Sujata is an Indian studying PhD at Tokyo Metropolitan University in Tokyo, Japan. She offered MEXT scholarship for her PhD studies. Her major is AutoML and Information Visualization System. She is leading Google Developer Student Club from her university from 2021-2022. She is an Ambassador of Women Techmakers in Japan. She is in the lead role of Microsoft Learn Student Ambassador at Tokyo Metropolitan University. She organized technical events to develop programming skills of the latest technology trends among students. She is also a member of the Flexible Design Scientist Interfaculty Program (FDSIP). She is an active member of Google Developers Community, WDA Japan, tinyml, 2d3d.ai, MLTokyo, Tokyo Python Society, GeoTokyo, GCPUG, Technovation Girls, Creative Tokyo, ODSC, mHealthIsrael, AI, and Cloud Innovation.
PhD, Takama Laboratory
Tokyo Metropolitan University, Japan
Doctor of Philosophy in Computer Science • April 2021 - March 2024
I am researching mainly Automated Machine Learning (AutoML) and Information Visualization. I also have a keen interest in NLP, Data Science, and Web Development. My Ph.D. research will add up my knowledge to contribute to data science and machine learning to develop advanced information visualization techniques for multiple applications such as digital humanities, real-time tracking, intellectual property, etc.
Master of Philosophy in Computer Science• Aug 2015 - April 2017
In 2015, I was closely related to data science and machine learning during my master's of philosophy in computer science at Chaudhary Ranbir Singh University in India. I worked as a teaching assistant to sharpen my skills and took the hands-on experience in soft computing and MATLAB. In my post-graduation project, I took a bold step and considered deep neural networks for computer vision applications to include in my research. My master thesis was on "Japanese Historical Character Recognition using Deep Convolutional Neural Network (DCNN) with Drop Block Regularization."
Masters of Science in Computer Science • Aug 2013 - May 2015
I have studied various computer science concepts deeply in my Master's degree. To solve computational problems and design solution-based algorithms, I took hands-on sessions in Data Structure and Algorithms along with Discrete Mathematics, C, C++, Software Engineering, Database Management Systems, Computer Graphics, Computer Networks, and Artificial Intelligence.
Bachelors of Science in Computer Science• Aug 2010 - May 2013
I have studied Mathematics, Physics, and Computer Science subjects in my Bachelor's degree. To learn the basics of these subjects, I have to continually focus on different patterns of how these concepts are related to real life.
Ambassador/Founder at Tokyo Metropolitan University • Jan 2022 - Present
I was selected as Microsoft Learn Student Ambassador in January 2022. I am so fortunate that I was given this opportunity to learn and grow with this profound tech community spreading around the globe. I am responsible to joined a technical path and learning from Microsoft resources. To extend this knowledge, I need to organize technical events collaborating with other ambassadors and industry professionals.
Mentor• Dec 2021 - March 2022
I was selected as a mentor in the Technovation Girls Coding challenge. I guided junior high school and high school girls on how to develop a theme-based mobile application and deploy it within time and budget.
Ambassador• Sep 2021 - Present
When I was given this opportunity, I realized the potential of women in technical fields. We can't ignore that the women percentage in this industry is considerably less than men. We need more women to balance the ratio and encourage them by providing valuable resources.
GDSC Lead/Founder at Tokyo Metropolitan University • Aug 2021 - Present
I was selected as a GDSC Lead at Tokyo Metropolitan University in the 2021-2022 session. I was dealing with two major problems in my institution: a lack of technical knowledge as per the latest trends among students and the second is communication. My job is to approach the students by all possible methods and deliver the technical content so they can secure a career in the tech industry.
Product Supervisor Intern, Bio-Metric Devices and Applications • Mar 2016 - Sep 2016
I have handled the Bio-Metric data of multiple users for fingerprint identification in Government State Examination Centers. My job is to travel to each center, collect the data, process it, and securely deliver it.
Teaching Assistant, Soft-Computing and Matlab • Sep 2015 - Feb 2016
I have worked as a teaching assistant at C.R.S University under the guidance of Prof. Anumpan Bhatia and Prof. Harish Rohil. I taught Soft computing, where I mainly focused on Neural Networks, fuzzy logic, and genetic algorithm. Also, I had given programming classes in MATLAB.
Sujata Saini, Vishal Verma, “Japanese Historical Character Recognition using Deep Convolutional Neural Network (DCNN) with DropBlock Regularization,” International Journal of Recent Technology and Engineering, Volume-8, Issue-2, July 2019, pp. 3510-3515.
Sujata Saini, Hiroki Shibata, Yasufumi Takama “Toward Construction of Handwritten Indus Signs Dataset” The 10th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA2022) Sep.23-Sep.25, 2022, Beijing, China.
Doctoral Course, Tokyo Metropolitan University • April 2021 - March 2024
Japanese Government (Monbukagakusho: MEXT) University Recommendation Scholarship under Flexible Design Scientist Interfaculty Program (FDSIP)
Automated Machine Learning Scholarship, Germany• Nov 2021
I was selected as one of the top five students who got this scholarship worldwide. This programme organized with the collaboration of Leibniz University Hannover, University of Freiburg & Bosch Center for Artificial Intelligence and Ludwig-Maximilians University Munich & Munich Center of Machine Learning.
Python, R, MATLAB, C, C++, SQL
Tensorflow, PyTorch, Keras, Caffe, OpenCV, Scikit-Learn, Numpy, SciPy, Matplotlib, Pandas, NLTK, fastai
AWS, Git, Docker, Kubernetes, Anaconda, RStudio, SAAS, Tableau
Coginitive AI Classes
Computer Vision NanoDegree
Machine Learning Crash Course with TensorFlow APIs
MicroMasters Program of Statistics and Data Science
Introduction to Digital Humanities
Collected handwritten Indus Signs data of multiple users via web application with the crowd-sourcing method.Data Collection, Web Development
IndusDraw is a mobile application that collects handwritten data in a significant amount and stores the server's data.Data Collection, Mobile Development
Mental health is essential to keep us moving with daily tasks. This app analyzes a user's mood daily and provides monthly predictions reports.Google Solution Challenge 2022
Bento Time is a mobile application that reminds the users to buy cheap and healthy food on time. It's a considerable initiative to stop food wastage in Japan. The app version is available for IOS and android, both mobile devices.Mobile App, UI/UX
Developed image classification model to recognize the Japanese historical characters using Deep Convolutional Neural Networks with DropBlock regularization method and achieve 97\% accuracy of state-of-art results.Japanese Character Recognition, Image Classification, Deep Learning
Performed Simple, Multi-Class, Convolutional Sentiment Analysis using Bi-Directional and Deep Layer RNNs, and CNNs in PyTorch.Natural Language Processing
Performed EDA and compared KNNs, Decision Trees, Logistic Regression, Naive Bayes, Random Forest on Cleveland Database.Machine Learning
Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven't found it yet, keep looking. Don't settle. As with all matters of the heart, you'll know when you find it.Steve Jobs
I'm interested in things that change the world or that affect the future and wondrous, new technology where you see it, and you're like, 'Wow, how did that even happen? How is that possible?'Elon Musk