Congratulations to Akshay Agarwal- Best Researcher - Award Winner 2023
Akshay Agarwal:
Akshay Agarwal is an accomplished professional and academician, currently serving as an Assistant Professor in the Department of Data Science and Engineering at IISER Bhopal, India. With a robust background in computer science and a focus on cutting-edge research in artificial intelligence (AI) and computer vision, Akshay has made significant contributions to the field.
professional profile:
Early Academic Pursuits
Akshay Agarwal embarked on his academic journey with a Bachelor's in Computer Science from Invertis, Bareilly, UP, India, where he excelled with an overall percentage of 77.24%. This laid the foundation for his subsequent academic achievements.
His pursuit of knowledge continued with a Master's in Information Technology from IIIT-Allahabad, UP, India, where he achieved a CGPA of 8.85. This early academic rigor set the stage for his passion for technology and research.
Professional Endeavors
Venturing into the realm of academia, Akshay pursued a Ph.D. in Image Analysis and Biometrics from IIIT-Delhi, New Delhi, India. His doctoral research, titled "Panoptic Defenses for Secure Computer Vision," showcased his commitment to advancing the field. This dedication earned him the prestigious Visvesvaraya PhD Fellowship from the Government of India.
Post-Ph.D., Akshay expanded his horizons as a Research Assistant Professor at Texas A&M University, Kingsville, Texas, USA, delving deeper into the intricacies of his research interests.
Contributions and Research Focus
Akshay's research focus revolves around AI Security, Trustworthy Computer Vision, ML/DL, Presentation Attacks, Adversarial Robustness, Deepfakes, and Bias. His work has notably contributed to the development of robust defenses in computer vision, addressing critical challenges in the ever-evolving landscape of artificial intelligence.
During his visiting researcher experience at West Virginia University, USA, Akshay worked on pioneering projects related to face presentation attack detection and morphing attack detection, resulting in impactful publications in prestigious conferences.
Accolades and Recognition
The accolades bestowed upon Akshay Agarwal stand as a testament to his excellence. Notably, he received the IEEE Biometrics Council 'Best Doctoral Dissertation' Award in 2021 for his outstanding Ph.D. work. His recognition extended to winning the second place in the Agrusa Student Innovation competition at the University at Buffalo in 2021.
Impact and Influence
Akshay's influence is evident not only through awards but also through his selection for the 7th Heidelberg Laureate Forum, where only the 200 most qualified young researchers are invited. His work has left a lasting impact on the academic community, shaping discussions and developments in the fields of AI Security and Computer Vision.
Legacy and Future Contributions
As an Assistant Professor at IISER Bhopal, Akshay Agarwal continues to shape the next generation of researchers. His legacy lies in inspiring students and colleagues alike, fostering a culture of innovation and excellence.
Looking ahead, Akshay envisions contributing further to the field, addressing emerging challenges in AI security, and leaving an indelible mark on the landscape of computer vision and machine learning.
Notable Publications:
G. Goswami, A. Agarwal, N. K. Ratha, R. Singh, M. Vatsa, “Federated Learning for Local
and Global Data Distribution”, ICLR TinyPapers, 2023
U. Rathore, A. Agarwal, “Is DFR for Soft Biometrics Prediction in Unconstrained
Images Fair and Effective?”, ICLR TinyPapers, 2023
A. Agarwal, M. Vatsa, and R. Singh, “Role of Optimizer on Network Fine-tuning for
Adversarial Robustness (Student Abstract)”, In AAAI Conference on Artificial Intelligence
(AAAI), 2021, vol. 35, no. 18, pp. 15745-15746.
A. Mehra, A. Agarwal, M. Vatsa, and R. Singh, “Detection of Digital Manipulation in
Facial Images (Student Abstract)”, In AAAI Conference on Artificial Intelligence (AAAI),
2021, vol. 35, no. 18, pp. 15845-15846.
R. Singh, A. Agarwal, M. Singh, S. Nagpal and M. Vatsa, “On the Robustness of Face
Recognition Algorithms Against Attacks and Bias”, AAAI Conference on Artificial Intelligence, 2020, vol. 34, no. 09, pp. 13583-13589. (ORAL)
G. Goswami, N. Ratha, A. Agarwal, R. Singh, and M. Vatsa, “Unravelling Robustness of
Deep Learning based Face Recognition Against Adversarial Attacks”, In Association
for the Advancement of Artificial Intelligence (AAAI), 2018, pp. 6829-6836. (ORAL)