Prof. Soumik Kumar Kundu

@iem.edu.in

Assistant Professor, Electronics and Communication Engineering
Institute of Engineering and Management, Kolkata

Prof. Soumik Kumar Kundu


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https://researchid.co/soumikkundu

RESEARCH INTERESTS

Nano-science and Nano-technology
50

Scopus Publications

Scopus Publications

  • First-Principle Investigation of Optical Responses in Pristine and Oxygen- Modified g- C3N4
    Soumik Kumar Kundu, Prativa Saha, Soumyadeep Seth, Samit Karmakar, G. S. Taki
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    A large amount of research has been devoted to determining what materials are suitable as photocatalysts for splitting water by using solar radiation to generate hydrogen and oxygen gas as products. The recent interest in sustainable energy and clean water has led to an increase in research activity relating to photocatalysts, specifically Photocatalytic Water-Splitting Materials. Graphitic carbon nitride (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$g-\mathrm{C}_{3} ~\mathrm{N}_{4}$</tex>), a low-cost and chemically stable photocatalyst, is a leading candidate for use in water-splitting reactions due to its ability to absorb a range of visible wavelengths. Due to limitations associated with not absorbing enough visible light and the quick recombination of the photo generated charge carriers, the photocatalytic performance of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{g}-\mathrm{C}_{3} ~\mathrm{N}_{4}$</tex> is still low. To better understand the electronic behavior of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$g-C_{3} N_{4}$</tex> as impacted by the introduction of oxygen, Density Functional Theory (DFT) will be utilized to study how the properties are affected, and therefore investigate the microscopic effects of oxygen doping of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$g-\mathrm{C}_{3} ~\mathrm{N}_{4}$</tex> throughout the visible light range. The electronic properties of three types of oxygen doping have been determined for both pristine g-C <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{N}_{4}$</tex> and g-C <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{N}_{4}$</tex> with the respective type(s) of oxygen doping: substitutional, interstitial, and add-atom doping configurations. The band structure and density of states for the three different doping types were analyzed, and their electronic properties systematically compared to those of pristine <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{g}-\mathrm{C}_{3} ~\mathrm{N}_{4}$</tex>. The results from these calculations indicate that oxygen doping greatly modifies the electronic structure and energy levels and band gap of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$g-C_{3} N_{4}$</tex>. The lowest electronic band gap value for the three doping types is for the substitutional oxygen doping. The decrease in the Band Gap of substitutional doping can be explained by the strong hybridization that exists between the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O$</tex> 2p and C/N 2p orbitals of the material.
  • High-Accuracy Water Quality Detection Using IoT-Integrated Ensemble Machine Learning
    Ritam Mitra, Tanmay Samanta, Soumik Kumar Kundu, Samit Karmakar, Malay Gangopadhyay
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    Availability of clean and fresh drinking water sources is an increasingly insurmountable challenge with the accelerated urbanization, industrial wastes and pollution of natural sources. Traditional Lab analysis techniques are highly credible yet less cost and time efficient and also not practical in distant and repeated testing. To address these shortcomings, this paper explains and illustrates an effective and compact solution to testing the water quality, which is the integration of the IoT sensors with an ML prediction algorithm. It uses a specially developed probe of pH, turbidity and TDS parameters of data that continually monitors the data on site and wirelessly encrypts the data and subsequently sends it to a cloud server. It operates an ML algorithm that is learned on a big pre-screened database and it either classifies water as drink or undrinkable depending on sensor values. Ten models were tested experimentally under supervision, and it was established that the ensemble techniques, to be more precise the Random Forest Classification algorithm, were highly accurate and recovered 99.95% of the recall rate when it came to detecting unsafe water. The dashboard that can be immediately displayed on any device. Based on the outcome It is possible to observe that the IoT-ML architecture is a low-cost efficient system that can be used to analyze the water quality and, therefore, can be applied in the home environment, agriculture, and rural settings.
