Chirantan Ghosh: India’s Wiz Kid on a global prowl!

Chirantan Ghosh is a computer science researcher with an interest in computer vision, data science, machine learning, and robotics. He has completed his undergraduate degree in computer science & engineering after securing 1st rank in the department. He got interested in research work while pursuing a master's degree at the New Jersey Institute of Technology in Information Systems. He later got 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.

According to news publication Media Hindustan during his second master's degree at the University of Delaware, he worked for two years on a research project funded by the National Oceanic and Atmospheric Administration (NOAA), the US government. It entails predicting the occurrence of surface runoff and its magnitude in order to alert farmers. Surface runoff occurs when nutrients are swept away into bodies of water, primarily as a result of heavy precipitation. It is detrimental to both the economy and the environment. Because of the loss of nutrients from agricultural fields, it has a negative impact on crop production and profit. It also pollutes the water, causing harmful algal blooms and hypoxia in the Great Lakes region. As a result, the alerting system is critical for preventing water pollution by reducing the effort, cost, and time required.

The current physics-based model used by NOAA does not perform well. So the goal of his research was to improve performance by utilising a machine learning algorithm for surface runoff and risk level prediction. He anticipate that this research will continue to focus on deep learning to improve model performance.
Chirantan's competence and curiosity have led him to work for a year on another research project financed by the National Institute of Health (NIH), the government of the United States. In this project, he used deep learning-based multi-segmentation to segment small RNA cells. This helps to automate the process, which decreases the complexity of manually segmenting the cell wall by minimising mistake and time.

All of this research has inspired him to conduct additional research on computer vision and deep learning at Lehigh University as a Ph.D. student beginning in the Fall of 2022. Chirantan will return to Lehigh to conduct research that will benefit society. One of his potential research projects will be to identify fake news among the abundance of online news available as videos or image content. This will aid in preventing or controlling the spread of misinformation across the internet, as well as halting any damage caused by it. He will also work on human and animal facial analytics.

His research abilities, combined with his entrepreneurial spirit, prompted him to consider launching a startup called camai.us, which is still in its early stages. Camai.us is intended to solve any object detection or identification problem, similar to Google Lens, but with greater accuracy and on any camera-equipped device. What can camai.us do? It is capable of identifying any object and providing detailed information to anyone interested in learning more about it. It can also suggest similar items. The type of information it provides will be determined by the object category. For example, if it's a food dish, it will not only provide its name or content, but it will also suggest the nearest places where it can be found, as well as any reviews that are available.

Chirantan's concern for society and the safety of women has prompted him to consider establishing another organisation called hap.ai. Hap.ai will use computer vision and deep learning-based surveillance methods to detect and identify any threat and alert the appropriate organisation and the subject in question. It will assist in overcoming the majority of the challenges and security concerns associated with women, as well as promoting a safe and healthy society. It will create a safe environment for women on a school or university campus or in the workplace. It will use the surveillance camera to recognise and track people, recognise their actions, and detect a potential threat. It will monitor a person's behaviour and issue an alert if anything out of the ordinary is discovered. It will monitor a person's behaviour and send an alert if anything out of the ordinary is discovered. On the streets, it will also help women understand which areas or roads to avoid and may guide them to safety in the event of a potential threat.