Arghya Biswas

About Arghya Biswas

  • Academic Level Master’s Degree
  • Gender Male


I have studied Science, Mathematics and Computer Science for as long as I can remember throughout my school life, I have passed my class 10th examination from the ICSE board affiliated to CISCE with 90% and my class 12th examination from the ISC board which is also affiliated to CISCE with 89%. All the while I was very much attracted towards Computer Science, Mathematics, Physics and Statistics and so studied these subjects in my curriculum. After class 12th I did my Bachelor’s in Architecture from Jadavpur University, where I learnt Designing, Materials and Methods of Construction, Structures, Advanced Mathematics, 3-D Modeling, 3-D Model Rendering, Computer Aided Delineation, etc. This is where I had my practical experience in the form of a Six months Architectural Internship where I designed an entire University campus, made quantitative analysis of the materials required, kept records and updated Bill of Quantities as required. I completed my 5 years Bachelor’s Degree with First Class Honors on 10th July, 2020. In the final semester of my Bachelor’s Degree, I applied for a Master of Technology Degree in Geomatics Engineering, in Indian Institute of Technology, Roorkee, and before my thesis I was accepted into the Master’s Program, I am currently actively pursuing my M. Tech. Degree and I have had subjects like Remote Sensing and Digital Image Processing, Photogrammetry, Optimization Techniques, Geodesy and GPS Surveying in the first semester, while I have studied Advanced Digital Image Processing, Analytical and Digital Photogrammetry, Thermal, Microwave and Hyperspectral Remote Sensing and Theory and Applications of Geographical Information Systems in the second semester. I also worked on my seminar the idea of which would become my thesis for the final year. My topic is Unmanned Air Vehicles in Vehicle Detection, for which I extensively studied various pre-existing reports on the traditional object detection models and the evolutionary Deep Learning Models. I had decided to focus my thesis on the One Stage Deep Learning Object Detection Models rather than the Two Stage Deep Learning Models, out of which YOLOv3, v4, v5, YOLOR and SSD Models have attracted my interest due to them being both very fast and almost as accurate as the Two Stage Models. Throughout all these I have pursued various self paced courses on Computer Architecture, Data Science, Artificial Intelligence, Web Development, and so on. I have been fond of information handling since the beginning. Data and how the world works through data fascinates me.