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.
Sujata Saini
PhD, Takama Laboratory
Tokyo Metropolitan University, Japan
Doctor of Philosophy in Computer Science • April 2021 - Sep 2024
My research primarily focuses on Automated Machine Learning (AutoML) and Information Visualization, with a keen interest in Natural Language Processing (NLP), Data Science, and Web Development. Currently pursuing a Ph.D., my aim is to augment my expertise to contribute significantly to the fields of data science and machine learning. Specifically, I aspire to develop advanced information visualization techniques applicable across various domains, including digital humanities, real-time tracking, and intellectual property. Through my research endeavors, I endeavor to drive innovation and address pressing challenges in these areas.
Master of Philosophy in Computer Science• Aug 2015 - April 2017
During my pursuit of a Master's of Philosophy in Computer Science at Chaudhary Ranbir Singh University in India in 2015, I immersed myself in the realms of data science and machine learning. As a teaching assistant, I honed my skills while gaining hands-on experience in soft computing and MATLAB. For my post-graduation project, I embarked on a pioneering endeavor, exploring the application of deep neural networks in computer vision. This led to my master thesis, which delved into "Japanese Historical Character Recognition using Deep Convolutional Neural Network (DCNN) with Drop Block Regularization," showcasing my commitment to advancing the field through innovative research.
Masters of Science in Computer Science • Aug 2013 - May 2015
In pursuit of my Master's degree, I delved deeply into a myriad of computer science concepts, equipping myself with a comprehensive skill set to tackle complex computational challenges. Through intensive study and practical application, I gained expertise in areas such as Data Structures and Algorithms, Discrete Mathematics, C, C++, Software Engineering, Database Management Systems, Computer Graphics, Computer Networks, and Artificial Intelligence. These hands-on sessions provided me with the necessary foundation and proficiency to develop solution-oriented algorithms and address diverse computing problems effectively.
Bachelors of Science in Computer Science• Aug 2010 - May 2013
Throughout my Bachelor's degree, I extensively studied Mathematics, Physics, and Computer Science, honing my understanding of fundamental principles in these disciplines. A key aspect of my learning process involved continuously exploring the various patterns and connections between these subjects and real-life applications. This holistic approach not only deepened my comprehension of the material but also cultivated a practical perspective essential for addressing real-world challenges effectively.
Researcher • May 2024 - Present
At RIKEN in Tokyo, my role involves harnessing the potential of tensor-based methods to tackle the intricate challenge of image classification for historical language datasets. The primary goal is to develop algorithms capable of accurately identifying and classifying script styles and ages from various historical periods. This task is particularly challenging due to the diversity and complexity of historical scripts, which often include variations in style, degradation over time, and regional differences. My research contributes to the broader field of digital humanities by creating tools that help historians and linguists access and analyze vast archives of unreadable texts more efficiently, thereby unlocking new insights into our cultural heritage.
Teaching Assistant • April 2024 - May 2024
In April 2024, I worked as a Teaching Assistant at Tokyo Metropolitan University’s Takama Laboratory, focusing on a comprehensive one-month survey of recommendation systems. My responsibilities included supporting academic research and assisting students with the technical aspects and applications of recommendation systems. This role required me to facilitate learning by organizing tutorials, managing course materials, and providing hands-on guidance to students as they navigated complex algorithms and data analysis techniques. My contribution helped enhance the students' proficiency in developing innovative solutions tailored to real-world problems using recommendation technologies.
Lead Ambassador • April 2024 - Present
Since April 2024, I have been serving as the Lead Ambassador for IEEE's R10 Adhoc Committee on Entrepreneurship and Innovation, based in Tokyo, Japan. In this role, I am responsible for spearheading initiatives aimed at enhancing entrepreneurial capabilities and promoting innovative methodologies among engineers throughout the Asia-Pacific region. My duties involve organizing workshops, seminars, and networking events that facilitate knowledge exchange and inspire innovation. Through these efforts, we strive to empower engineers to develop groundbreaking solutions and advance technological progress across diverse industries within the region.
Vice-Head Finance • Aug 2023 - Present
Appointed as Vice Head of Finance for the Mext Scholarship Association in 2023, I leveraged this opportunity to engage with international students, address their concerns, and foster a supportive environment. My responsibilities included overseeing financial management, including budgeting, fund disbursement, and securing sponsorships. Additionally, I played a pivotal role in assisting students and coordinating various events, contributing to the association's overall success and impact.
Ambassador/Founder at Tokyo Metropolitan University • Jan 2022 - Present
Appointed as a Microsoft Learn Student Ambassador in January 2022, I am privileged to contribute to a dynamic tech community with a global footprint. My responsibilities include embarking on technical learning paths through Microsoft resources and organizing collaborative events with fellow ambassadors and industry experts, fostering continuous learning and growth within the community.
Mentor• Dec 2021 - March 2022
Honored to serve as a mentor in the Technovation Girls Coding Challenge, I provided guidance to junior high school and high school girls in developing theme-based mobile applications. Through effective mentorship, I facilitated the successful deployment of these applications within defined timeframes and budgets, empowering young women to excel in technology and innovation.
Ambassador• Sep 2021 - Present
Upon seizing this opportunity, I recognized the untapped potential of women in technical fields. Acknowledging the significant gender disparity within the industry, I advocate for initiatives that aim to empower and support women by providing valuable resources. It is imperative to strive for gender balance in the tech sector, fostering an inclusive environment that harnesses the talents of all individuals.
GDSC Lead/Founder at Tokyo Metropolitan University • Aug 2021 - Aug 2022
Appointed as a GDSC Lead at Tokyo Metropolitan University for the 2021-2022 session, I addressed key challenges within the institution, notably the gap in students' technical knowledge and communication barriers. Employing diverse outreach strategies, I endeavored to provide students with up-to-date technical content, empowering them to pursue successful careers in the ever-evolving tech industry.
Product Supervisor Intern, Bio-Metric Devices and Applications • Mar 2016 - Sep 2016
Tasked with managing biometric data for fingerprint identification at Government State Examination Centers, I executed a meticulous process involving travel to multiple centers, data collection, processing, and secure delivery. My role demanded precision and adherence to stringent security protocols to ensure the integrity and confidentiality of the data entrusted to me.
Teaching Assistant, Soft-Computing and Matlab • Sep 2015 - Feb 2016
As a teaching assistant at C.R.S University, under the mentorship of Prof. Anumpan Bhatia and Prof. Harish Rohil, I played a pivotal role in instructing Soft Computing courses. With a focus on Neural Networks, fuzzy logic, and genetic algorithms, I facilitated comprehensive learning experiences for students. Additionally, I conducted programming sessions in MATLAB, equipping students with practical skills to complement theoretical knowledge in the field.
Sujata Saini, Hiroki Shibata, Yasufumi Takama, “ Construction of Handwritten Indus Signs Dataset Employing Social Approach,” Special Issue, JACIII: Journal of Advanced Computational Intelligence and Intelligent Informatics, Volume-2, Issue-1, Jan 2024, pp. 122-128.
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.
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.
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 DevelopmentIndusDraw is a mobile application that collects handwritten data in a significant amount and stores the server's data.
Data Collection, Mobile DevelopmentMental 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 2022Bento 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/UXDeveloped 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 LearningPerformed Simple, Multi-Class, Convolutional Sentiment Analysis using Bi-Directional and Deep Layer RNNs, and CNNs in PyTorch.
Natural Language ProcessingPerformed EDA and compared KNNs, Decision Trees, Logistic Regression, Naive Bayes, Random Forest on Cleveland Database.
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