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Chirantan Ghosh Innovates New Tech Startup:

Deep learning has become an integral part of the tech industry, and research into its advancement has received tremendous funding and attention. One journal article, surveying the application of deep learning in object detection, argues that, “In recent years, with the rapid development of deep learning, a number of research areas have achieved good results, and accompanied by the continuous improvement of convolution neural networks, computer vision has arrived at a new peak.” Deep learning has become integral to the continuation of object detection – a sector of the tech industry that has become increasingly important. 

Chirantan Ghosh has contributed a vast amount of valuable research to deep learning, machine learning, and computer science. His recent startup is set to change the way object detection is utilized, as well as its performance capabilities.


Ghosh began his career as he completed his undergraduate degree in computer science and engineering – securing 1st rank in the department. He became deeply invested and  interested in research work while pursuing a master’s degree at the New Jersey Institute of Technology in Information Systems. However, he later enrolled in another master’s program in Computer Science at the University of Delaware. His passion for research work has motivated him to solve complex environmental problems for the social good. He is now a computer science researcher, focusing on computer vision, data science, machine learning, and robotics.

While pursuing his second master’s at the University of Delaware, he began working on a research project that was funded by the National Oceanic and Atmospheric Administration. This involved creating technology that can predict any event of surface runoff, and its magnitude, in order to alert the nation’s farmers. Surface Runoff occurs due to the process of nutrients being washed away into a body of water. This occurs mainly as a result of heavy precipitation. The process negatively affects both the economy and the environment. It impacts crop production and profit due to the loss of nutrients from the agricultural fields. It also pollutes the body of water, which can lead to harmful algal blooms and hypoxia in the Great Lake region. Thus, the alerting system is essential to prevent water pollution by mitigating the effort, cost, and time of farmers. The existing physics-based model used by NOAA did not show adequate performance. As a result, Ghosh’s research work was used to improve the performance of the alerting system by utilizing a machine learning algorithm for runoff and risk level prediction of surface runoff. The project is still ongoing, however, Ghosh states that, “I can foresee that the future direction of this research leans towards deep learning for further improvement of model performance.” and

Ghosh realized that his skills with research, and his growing entrepreneurial mind, could help him create a business. He began working on, which is now in its early stages of formation. is being designed to solve any object detection or identification issues. It is, in a way, similar to Google lens, but is being crafted for improved accuracy. Additionally, the technology will be available for any device with a camera. When asked what can do, Ghosh responds, “It can possibly identify any object and provide detailed information to someone who is trying to know more about it. It can also recommend similar objects. The type of information it will provide will depend upon the object category.”

Ghosh has also expressed a deep concern for women’s security and safety. This has pushed him to initiate another startup named will use computer vision and deep learning-based surveillance methods to detect and identify any threat, and alert the appropriate organization and the subject in concern. Ghosh hopes to help overcome most of the challenges and security concerns related to women and promote a safe and healthy society. Ghosh argues that, “will create a safe atmosphere for women on a school or university campus or workplace. It will use the surveillance camera to recognize and track people, recognize their actions, and detect a possible threat. It will keep track of a person’s behavior and create an alert if something unusual is found. When used in public places, it will help alert women which places or roads to avoid and may guide them to rescue in any case of a possible threat.”

Final Thoughts

As machine and deep learning continues to develop as a vital facet of the tech industry, it is incredibly important for startups in the industry to receive attention and backing. This is especially vital for startups that intend to use their technology for good. Both and, innovated and founded by Ghosh, are startups that can contribute both to the tech industry and the society that consumers live in.

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