Dr. Rashad M Jillani

Dr. Rashad M. Jillani
Ext. 2520

Dr. Rashad M Jillani

Assistant Professor

Qualifications: Ph.D (Computer Engineering) – Florida Atlantic University, USA
Research Interests: Cyber Security, Encryption Protocols,  Digital Multimedia Systems, Video Compression and Communication, Video Transcoding, Content Adaptation, Pervasive Media delivery


Dr. Rashad Jillani holds PhD degree in Computer Engineering from the Department of Computer & Electrical Engineering and Computer ScienceFlorida Atlantic University, USA (2012).

His PhD dissertation is on scalable extension (SVC) of H.264/AVC (Advanced Video Coding) to reduce complexity by improvising motion estimation algorithms using machine learning techniques. During his PhD, he worked with Dr. Hari Kalva in the Multimedia Lab (mlab). During his doctoral research, he worked as Research/Graduate Assistant in FAU, where on various teaching and research assignments, he has taught different courses and participated in the RnD efforts on image and video processing.

His industrial and professional experience includes cyber security and building Application Security Platform  that provides strong security throughout any enterprise and its connected partners. This service provides authentication/authorization modules based on digital certificates and role based access model.

Research Overview

Our research interests are in the areas of visual information processing that considers the entire video pipeline — capture, compression, communication, and consumption. We are interested in understanding how visual perception, cognition, and emotion can help optimize video services. One key area of focus is understanding and applying human visual perception, cognition, and social context to optimize video quality and reduce bandwidth needed for video services.

Dr. Rashad Jillani has extensive R&D experience in the area of video encoding, compression, and adaptation especially experienced in video encoding, H.264/AVC standard implementation including design and implementation of new low complexity video coding algorithms by employing machine learning techniques.

Standardization Research

We are actively involved in research related to audio-visual compression and communication standards. Our work includes low complexity encoding and transcoding of HEVC, AVC/H.264, and AV1. A related area of focus is video encoding and delivery optimization for mobile devices. Applying and optimizing WebRTC for realtime services is another area of interest.

Industry Experience

Dr. Rashad Jillani has extensive professional industry experience. He is a software engineer with over 10 years of professional experience in the full life cycle of software engineering starting from requirements gathering, design, prototype, development, testing and to the maintenance. He has advanced knowledge of developer applications, tools, methodologies and best practices (including OOD, design patterns, UML and Rational Rose).  He has experience working in Scrum/Agile methodology and managing Git repositories.

From 2000 to 2005, he has served as a software engineer, where he was responsible for different phases of full lifecycle development of web based application security platform, innerGuard, from initial requirement gathering to design, coding, testing, documentation, implementation and integration.

During his stay in USA, he has worked in the following organizations in various capacities as an expert in digital media system.

Representative Publications:

  • U. Joshi, R. Jillani, C. Bhattacharyya, H. Kalva, and K. R. Ramakrishnan. “Speedup Macroblock Mode Decision in H.264/SVC Encoding Using Cost-Sensitive Learning”, Proceedings of the IEEE International Conference on Consumer Electronics, Las Vegas, USA, January 11-13, 2010.
  • R. Jillani, U. Joshi, C. Bhattacharyya, H. Kalva, and K. R. Ramakrishnan. “Video Coding Mode Decision As A Classification Problem”, Proceedings of SPIE/IS&T Visual Information Processing and Communication, San Diego, USA, January 17-21 2010.
  • R. Jillani, and H. Kalva. “Low Complexity Intra MB Encoding in H.264/AVC”, Consumer Electronics, IEEE Transactions on, vol.55, no.5, pp.277-285, February 2009.
  • H. Kalva, P. Kunzelmann, R. Jillani, and A. Pandya. “Low Complexity H.264 Intra MB Coding,” Proceedings of the IEEE International Conference on Consumer Electronics, Las Vegas, USA, January 9-13, 2008.
  • R. Jillani, C. Holder, and H. Kalva. “Exploiting Spatio-Temporal Characteristics of Human Vision for Mobile Video Applications” SPIE Optics Photonics 2008, Applications of Digital Image Processing XXXI, San Diego, CA, Aug 2008, Invited Paper.
  • G. F. Escribano, R. Jillani, C. Holder, H. Kalva, J. L. Martinez Martinez, and P. Cuenca. “Video Encoding and Transcoding Using Machine Learning”, In Proceedings of the 9th Intl. Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD  2008 (MDM ‘08), ACM, New York, NY, USA, pp. 53-62.
Book Chapter
  • R. Jillani and H. Kalva. “Scalable Video Coding Standard”, in Encyclopedia of Multimedia, B. Furht, Springer US, 2008, pp. 775-781.

-Graduate Courses

Cybersecurity and IoT

Advanced Image Processing

Undergraduate Courses

Digital Image Processing

Logic Design

Computer Architecture

Computer Organization

Data and Network Security

Object Oriented Analysis and Design

Data Security and Encryption

Introduction to Computing

Mobile Computing 

Professional Memberships

Image result for IEEE logo small Institute of Electrical and Electronics Engineers (IEEE), Senior member

Association for Computing Machinery (ACM), Professional member

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