CURRICULUM VITAE

Ms. SANCHARI CHATTERJEE

To continue a deep passion and strong interest in my journey as an innovative academic leader and passionate technologist to explore a magnificent career in teaching and research as Computer Scientist, Instructional Faculty in Healthcare Informatics, Computer Science or Information Science domain. Currently I am a fifth year Ph.D. student in the department of Computing and Informatics at UNC-Charlotte and am looking for an academic career to dedicatedly help students to achieve great success using both traditional and modern approaches.

·   Ph.D. in Computer Science & Engineering                                                              CGPA – 3.94 / 4.0

        Dept. of Computing Science, University of North Carolina, NC, USA               (2021 - Present)

    Thesis Topic: Cloud Mining Actionable Pattern Discovery in BigData.

    Relevant Courses – Cloud Computing, Artificial Intelligence, Wireless and Mobile Computing, Ad Hoc and Sensor Networks, Advanced Algorithm I, Sensor Systems, Intelligence Data Analysis, Android Development, Computer Graphics, Large Scale Software Engineering

·   MS in Computer Science                                                                                           CGPA – 3.93 / 4.0

      Dept. of Computing Science, University of North Carolina, NC, USA                 (2018 - 2020)

      Thesis Topic: Working on Recommender system in Healthcare.

      Relevant Courses – Artificial Intelligence I, Network Security, Advanced data Model, Computer Security I, Advanced Operating Systems, Data Warehouse Design, Biomorphic Systems, Data Warehouse Design, Biomorphic Systems 

·       https://webpages.charlotte.edu/schatt10/

·       https://webpages.charlotte.edu/ras/students-2022.html

·       https://webpages.charlotte.edu/aatzache/mentoring.html

Ø  Instructor of Record – Fall 2025 – Present

Department of Computer Science, College of Computing and Informatics

University of North Carolina, Charlotte

Courses:

Database and Design Implementation ITSC 3160

Data Structure and Algorithm ITSC 2214

Ø  Adjunct Instructor – Fall 2023 – Present

Department of Computer Science and Engineering, College of STEM,

Johnson C. Smith University, Charlotte, NC – 28216

Courses: CSC 438A- Database Management System, CSC 131- Computers in Society, CSC335A – Internet Programming

Responsibilities includes-

·   Developing and delivering course material, curricula, and syllabi.

·   Assisting with the training and recruitment of new lecturers, teaching assistants, and Professors.

·   Conducting research, publishing papers, and attending conferences.

·   Attending academic events and networking with other researchers and field experts.

·   Supervising, advising, and mentoring teaching assistants and undergraduate students.

·   Participating in faculty and departmental meetings.

·   Shortlisting, interviewing, and selecting students for undergraduate scholarship programs.

·   Organizing guest seminars and faculty events where students can interact with established industry professionals.

·   Traveling to other higher education settings to gain experience and expand networks.

·   Writing proposals to secure research funding.

Ø  Faculty Research Assistant – Fall 2024 – Summer 2025

Department of Computer Science and Engineering, College of STEM,

Johnson C. Smith University, Charlotte, NC – 28216

Project - AIM-AHEAD Program for Artificial Intelligence Readiness (PAIR)

This project aims to leverage AIM-AHEAD resources to jump start AI research for health equity in minority serving institutions (MSI) with inadequate resources. And this program is designed for these organizations to strengthen the foundations for sustainable success in AI/ML health equity research.

Specific Aims:

Metabolic Syndrome (MetS), as defined by the Joint Scientific Statement harmonized criteria, is the clustering of at least three of five cardiometabolic risk factors (elevations in waist circumference, blood pressure, fasting blood glucose, triglycerides and HDLc or appropriate medications) and has increased in prevalence from 36.2% in 1999 to 47.3% in 2018. MetS increases risk for the development and progression of cardiometabolic diseases. However, despite greater morbidity and mortality from hypertension, diabetes, stroke and other cardiometabolic conditions, Black Americans are reported to have a lower prevalence of MetS than White Americans. The long-term goal of this research is to reduce racial and ethnic disparities in cardiometabolic disease prevalence and related morbidity and mortality by improving accuracy of cardiometabolic disease definitions in minoritized groups, increasing cardiometabolic health literacy and increasing health equity for minority populations. The major objective of this application is to leverage artificial intelligence and machine learning (AI/ML) with demographic, anthropometric, clinical, blood biomarker, psychosocial, and lifestyle information to better identify predictors of cardiometabolic risk within racial subgroups for more targeted prevention efforts

Our central hypotheses are (1) that race and sex-specific MetS algorithms can be generated and (2) that these algorithms will improve identification of individuals at elevated risk for poor cardiometabolic outcomes such as cardiovascular disease or diabetes. ML algorithms, particularly Random Forest algorithms, have been reported to enhance prediction of MetS, diabetes, and cardiovascular disease. Random Forest modeling has also been used to identify race and ethnicity specific features of importance in predicting MetS. For example, in a Mexican population Random Forest modeling identified waist/hip ratio was as a better index of abdominal obesity than waist circumference, which is considered a MetS component by most definitions. Our specific aims are:

Aim 1- To identify race- and sex-specific MetS Random Forest algorithms with identified Variables of Importance for Black and White Adults.