  • Autonomous Field-Monitoring Rover for Early Detection of Cattle Health Anomalies Using Yolov8 and Thermal Imaging
    Samriddha Roy, Kankana Karmakar, Subhabrata Banerjee, Soumik Kumar Kundu, Malay Gangopadhyaya
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    Health monitoring in cattle in most cattle rearing systems is done manually by visual inspection, which is inefficient in larger or open-field settings. Accordingly, symptoms of FMD and LSD are often overlooked in their early stages due to this system, contributing to losses and increased cattle risks. The paper describes an autonomous cattle health anomaly sentinel robot developed to monitor cattle in their early stages. The robots are equipped with an RGB camera and an IR thermal imaging sensor. The YOLOv8 model is used to analyze visual symptoms such as skin lesions, posture, and injuries, with thermal imaging used to analyze surface temperature variations indicative of high temperatures (due to sickness or heat stress), as well as estrous cycles. The results showed that it achieved an mAP@0.5 of 0.88 and thermal accuracy of 89% in farm environment.
  • Optimizing Drug Management: Enhancing Pharmacy Analytics and Electronic Health Records with Explainable AI and Graph Neural Networks
    Samit Karmakar, Chandan Kumar Mahato, Sourav Pandey, Sutapa Ray, Soumik Kumar Kundu, Md Moniruzzaman
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    The paper probe an improved upon AI-Driven approach to pharmacy analytics with Electronics Health Records (EHRs) by introducing XGBoost combined with SHAP for explainable medicine recommendation and Graph Neural Networks (GNNs) to predict drug-drugs interactions. The paper presents the growth and evaluation of an AI-powered medicine managements system unification SHAPs-based model interpretability and GNNs-based drug-drug interaction prediction to safeguard patient health. This research look at these models on public data and pretends to use healthcare data, achieving good accuracy, interpretability, and safety. The future work previous efforts by combining interpretability and safety into practical, patient pharmacy management.
  • A Sturdy Hybrid Framework for Differentiating Between Real and Forged Signatures
    Hritankar Sarkar, Souradip Ghosh, Rohan Chatterjee, Ratna Chakrabarty, Samit Karmakar, Soumik Kumar Kundu
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    This paper presents a hybrid signature verification framework that combines K-Means clustering in the HSV color space with ORB-based feature matching. This approach analyzes both the overall ink distribution and local structural details. By merging these methods, the system gains better ability to tell genuine signatures apart from forgeries through a dual-threshold decision mechanism. Experimental results show the framework's effectiveness, making it a practical choice for authentication applications.
  • Dual Layered Hybrid Blockchain Architecture - Securing Electronic Health Records (EHR) Using Blockchain Technology with AI Enabled EHR Data Analysis
    Samit Karmakar, Himanshu Shekhar, Piyush Rai, Souhardya Chowdhury, Srinjoy Bandyopadhyay, Ankana Roy, Soumik Kumar Kundu
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    With rapid advancement in technology and digitisation of data, the end users have started to perform their work more efficiently, minimising their work time. The enhancement of Electronic Health Records (EHR) is one of the examples of this digitisation, enabling less paperwork. But this advancement in EHR has raised challenges over the security and privacy of the user and the medical institution's data. To keep it safe and reliable for the users and the medical institutions, integrating EHR with blockchain technology would be a proposed solution to the problem. The combination of decentralised blockchain properties with cryptographic methods enhances the security. This paper proposes hybrid blockchain-based electronic health records, a hybrid multilayer blockchain architecture using artificial intelligence which provides ease of self-sustained approaches to personal privacy through smart contracts by keeping data control in user hands and AI-based anomaly detection and predictive analytics.
  • Power Prediction and Optimization for FPGA Designs Using Explainable Machine Learning
    Kankana Karmakar, Samriddha Roy, Swastika Sau, Soumik Kumar Kundu, Samit Karmakar, Subhabrata Banerjee, Sutapa Ray Adhikari
