With a 7+ years of SE experience, I’ve been fortunate to lead innovation in software engineering management, with a specialized focus on cloud computing and automation. My true passion lies in seamlessly connecting technology with business, ensuring the delivery of exceptional solutions that align perfectly with customers' needs.
As a Software Engineer at Cardinal Health, I am leading the design and development of conversational AI chatbots, leveraging cutting-edge technology to revolutionize healthcare automation, collaborating closely with cross-functional teams to ensure timely delivery of top-notch products.
I’m best reached via email (supriti.ghosh.ju@gmail.com). I’m always open to interesting and engaging conversations and I appreciate feedback from others.
Member of Technical Staff (MTS)
Software Engineer at the Biocomputational Biological Engineering Lab, Department of Biomedical Engineering
January 2021 - December 2021, Vermillion, SD 57069
Machine Learning (ML) Engineer at the 2AI- Applied Artificial Intelligence Research Lab, Department of Computer Science
March 2020 - November 2020, Ames, IA 50010
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January 2021 - May 2022
MS in Computer SciencePublicationsTaken Courses
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January 2016 - January 2018
MS in Information TechnologyPublicationsTaken Courses
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December 2011 - December 2015
BS in Information TechnologyTaken Courses
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September 2022
As an engineer standing between the dynamic worlds of technology and healthcare, is a pivotal point where the career path could be profoundly shaped by the choice. Both fields offer immense opportunities for growth, innovation, and the chance to make a difference, but they each come with their own set of challenges and rewards. |
For this project, we have used Prometheus, Grafana and C++. For visualization of the data, beegfs-mon provides predefined Grafana dashboards and charts to provide insight into both the health and performance of the filesystem. The service and the Grafana panels are contained in the optional beegfs-mon package. The package is available from the general BeeGFS repository.
AI-guided algorithms have been utilized to screen CT scans for Covid-19 analysis. A total of 1, 810 CT scan datasets have been collected for this project where 1, 267 Covid-19 patients’ and 543 healthy patients’ CT Scans. The pre-trained models InceptionNet V3 and U-net have been used for training purposes. K-fold cross-validation has been used to verify a better model. Our main goal was to show which model can perform better to detect, localize and segment Covid-19 cases using CT scan images so that we can use one or two globalized models for Covid-19 analysis.
Used 400 images in total (200—200 - balanced data) in this project. Trained Neural Network with three different activation functions- a) linear, b) Sigmoid, and c) Tanh. Used k (=5)-fold cross-validation and computed the confusion matrix, precision, recall, and F1-score. Reported which kernel performs better of all.
In this project, used Python to cluster documents. At first, fetched Wikipedia articles and then represented each article as a vector. Performed k-means clustering to cluster documents and then evaluated the result.
In this project, collected temperature and humidity data for continuously two hours on five different days using esp32, DHT11, MQTT, Raspberry Pi 4, breadboard and saved all the data in google firebase. For data plotting, used python libraries for line plotting, box plotting of temperature and humidity data and also line grid plots for three different days of temperature and humidity data. Then data has been pre-processed and linear regression models have been used for data analysis of MSE, AIC and also to plot the actual and predicted values.
Used PostgreSQL to manage big datasets for Internet-of-Things in this project. Also used python to change the time format (UNIT time to dd-mm-yy) and after that, included 4000 rows of data in the PostgreSQL to store and process.
Used Python libraries to detect fake jobs. The dataset contains of 18k job descriptions where around 800 false job descriptions is also included. Used logistic regression model because it can be used when the dependent variable is binary and also the dataset has been used to train and classify suspicious job descriptions.
Used automated iris recognition for personal identification to verify both uniqueness of the human iris and also its performance as a biometric based system. The performance of research was measured for stored database which is scored 0% each for False Reject Rate (FRR) and False Accept Rate (FAR) and consequently, iris recognition is shown to be a precise and reliable biometric technology.
Designed a database for the hotel management system. In this project, created relations between customers, HR, services of the hotel etc. It would allow the hotel management to handle all hotel activities.
In this project, developed an application software in C# entitled “Final Result Processing System” which is a desktop application where the teachers can insert students databases, calculate results and Grade Point Average. The teachers could log in and update the student databases and results. The mark would be calculated automatically and saved in this software for future use. The application is built through C#, MySQL and provides the flexibility to add, modify or recreate new results for students.
