Dr. Seema Gulati | Faculty Computer Science and Engineering

Dr. Seema Gulati
Assistant Professor

RESEARCH AREA
Machine Learning, Deep Learning, Federated Learning

EDUCATION

  • Ph.D. (Computer Science and Engineering), Chitkara University, Rajpura, Punjab, India. (2025) 
  • M.Tech. (Computer Science and Engineering), Punjab Technical University, Punjab, India. (2014) 
  • B.Tech. (Computer Engineering), Kurukshetra University, Haryana, India (2011) 

ACADEMIC, RESEARCH AND INDUSTRIAL EXPERIENCE

  • Academic Experience: 5 Years
  • Research Experience: 4 Years

Dr. Seema Gulati is a distinguished academician and researcher specializing in the fields of Computer Science and Engineering. She holds a Ph.D. from Chitkara University, Punjab, and boasts a comprehensive teaching career that spans over nine years. Dr. Gulati is actively engaged in cutting-edge research, with a focus on machine learning, deep learning, federated learning, and their diverse applications in the healthcare sector. Her scholarly contributions are well-recognized, with several peer-reviewed journal articles and conference papers published in high-impact journals, such as IEEE Access, Current Medical Imaging and SN Computer Science. Furthermore, Dr. Gulati has served as a reviewer for numerous articles published in esteemed high-impact journals by Springer, further underscoring her expertise and reputation in her field.

ORCID ID: 0009-0001-3869-7240

Scopus ID:  57832085400     

Vidwan ID:   NA            

Google Scholar ID:   https://scholar.google.com/citations?user=oMCOEe4AAAAJ&hl=en

Web of Science: HNI-4975-2023

RESEARCH PUBLICATIONS

  • Gulati, S., Guleria, K., Goyal, N., AlZubi, A. A., & Castilla, Á. K. (2024). A Privacy-Preserving Collaborative Federated Learning Framework for Detecting Retinal Diseases. IEEE Access.
  • Gulati, S., Guleria, K., & Goyal, N. (2025). Privacy-Preserving and Collaborative Federated Learning Model for the Detection of Ocular Diseases. International Journal of Mathematical, Engineering & Management Sciences, 10(1).
  • Gulati, S., Guleria, K., & Goyal, N. (2024). Collaborative, Privacy-Preserving Federated Learning Framework for the Detection of Diabetic Eye Diseases. SN Computer Science, 5(8), 1100.
  • S. Gulati, K. Guleria, N. Goyal, and A. Dogra, “Federated Deep Learning Approaches for Detecting Ocular Diseases in Medical Imaging: A Systematic Review,” Curr Med Imaging, vol. 21, no. 1, p. E15734056400866, 2025.
  • Gulati, S., Guleria, K., & Goyal, N. (2024). Detection and Multiclass Classification of Ocular Diseases using Deep Learning-based Ensemble Model. International Journal of Intelligent Systems and Applications in Engineering, 12(19s), 18–29. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5041
  • Gulati, S., Guleria, K., & Goyal, N. (2023, December). Classification and detection of diabetic eye diseases using deep learning: A review and comparative analysis. In AIP Conference Proceedings (Vol. 2916, No. 1). AIP Publishing.
  • Gulati, S., Guleria, K., & Goyal, N. (2023, July). Classification of diabetic retinopathy using a pre-trained deep learning model, DenseNet 121. In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
  • Gulati, S., Guleria, K., & Goyal, N. (2022, April). Classification and detection of coronary heart disease using machine learning. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1728-1732). IEEE.
  • Gulati, S., Guleria, K., & Goyal, N. (2022, October). Classification of migraine disease using supervised machine learning. In 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (pp. 1-7). IEEE.
  • R. Singh, A. Jaguri, S. Gulati, and M. Kumar, “Deep learning-based musical instrument classification using LSTM networks,” AIP Conf Proc, vol. 3357, no. 1, p. 40001, Dec. 2025, doi: 10.1063/5.0297739.
  • R. Singh, S. Gulati, A. Mohan, and Y. Tyagi, “Leveraging machine learning techniques for early detection of Parkinson’s disease,” AIP Conf Proc, vol. 3357, no. 1, p. 40003, Dec. 2025, doi: 10.1063/5.0297738.
  • R. Chaudhary, P. K. Goel, S. Verma, H. Tyagi, S. Gulati, and H. Tyagi, “Sustainable Health Tech Managing Eco-Conscious IoT Devices for Medical Innovation,” in Development and Management of Eco-Conscious IoT Medical Devices, IGI Global Scientific Publishing, 2026, pp. 123–154.

Admissions Open 2026

The application process at Graphic Era is strictly based on the Merit of the qualifying examination with the entire Admission Process available for completion online

Admissions Open 2026

The application process at Graphic Era is strictly based on the Merit of the qualifying examination with the entire Admission Process available for completion online