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    In the context of the increasing need for energy-efficient and resource-constrained computing systems, power consumption has become a major design constraint for the design of modern FPGA-based architectures. The conventional approach to power estimation for FPGA-based architectures relies on the analysis of the design at the post-synthesis level, which often requires a considerable amount of design iterations. This often results in increased design time and computation. To overcome this limitation of the conventional approach, this work presents a novel AI-based predictive approach for the power estimation of FPGA-based architectures using a set of machine learning regression models. The design parameters used for the proposed approach include a set of synthesis-inspired design parameters such as logic utilization, registers, fanout, clock frequency, and switching activity. The proposed approach uses a set of machine learning regression models such as Linear Regression, Decision Tree Regression, Random Forest Regression, and Gradient Boosting Regression for power estimation. The performance of the proposed approach is evaluated using a set of metrics such as cross-validation, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score, and Root Mean Square Error. From the experimental results, it is observed that Linear Regression has the highest accuracy compared to other models, achieving an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score of 0.992 and RMSE of 0.43 mW, which signifies the strong relationship between the design parameters and power consumption. Ensemble learning models are found to have high accuracy, where Gradient Boosting Regression achieves an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score of 0.985 and RMSE of 0.60 mW, and Random Forest Regression achieves an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score of 0.955 and RMSE of 1.03 mW, and Decision Tree Regression achieves an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{R}^{\mathbf{2}}$</tex> score of 0.913 and RMSE of 1.44 mW. Moreover, feature importance analysis provides useful insights into power-critical design parameters, which can be used for interpretable and AI-driven optimization. The proposed approach allows for accurate power prediction at the early design stage without relying on exhaustive synthesis-based power analysis, which simplifies the design complexity and reduces the development cycle for power-aware intelligent FPGA-based systems.
  • Evaluation and Comparison of Machine Learning Models for Precision Health Monitoring in IoT Systems
    Kankana Karmakar, Ishita Sen, Aditya Deb, Shilpy Suman Bhattacharya, Adreeza Banerjee, Soumik Kumar Kundu, Samit Karmakar
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    Precision health tracking has emerged as a key transformative approach in modern healthcare due to the possibility of continuous and real-time acquisition of physiological parameters by using infrastructures based on IoTs. Large volumes of heterogeneous data, such as heart rate, body temperature, SpO, and physical activity, are generated from IoT-enabled health monitoring systems. These high-dimensional data require robust and efficient ML techniques for an accurate interpretation of noisy data. This paper proposes an IoT-based precision health monitoring framework and conducts a comparative performance evaluation of several ML algorithms to identify the most suitable model for real-time health anomaly detection. The models include the Logistic Regression, Support Vector Machines, Random Forests, and Gradient Boosting. In the experimental evaluation, the Gradient Boosting model, XGBoost, attains the best performance in view of accuracy, robustness to noise, and capability of handling nonlinear and multi-dimensional physiological data. The findings indicate that ensemble learning approaches are very effective when it comes to dependable and scalable precision health monitoring applications.
  • Comparative Evaluation of Classical Perturb and Observe and Incremental Conductance MPPT Algorithms for Photovoltaic Systems
    Supratim Nandi, Sumit Barnwal, Yash Vardhan Choudhary, Tanisha Goswami, Samit Karmakar, Soumik Kumar Kundu, Malay Gangopadhyaya
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    A power conditioning stage that includes a DC-DC converter is necessary, when combining photovoltaic systems with controlled current source loads. The operation of this converter is managed by Maximum Power Point Tracking (MPPT) techniques, in order to effectively harness the maximum energy possible from the solar array, and is sensitive to changes in solar irradiance and temperature. This study conducted a comparative analysis of two popular MPPT algorithms. Perturb and Observe (P&O) and Incremental Conductance (Inc), and brought into the picture factors such as characteristics of the PV modules and behavior of the converter, which were also considered to be of prime importance. The two algorithms were built and run on MATLAB/Simulink in response to fluctuating irradiation to test their accuracy, speed, and steady state efficiency, the results showing that even if P&O and Inc delivered nearly similar results, the latter's ability to accurately predict variations in system behavior made it a more preferred option for practical PV applications, in addition to being a consistent and reliable energy harvester.
