khan, and M. Hasan, “Memory-efficient architecture for FrWF-based DWT of high-resolution images for IoMT applications,” Multimedia Tools and Applications, 80, pp. 11177–11199, Mar. 2021.
- M. Tausif, E. Khan, M. Hasan, and M. Reisslein, “Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors,” Advances in Multimedia, Vol. 2020, pp. 1-13, Dec. 2020.
- M. Tausif, A. Jain, E. Khan, and M. Hasan, “Low Memory Architectures of Fractional Wavelet Filter for Low-Cost Visual Sensors and Wearable Devices,” IEEE Sensors Journal, vol. 20, no. 13, pp. 6863-6871, Jul., 2020.
- M. Tausif, N. R. Kidwai, E. Khan, and M. Reisslein, “FrWF-based LMBTC: Memory Efficient Image Coding for Visual Sensors,” IEEE Sensors Journal, Vol. 15, No. 11, pp. 6218-6228, Nov. 2015.
- M. Tausif, E. Khan, M. Hasan, and M. Reisslein, “SMFrWF: Segmented Modified Fractional Wavelet Filter: Fast Low-Memory Discrete Wavelet Transform (DWT),” IEEE Access, vol. 7, issue 1, pp. 84448-84467, Dec. 2019.