Dr Kaushik Mahata’s purpose-built mathematical processes are making new engineering innovations, solutions and products, possible.

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April 11, 2022
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Anditi is excited to announce the appointment of Dr Kaushik Mahata as Chief Data Officer. Dr Mahata is a world-renowned expert in signal and image processing with over 120 peer-reviewed published research works. Dr Mahata has a degree in Electrical Engineering from Jadavpur University, a Masters's in Signal Processing from the Indian Institute of Science and a Doctorate in Signal Processing from Uppsala University, Sweden.

Dr Mahata has experience in engineering and manufacturing combined with nearly two decades of experience in academia, most recently with the University of Newcastle, Australia. As an Associate Professor with the School of Electrical Engineering and Computing, he focused on developing mathematical algorithms and manipulating data to solve complex problems and inform real-world solutions. During his tenure, he led several large-scale industry and government-funded projects that resulted in 5 PhD and 3 Masters theses amongst his students.

Dr Mahata will work closely with Anditi Managing Director Peter Jamieson and other recent hires, including ex-JPMorgan banker Frances Agelavu and Microsoft alumni Tony Campbell, who joined in 2021 as COO and Head of Business Development, respectively. Both bring a wealth of overseas experience to Anditi. Jamieson, Agelavu and Campbell are all UoN graduates.

"For the past six years, Anditi has been developing cutting edge analytical solutions in collaboration with Kaushik and his team at the University of Newcastle. The natural progression for Kaushik to join the team has been a natural fit, as we take our business to the next level" - Peter Jamieson.

This announcement is a testament to Anditi's commitment to innovation and the provision of solutions in the transformation and analysis of remote sensing data.

Links to Dr Mahata's work

University of Newcastle: The clever processes driving new engineering solutions

Reseach:Direct Tip-Sample Force Estimation for High-Speed Dynamic Mode Atomic Force Microscopy

Google Scholar

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