About Me

Hello! 👋 I am Samarjeet Das: a researcher with a PhD in Signal Processing and Machine Learning from IIT Guwahati. I am deeply intrigued by signals and passionate about leveraging machine learning and deep learning models to predict and classify future trends and patterns.

+ From April 2024 - Now: I am an AI/ML Research Engineer at the Tata Consultancy Services (TCS), Bengaluru (India).

Research Interests: - Application of Machine Learning and Deep Learning Models, - Time-frequency Analysis of Non-stationary Signals, - Laser Weld Quality Monitoring, - Design and Development of Embedded Systems

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Previous Affiliations

+ From June 2023 - March 2024: I was a Research Assistant at the Technology Innovation Hub, in the Indian Institute of Technology, Guwahati (India).
+ From July 2017 - October 2023: I pursued a Ph.D. degree (Signal Processing and Machine Learning), from the Indian Institute of Technology, Guwahati (India). My Ph.D. thesis was titled "Automated Diagnosis of Heart Valve Diseases From Phonocardiogram Signals Using Deep Learning". I had my research denizen at the wonderful Electro Medical Speech Technology (EMST) Lab, with the guidance of Prof. Samarendra Dandapat.
+ From July 2015 - May 2017: I received a M.Tech degree (Mechatronics), from the Indian Institute of Engineering Science and Technology, Shibpur (India). My M.Tech thesis was titled "Studies on Development of an Underwater Acoustic Pinger System for Source Localization". I had my research habitat at the robotics and automation group, CSIR-CMERI, Durgapur, with the guidance of Dr. Siva Ram Krishina Vadali, Principal Scientist.
+ From August 2011 - May 2015: I was a Lecturer (Department of ECE) at Einstein Academy of Technology and Management, Bhubaneswar.
+ From August 2007 - May 2011: I received a B.Tech degree (Applied Electronics and Instrumentation), from the BPUT, Odisha, India.

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A bit more information

GitHub-ID: oksamar.
Google Scholar: Click here.
Email-id: samarjeet025@gmail.com, samar176102005@iitg.ac.in

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Courses Taken

Linear Algebra, Pattern Recognition and Machine Learning, Biomedical Signal Processing, Digital Signal Processing and Architecture, Probability and Random Process, Mechatronics, Robotics, Embedded system, Micro-electromechanical Systems. The above courses are the few I took during my M.Tech and Ph.D coursework.

Skills summary

Coding: Python, Matlab, SQL, C++; Documentation: Latex, Microsoft Word. Machine Learning: Theory and implementation of regression and classification models; Platforms: Linux, Windows; Soft-skills: Critical thinking, Technical writing, Public speaking, Event management.

Research

• Biomedical signal processing especially analysis of cardiovascular signals such as heart sound using phonocardiogram (PCG), electrocardiogram (ECG) signal and seismocardiogram (SCG) signal. Time-frequency analysis of non-stationary signals, Design and development of electronic circuits, Machine learning and deep learning applications

Peer-reviewed Published Findings
(for updated list see Google Scholar)

List of Journals

• • S. Das and S. Dandapat, “Heart Murmur Severity Stages Classification Using Multikernel Residual CNN,” IEEE Sensors Journal, 2024.
• • S. Das, D. Joytishi, and S. Dandapat, “Automated Detection of Heart Valve Diseases Using Stationary Wavelet Transform and Attention Based Hierarchical LSTM Network,” IEEE Transactions on Instrumentation and Measurement, 2023.
• • S. Das, D. Joytishi, and S. Dandapat, “Heart Valve Diseases Detection Based on Feature-fusion and Hierarchical LSTM Network,” IEEE Transactions on Instrumentation and Measurement, 2022.
• • S. Das and S. Dandapat, “Multicomponent Oscillatory Model based Heart Sound Classification,” Journal of acoustic society of India (JASI), 2020.

List of Conferences

• • MJ Singh, S. Das, LN Sharma, and S. Dandapat, “Stationary Wavelet Transform Based Detection of Aortic Stenosis Using Seismocardiogram Signal,” 2023 National Conference on Communications (NCC), Guwahati, India, 2023.
• • S. Das and S. Dandapat, “Automated Detection of Heart Murmurs From the PCG Signal Using Stationary Wavelet Transform,” INDICON, Kerala, India, 2022.
• • S. Das and S. Dandapat, “Multiscale Kernel Residual Convolutional Neural Network to Detect Heart Valve Diseases,” INDICON, Kerala, India, 2022.
• • S Kumari, D Jyotishi, S. Das, and S. Dandapat, “Analyzing The Effect of Segmentation on PCG Based Biometric System,” INDICON, Kerala, India, 2022.
• • S. Das and S. Dandapat, “Synthesis and Classification of Heart Sounds Using Multi-component Oscillatory Model,” 2020 National Conference on Communications (NCC), Kharagpur, India, 2020.
• • S. Das, and SRK. Vadali, “Design Development and Experimental Validation of an Underwater Acoustic Pinger System,” INDICON, Roorkee, India, 2017.

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Projects and Workshops

• • Automated Detection and Classification of Heart Valve Diseases Using Phonocardiogram Signals
  Mentor: Prof. S. Dandapat, EEE Department, IIT Guwahati.
  The Project was my PhD Thesis Work. The project aims to develop a robust framework consists of extracting novel features followed by machine learning models to detect different heart valve abnormalities. (2017 - Present)
• • Studies on Development of an Underwater Acoustic Pinger System for Source Localization
  Mentor: Dr. SRK Vadali, Principal Scientist, CSIR-CMERI, Durgapur.
  The Project was my MTech Thesis Work. The objective of the project was to design and develop an underwater communication system for source detection and localization. (2015 - 2017)
• • Development of a GSM Based Home Automation and Security System
  Mentor: Dr. Satyasen panda, Krupajal Engineering College, Bhubanseswar.
  This was my BTech Project. The objective of the project was to design a cost-effective solution that remotely controls home appliances and enables home security against intruders. (2010 - 2011)
• • Attended workshop on “Tutorial Series on Deep Learning using Tensorflow (TSDLT),” organized by IEEE Branch, IIT Guwahati, Oct. 2018.
• • Student Member, Organizing Committee, Workshop on "AI in Healthcare Engineering", NECBH, IIT Guwahati, March 28-30, 2019.
• • Attended workshop on "Summer School on Automatic Speech Recognition" jointly organized by department of EEE and CLST, IIT Guwahati, June 2-7, 2019.

Academic Achievements

• • PhD scholorship holder of MHRD fellowship, Govt. of India, 2017 - 2022.
• • MTech scholorship holder of MHRD fellowship, Govt. of India, 2015 - 2017.
• • Graduate student member of IEEE community, 2022 - Present.
• • Member, IEEE Instrumentation and Measurement Society, 2022 - Present.
• • Member, IEEE Young Professionals, 2022 - Present.
• • Reviewer of Elsevier and Springer Journals, 2020 - Present.
• • Event Manager (Organizing technical events, workshops and talks), RSF-EEE, IIT Guwahati, 2018 - 2019.

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