This is a web service based application where the list of books can be saved in the database. People can log in and can read books and can also hire or purchase books. The application is built through PHP & MySQL.
This is a hardware based device which is used in basic calculators, digital clocks, electronic meters and other electronic devices. This is a procedure of electronic display device for displaying decimal numerals.
A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. NoSQL databases are increasingly used in big data and real-time web applications. NoSQL systems are also sometimes called Not only SQL to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures.
Courses:
The basic steps of this course:
This is a path to a career in data analytics. Courses:
Across these four courses, learnt how to use the PostgreSQL database and explore topics ranging from database design to database architecture and deployment. Also, comparing and contrasting SQL and NoSQL approaches to database design. Courses:
This skills-based specialization is intended for learners who want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. - GitHub
Courses:
This Specialization is designed for data-focused developers, scientists, and analysts familiar with the Python and SQL programming languages and can learn how to build, train, and deploy scalable, end-to-end ML pipelines - both automated and human-in-the-loop. - GitHub
Courses:
This specialization is a good next step after completing Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that we can proceed with confidence to specializations like Applied Data Science with Python. - GitHub
Courses:
This Specialization builds on the success of the Python for Everybody course and introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. - GitHub
Courses:
This course is a complete guide to master the SDIs. It is created by hiring managers who’ve been working at Google, Facebook, Microsoft, and Amazon. We’ve carefully chosen a set of questions that have not only been repeatedly asked at top companies, but also provide a thorough experience to handle any system design problem.
This course is the basics of digital marketing and there are 26 modules to explore, all created by Google trainers, packed full of practical exercises and real-world examples to help turn knowledge into action.
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KC Santosh, Supriti Ghosh, Debasmita GhoshRoy, International Journal of Pattern Recognition & Artificial Intelligence (IJPRAI). |
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KC Santosh, Supriti Ghosh, The 4th International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R), Msida, Malta. |
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July 2016
Supriti Ghosh, Mohammad Abu Yousuf, International Journal of Advanced Engineering, Management and Science (IJAEMS), ISSN- 2454-1311, Vol-2, Issue-7. |
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Munira Akter Lata, Supriti Ghosh, Farjana Bobi, Mohammad Abu Yousuf, 5th International Conference on Informatics, Electronics and Vision (ICIEV 2016), Dhaka, Bangladesh. |
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September 2022
Led a session in YWIT 2022 event to inspire young women to continue to pursue their interest in technology education and careers and presented web scraping in python which means how to process of gathering information using automatic method to obtain large amounts of data from websites where most of this data can be unstructured data in Python. |
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April 2022
Presented research in the IdeaFest 2022 at the University of South Dakota (USD). |
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December 2021
Presented paper in the International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R). |
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April 2021
Presented research proposal in the IdeaFest 2021 at the University of South Dakota (USD). |
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Presented my research in the seminar lecture series of department of computer science at the University of South Dakota (USD). |
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Cardinal Health |
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University Merit Scholarship2018
Top 10% in Graduate Level, Jahangirnagar University, Dhaka, Bangladesh. |
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University Merit Scholarship2016
Top 20% in Undergraduate Level, Jahangirnagar University, Dhaka, Bangladesh. |
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Sep 2022
NetApp Inc, Cranberry Township, PA 16066. |
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Aug'21 - Jun'22
Coursera, Remote. |
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Jul'22 - present
NetApp Inc, Cranberry Township, PA 16066. |
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Mar 2022
Teens in AI x Harvard x MIT Hackathon, Cambridge, MA. |
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Oct 2022
SN Computer Science, Remote. |
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Jul'21 - May'22
Association for Computing Machinery (ACM), University of South Dakota, Vermillion, SD 57069. |
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Mar 2021
Teens in AI, San Francisco, CA. |
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Sep'19 - Oct'20
YSS (Youth Standing Strong), Ames, IA 50010. |
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May'15 - May'16
IEEE Student Branch, Jahangirnagar University, Dhaka, Bangladesh. |
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May 2015
International Conference on Electrical Engineering and Information & Communication Technology’ 2015. |
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Mar'24 - p
Member |
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Oct'20 - Dec'23
Member |
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May'15 - May'16
Student Member |
