Projects
Sponsored PROJECTS:
ONGOING:
1. CAYT Operation Efficiency Improvement AI Algorithm Prototype Development
Type: R&D Industry Consultancy Project
Role: Principal Investigator (Research Director)
Period: January 2023 – Ongoing
Funding Amount: KRW 30,000,000 (~USD 30,000)
Funding Agency: Logistics System Institute of Total Soft Bank, Ltd, South Korea.
Place: Busan, South Korea.
2. Development of Real-Time Parking Space Availability Tool for University Campus Using IoT and Machine Learning Techniques
Industry-Academy Cooperation Project of National Project for Excellence in Software
Role: Principal Investigator (PI)
Period: April 2023 – Ongoing
Funding Amount: KRW 5,000,000 (~USD 5,000)
Funding Agency: Ministry of Science and ICT, Government of Korea.
Place: Tongmyong University, Busan-48520, South Korea
3. Development of an Air Quality Prediction Model through Artificial Intelligence Learning Using Results Measured by Fine Dust Measurement Devices
Industry-Academy Cooperation Project of National Project for Excellence in Software
Role: Co-Principal Investigator (Co-PI)
Period: April 2023 – Ongoing
Funding Amount: KRW 5,000,000 (~USD 5,000)
Funding Agency: Ministry of Science and ICT, Government of Korea.
Place: Tongmyong University, Busan-48520, South Korea
COMPLETED:
Uncovering the historic alleys of Neuroscience's growth in South Korea: A timelapse from the 17th century to date
Principal Investigator (PI) and Author: Dr. Indranath Chatterjee
Co-Author: Ms. Videsha Bansal
Period: February 2021 – November 2022
Funding Amount: Euro 1,100 (~ 100,000 INR)
Funding Agency: The Federation of European Neuroscience Societies (FENS), Belgium.
Place: Tongmyong University, South Korea
2. AI-based Time-series Analysis for Korean Stock Index
Principal Investigator (PI): Dr. Indranath Chatterjee
Co-PI: Dr. Migyung Cho
Members: Sun Hu Kang, Seung Yeol Jeon, Min Ho Choe, Jae Won Choi
Period: April 2021 – Novembr 2021
Industry-Academy Cooperation Project of National Project for Excellence in Software
Nature of the Project: Academic R&D project
Funding Amount: USD 20,000 (~ 20,000,000 KRW)
Funding Agency: Ministry of Science and ICT, Government of Korea.
Place: Tongmyong University, Busan-48520, South Korea.
3. Developing Tool for Stock Market Prediction using AI
Principal Investigator (PI): Dr. Indranath Chatterjee
Co-PI: Dr. Migyung Cho
Members: Jeon Gwan, Yong Jin Kim, Min Seok Lee
Period: March 2020 – November 2020
Industry-Academy Cooperation Project of National Project for Excellence in Software
Nature of the Project: Academic R&D project
Funding Amount: USD 20,000 (~ 20,000,000 KRW)
Funding Agency: Ministry of Science and ICT, Government of Korea.
Place: Tongmyong University, Busan-48520, South Korea.
Other PROJECTS:
Understanding the perspective of green-neuromarketing using EEG
PI: Indranath Chatterjee
Member(s): Tamara Hummadi
Goal: Understanding the perspective, sustainability and challenges of green marketing as a part of neuromarketing using EEG technology.
Investigation of chronic pain sensation using fMRI
PI: Indranath Chatterjee
Member(s): Lea Baumgaertner
Goal: Multi-Classification of chronic pain patients by functional magnetic resonance imaging (fMRI) based on deep learning techniques. Pain has been ever since a complex phenomenon in the medical area. Much knowledge about pain is still undiscovered. Therefore machine learning methods may be helpful in pain-related research, by predicting pain types or distinguishing brain areas between pain patients and healthy controls.
Study on Various Neurotransmitters involved in Schizophrenia
PI: Indranath Chatterjee
Member(s): Videsha Bansal
Goal: Study of the role of neurotransmitters in the brain of schizophrenia patients. We also aim to identify the neural pathways associated with the schizophrenic symptoms, thereby targeting to discover the connected brain maps in terms of neurotransmitters' pathways across the brain.
Time-series analysis using Fuzzy logic and machine learning.
PI: Indranath Chatterjee
Member(s): Partha Pratim Deb and Dr. Diptendu Bhattacharya
Goal: Time-series analysis using Fuzzy logic and machine learning algorithms. It is a part of student's PhD project.
Prediction of Brain Performance and Complexity Measures of EEG Signal of Schizophrenia patients.
PI: Indranath Chatterjee
Member(s): Susweta Das
Goal: Prediction of Brain Performance and Complexity Measures of EEG Signal of Schizophrenia patients.
Brain mapping and functional connectivity in Schizophrenia
PI: Indranath Chatterjee
Member(s): M. Ferdousi
Goal: A resting-state fMRI based study on schizophrenia to map the brain in terms of functional connectivity in schizophrenia.
Genetic Study of Schizophrenia: Investigation of inheritance and missing links in genes.
PI: Indranath Chatterjee
Member(s): Namrata Jawanjal
Goal: A key risk factor for schizophrenia is inheritance. Molecular genetic research has created novel discoveries in the last decade, infusing hope about understanding schizophrenia's molecular origins. The difficulty of the object of investigation, however, makes it nearly difficult for non-genetic experts (e.g., many physicians and researchers) to get a clear understanding and knowledge of the genetic results and their limitations. This research aims to encourage such an understanding by presenting a concise summary of some of the main approaches and observations in the biology of schizophrenia, from its historical roots to its present status, and also by discussing the shortcomings and obstacles facing this area of study.
Data Science and Machine learning
PI: Indranath Chatterjee
Member(s): Akansha Gautam; Ajay Kumar
Goal:
Evaluation of Psychological/ Cognitive Flexibility in Adventure Sports.
PI: Indranath Chatterjee
Member(s): Debjani Kar
Goal: To enlighten our understanding regarding the cognitive flexibility in adventure sports persons.