When I've met Dyuti, I was deeply impressed by her enthusiasm and ability to adapt into the corporate world as she was fresh from academia, just after completing her postdoctoral research at Harvard. After our initial introduction, she further influenced me to engage in long discussions over lunch and coffee breaks about Python, neural networks, time series analysis nad methods of data cleaning. Recently, I got the opportunity to collaborate with her in the same project and again she quickly engaged her time in learning relevant software technologies like Docker, Kubernetes. Dyuti is highly motivated, open-minded person that wants to explore research topics to the deep scientific and engineering understanding. Coming from a strong academic background, she is well versed with insights of statistical modeling and coding and toghether with her quick adaptability into any new skills or information it is her standout trait. Dyuti is very dedicated, self-motivated and earns my highest recommendation.

Enthusiastic learner is the phrase that comes to my mind when I think about Dyuti. I have had the pleasure to meet Dyuti at ABB Corporate Research Center during which we collaborated on an ongoing project regarding the battery storage systems monitoring. She joined the project in between but quickly went through the thousands of lines of code and the background materials in a very short period of time, though the line of work was far from her area of expertise. She soon became an active member of our daily agile stand up and she came up with some completely new ideas for long term prediction of battery health using various machine learning techniques. Her intense work alone became another independent project which may lead to a possible publication. Although she joined the team in between it did not stop her to contribute and give it a new direction, which is her strong personality trait. Dyuti would be a true asset for any positions requiring innovative thinking, heavy coding and knowledge of statistical mechanical and machine learning tools.

When I've met Dyuti, I was deeply impressed by her enthusiasm and ability to adapt into the corporate world as she was fresh from academia, just after completing her postdoctoral research at Harvard. After our initial introduction, she further influenced me to engage in long discussions over lunch and coffee breaks about Python, neural networks, time series analysis nad methods of data cleaning. Recently, I got the opportunity to collaborate with her in the same project and again she quickly engaged her time in learning relevant software technologies like Docker, Kubernetes. Dyuti is highly motivated, open-minded person that wants to explore research topics to the deep scientific and engineering understanding. Coming from a strong academic background, she is well versed with insights of statistical modeling and coding and toghether with her quick adaptability into any new skills or information it is her standout trait. Dyuti is very dedicated, self-motivated and earns my highest recommendation.

Enthusiastic learner is the phrase that comes to my mind when I think about Dyuti. I have had the pleasure to meet Dyuti at ABB Corporate Research Center during which we collaborated on an ongoing project regarding the battery storage systems monitoring. She joined the project in between but quickly went through the thousands of lines of code and the background materials in a very short period of time, though the line of work was far from her area of expertise. She soon became an active member of our daily agile stand up and she came up with some completely new ideas for long term prediction of battery health using various machine learning techniques. Her intense work alone became another independent project which may lead to a possible publication. Although she joined the team in between it did not stop her to contribute and give it a new direction, which is her strong personality trait. Dyuti would be a true asset for any positions requiring innovative thinking, heavy coding and knowledge of statistical mechanical and machine learning tools.

When I've met Dyuti, I was deeply impressed by her enthusiasm and ability to adapt into the corporate world as she was fresh from academia, just after completing her postdoctoral research at Harvard. After our initial introduction, she further influenced me to engage in long discussions over lunch and coffee breaks about Python, neural networks, time series analysis nad methods of data cleaning. Recently, I got the opportunity to collaborate with her in the same project and again she quickly engaged her time in learning relevant software technologies like Docker, Kubernetes. Dyuti is highly motivated, open-minded person that wants to explore research topics to the deep scientific and engineering understanding. Coming from a strong academic background, she is well versed with insights of statistical modeling and coding and toghether with her quick adaptability into any new skills or information it is her standout trait. Dyuti is very dedicated, self-motivated and earns my highest recommendation.

Enthusiastic learner is the phrase that comes to my mind when I think about Dyuti. I have had the pleasure to meet Dyuti at ABB Corporate Research Center during which we collaborated on an ongoing project regarding the battery storage systems monitoring. She joined the project in between but quickly went through the thousands of lines of code and the background materials in a very short period of time, though the line of work was far from her area of expertise. She soon became an active member of our daily agile stand up and she came up with some completely new ideas for long term prediction of battery health using various machine learning techniques. Her intense work alone became another independent project which may lead to a possible publication. Although she joined the team in between it did not stop her to contribute and give it a new direction, which is her strong personality trait. Dyuti would be a true asset for any positions requiring innovative thinking, heavy coding and knowledge of statistical mechanical and machine learning tools.