Aim 2- To determine the predictive accuracy of the RF generated MetS algorithms (top 5 features of Importance) in cardiometabolic disease incidence.

Ø  Teaching Assistant/ Research Assistant/ Graduate Assistant – 2021 - 2024

·     Software Design and Implementation ITCS 6112 – worked as a volunteer teaching assistant at UNC-Charlotte

·     Knowledge Discovery in Database ITCS 6162– worked as a volunteer teaching assistant at UNC-Charlotte

·     Cloud Computing for Data Analysis ITCS 6190– worked as a volunteer teaching assistant at UNC-Charlotte

·     Cyber Security Introduction– worked as a volunteer teaching assistant at West Virginia University (WVU)

·     Practicing Cyber Security Attacks and Counter Measures– worked as a volunteer teaching assistant at West Virginia University (WVU)

·     Machine Learning – worked as a volunteer teaching assistant at UNC- Charlotte

·     Introduction to Computer Systems and Assembly Programming– worked as a volunteer teaching assistant at West Virginia University (WVU)

·     Introduction to Computer Networks– worked as a volunteer teaching assistant at Central Piedmont Community College (CPCC)

• Software Design and Implementation ITCS 6112
• Database Design ITCS 6160
• Operating System and Design ITCS 6144
• Intelligent System ITCS 6150
• Computer Communication and Networks ITCS 6166
• Knowledge Discovery in Database ITCS 6162
• Algorithm and Data Structure ITCS 6114
• Machine Learning ITCS 6156
• Survey of Programming Language ITCS 5102
• Cloud Computing for Data Analysis ITCS 6190
• Survey of Recommender system in Health Informatics – Individual Study

·       Microsoft 365 Package

·       Amazon AWS Cluster in Cloud Computing

·       Amazon Cloud S3 Bucket

·       Java using Eclipse

·       Python using virtual platform

·       Scala using Eclipse

·       HTML using Kompzer

·       Kotlin

·       SQL Database and MySQL

·       Github System

·       Agile Management

·       WEKA software for support vector machine

·       Lisp Miner

·       "A Dual-Agent Architecture for Efficient and Scalable Document Processing and Intelligent Retrieval" (Southeast Conference 2025)

·       "Flight Delay Prediction Using Random Forest with Enhanced Feature Engineering" (Southeast Conference 2025)

·       "Cardi-GPT: an Expert ECG-Record Processing Chatbot" (Southeast Conference 2025)

·       “Enhancing Ecological Forecasting with LSTM Models: the Impact of Partition-Based Data Shuffling on Predictive Accuracy” (Southeast Conference 2025)

·       "A Low-Power IoT-Based Smart Desk Integrated with a Classroom Response System" (Southeast Conference 2024)

·       "Strengthening the Nigerian Grid: Impact of SCR Thresholds on Synchronous Condenser Allocation for Inverter-Based Generation Integration" (SoutheastCon 2024)

·       “Altruistic Asd (Autism Spectrum Disorder) Virtual Reality Game Assisting Neurotypicals Understanding Of Autistic People” in 10th International Conference on Computer Science and Information Technology (CoSIT 2023)

·       “Unsupervised Adversarial and Cycle Consistent Feature Extraction Network for Intelligent Fault Diagnosis” in Applied Soft Computing Journal (2023)

·       ACM Tapia Conference (2023)

·       “Bangla Speech Emotion Detection Using Machine Learning Ensemble Methods” in Advances in Science, Technology and Engineering Systems Journal (ASTESJ) (2022)

·       “Fish Images Classification Based On Robust Features Extraction From Shape Signature Using Rbfnn And Svm” in 9th International Conference on Computer Science and Information Technology (CoSIT 2022)

·       “Trust for Big Data Usage in Cloud “ in 12^th International Conference on Computer Science, Engineering and Applications(CCSEA 2022)

·       “Cryptographic  Algorithms Identification Based On Deep Learning” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “Deep Learning-Based Plant Diseases Recognition” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “Energy Consumption Forecasting In Industrial Sector With Machine Learning Algorithms” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “An Online Graphical User Interface Application to Remove Barriers in the Process of Learning Neural Networks and Deep Learning Concepts Using TensorFlow” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “Blockchain Security: Enhanced Control Evaluation Approach To Safeguard Organizations’ Accounting Information” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “The Effectiveness Of Applying Different Strategies On Recognition And Recall Textual Password” in 3^rd International Conference on Artificial Intelligence and Machine Learning(CAIML 2022,July)

·       “Universal Pooling - A New Pooling Method for Convolutional Neural Networks “ in Expert Systems With Applications (ESWA 2020)

·       "SA-MSVM: A Hybrid Heuristic Algorithm Based Feature Selection for Sentiment Analysis in Twitter Bigdata" in Journal of Intelligent & Fuzzy Systems (2020)

·       ProjeQtor- This is a project management tool using php, found black box testing and white box testing, the challenges we faced, especially in reverse engineering leading the future work related to it.

