Dr. Saumendra Mohanty possesses over 35 years of extensive experience in
leadership roles within Global Technology MNC Companies, coupled with an
impressive track record of 5 years in academics, focusing on teaching
and research. He has made significant contributions as a Visiting &
Adjunct Professor in esteemed institutions where he imparts knowledge in
the fields of Data Science, Statistics, Artificial Intelligence, Machine
Learning & Information Technology
Furthermore, Dr. Mohanty is a Research Guide for 4 PhD Scholars at IIC
University of Technology in Cambodia and Liutebm University, School of
International Programs, Lusaka, Zambia and Swiss School of Management,
Geneva, program conducted through GradXs (an educational support service
organisation).
He is also actively engaged in conducting PhD coursework centered around
"Statistical Research Techniques," utilizing tools and platforms such as
SPSS, Jamovi, Orange, Python, and Excel to facilitate comprehensive
learning experiences for the PhD Research Scholars and is Author of Book
titled “ Decoding Machine & Deep Learning with Python “
Dr. Mohanty's academic journey includes a B.Tech degree in Electronics
from the prestigious National Institute of Technology (NIT Calicut,
1984-88), a PGP from the International Management Institute (IMI New
Delhi, 1990-92), and PhD from IIC University of Technology (a member of
the International Association of Universities, IAU) with PhD Course Work
from Sharda University.
Throughout his career, he has made valuable contributions to renowned
companies such as Wipro, Hughes USA, Primus, and Twilio USA,
demonstrating his expertise and leadership in the technology industry.
Dr. Mohanty's rich background in academia and industry positions him as
an accomplished professional with a profound impact on the realms of
education, research, and technological innovation
Concurrent with current assignment in Corporate sector, a serial
entrepreneur with successful exits from two Start-ups via Merger and
Acquisition and raised Seed Fund from Department of Science & Technology
(DST) Start-up Accelerator