·       Operating System Measurement- To measure the characteristic and understanding the performance of CPU and OS Services, Memory and File System.

·       Movie Theatre- By the help of MYSQL Workbench formed a database of movie theatre having 2D and 3D movie screen. Each screen has different movies in different format at different times or even the same movie at different times throughout the day. Additional features like customers can put feedback were included.

·       A star algorithm - Comparison between Manhattan and Misplaced Tiles algorithms, we had to find the heuristics and run four different input case to find the ouput and which method is more efficient.

·       Socket programming with HTTP Client and HTTP Server-Created HTTP Client and HTTP server in java and connecting them through HTTP Port.

·       Algorithm and data structure related various projects in java.

·       Extraction of Action Rules and Classification Rules-Used different logics and techniques.

·       Extraction of Action Rules and Classification Rules-Used different logics and techniques.

·       Android application- The news application in kotlin.

·       Evaluation of supervised learning algorithm -comparison report of supervised machine learning algorithms. New York Taxi Fare dataset from Kaggle were used for the analysis. Based on the accuracy, precision, recall and F1 score, two best algorithms were determined.

·       Survey of Recommender System-Compare the different recommender systems in Healthcare and found the suitable recommender system for different field.

·       Reviewed a paper-An interpretable mortality prediction model for Covid-19 Patients.

1.   Tzacheva, A. A., Chatterjee, S., Shaik, R. S., and Chakinala, S. S. P., "Discovery Of Actionable Pattern In Bigdata Using Information Granules And Meta Action With Cost And Feasibility For Emotion Detection" In 11th International Conference on Data Mining (DTMN 2025), Vol.15, No. 20, pp 257-272, October 25 - 26, 2025, Vienna, Austria, ISSN : 2231 - 5403.

DOI: 10.5121/csit.2025.152019

https://aircconline.com/csit/papers/vol15/csit152019.pdf

2.   Chatterjee, S, and Tzacheva, A A., “Mining Actionable Patterns in BigData for Enhanced Human Emotions” In International Journal of Data Mining & Knowledge Management Process (IJDKP), Vol.13, No. 1, pp 1 - 22, January 2025

    DOI: 10.5121/ijdkp.2025.15101

    https://aircconline.com/ijdkp/V15N1/15125ijdkp01.pdf

3.   Tzacheva, A A., and Chatterjee, S, “ Actionable Pattern Discovery for Emotion Detection in Big Data in Education and Business” In International Conference on AI, Machine Learning and Data Science (AIMDS 2024), Vol.13, No 6, pp 93 - 117 , December 2024

     DOI: 10.5121/ijci.2024.130607

     https://ijcionline.com/paper/13/13624ijci07.pdf

4.     Tzacheva, A.A., Chatterjee, S., and Ras, Z.W., "Discovery of Actionable Patterns through Scalable Vertical Data Split Method with Meta Actions and Information Granules" , In International Journal of Data Mining & Knowledge Management Process (IJDKP), Vol.13, No. 1/2, March 2024,  pp 17 - 42
DOI:10.5121/ijdkp.2023.14202
https://aircconline.com/ijdkp/V14N2/14224ijdkp02.pdf

5.   Chatterjee S., Tzacheva, A.A., Ras, Z.W., “Scalable Action Mining For Improving Customer Satisfaction”, 3rd International Conference on NLP, Data Mining and Machine Learning (NLDML 2024), January 13 ~ 14, 2024, Virtual Conference https://ijcionline.com/volume/v13n1

6.   Tzacheva, A.A., Chatterjee S., Ras, Z.W., “Cloud Mining Actionable Pattern Discovery In Big Data: A Survey”, in Transactions on Machine Learning and Artificial Intelligence (TMLAI), Vol.10, No.3, 2022

     DOI:https://doi.org/10.14738/tmlai.103.2022
https://journals.scholarpublishing.org/index.php/TMLAI/issue/view/406

7.   Sanchari Chatterjee -"Studying the Risk of Backdoors In Encrypted Systems" in Tapia 2019 Conference in San Diego, CA in September 2019.

8.   Sanchari Chatterjee, Sanghamitra Chatterjee, "Logical Models Using Boolean Network to Study Breast Cancer Signaling Pathways. “Published by International Research Journal of Advanced Engineering and Science (I.R.J.A.E.S) in the year 2017.

·         Reviewer at SoutheastCon 2024, Atlanta.

·         Scholarship Attendee at Tapia Conference 2022, Washington, D.C.

·         Reviewer at Tapia Conference 2023, TX.

·         CRA Woman Conference in April 2023 in San Francisco, CA, as Scholarship Recipient