  • Analytical Investigation of Field-Dependent Carrier Mobilities in Nanoscale GFETs Employing GO and HGO Channels
    Sagnik Bhattacharyya, Soumyadeep Seth, Samit Karmakar, Malay Gangopadhyay, Prativa Saha, Soumik Kumar Kundu, Ishani Ray Chaudhury, Debjit Biswas
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
    This research presents the comparison of the field-dependent effective mobilities of GFETs using SLG, graphene oxide (GO), and HGO as channels at dimensions in the range of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 0 - 1 8 ~ n m}$</tex>. Since GO and HGO utilize oxidation and hydrogenation processes for bandgap engineering, ambipolarity can be reduced and then overcome in SLG. Analyzing the transfer curve of these GFETs shows extremely high values of extracted field effect mobilities <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\left(10^{3}-10^{5} ~\text{cm}^{2} ~\mathrm{V}^{-1} ~\mathrm{s}^{-1}\right)$</tex> for SLG, low values of insulated regions (less than <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1} \text{cm}^{2} ~\mathrm{V}^{-1} ~\mathrm{s}^{-1}$</tex>) for GO, and relatively moderate values for HGO (order of 10-12 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{c m}^{\mathbf{2}} \mathbf{V}^{\mathbf{- 1}} \mathbf{s}^{\mathbf{- 1}}$</tex>). Output curve measurements using MOSFET parameters also show consistent results for HGO. Additionally, electrostatic control, short-channel effect, and output resistances measured using GFETs having scaled HGO and SLG channels also support HGO as a superior variant over SLG.
  • High-Accuracy Diabetic Retinopathy Detection Using DenseNet-201 Architecture
    Samit Karmakar, Oishi Banerjee, Priyanshu Mazumder, Animesh Dutta, Aman Verma, Soumik Kumar Kundu, Ratna Chakrabarty, Madhusmita Behera
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
  • IoT-Integrated Smart Cold Storage Monitoring System with SaaS-Based Real-Time Analytics for Precision Agriculture
    Soumita Mandal, Ritam Mitra, Soham Sarkar, Tanmay Samanta, Krishna Karmakar, Anuj Dutta, Samit Karmakar, Soumik Kumar Kundu, Arunava Mukhopadhyay
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
  • Voice-Enabled Healthcare Assistance Systems for Elderly And Visually Impaired: A Comparative Analysis
    Riddhiman Rakshit, Nirvik Roy, Priyadarshi Gupta, Rajarshi Dhara, Akash Saha, Ayushi Banerjee, Soumik Kumar Kundu, Samit Karmakar, Rajib Ghosh
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
  • Autonomous Self-Healing IoT Networks: A Distributed MQTT-Based Architecture for Device-Level Fault Detection and Recovery
    Niel Dip Saha, Sreshtha Hira, Akash Patra, Sandipan Maji, Sambaran Sen, Piyush Rai, Samit Karmakar, Soumik Kumar Kundu, Mili Sarkar
    2026 9th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2026, 2026
  • A Brief Review on Photocatalytic Materials for Waste Water Treatment
    Prativa Saha, Soumyadeep Seth, Sonia Saha, Soumik Kumar Kundu, Samit Karmakar
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Optimizing Drug Management: AI-Driven Pharmacy Analytics and Electronic Health Records
    Samit Karmakar, Chandan Kumar Mahato, Sourav Pandey, Sutapa Ray, Soumik Kumar Kundu
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • A Brief Review on AI Based Stock Market Prediction Tools
    Soumya Basu, Anurag Shaw, Rahul Thakur, Soumik Kumar Kundu, Samit Karmakar
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • A Brief Review on Smart Farming Technologies for Precision Agriculture
    Rishav Raj, Arijit Ghosh, Amar Pal, Soumik Kumar Kundu, Samit Karmakar
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Fetal Health Classification Using Machine Learning on Cardiotocography Data
    Samit Karmakar, Sudipta Ray, Shubhayu Basak, Suvrajeet Chatterjee, Soumik Kumar Kundu
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Lithium-Ion Batteries in EVs: Comparative Analysis and BMS Innovations
    Samit Karmakar, Sayan Sengupta, Nirjhar Pal, Yash Vardhan Choudhary, Arpan Jana, Soumik Kumar Kundu
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • FPGA-Based Adaptive Traffic Management System for Optimizing Five-Point Intersection Flow
    Samit Karmakar, Supratim Nandi, Atalanta Pal, Oishi Banerjee, Wrishav Das, Sumit Barnwal, Soumik Kumar Kundu
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Design of a Flexible Metasurface based dual Bandpass Filter in ISM and 5G cellular band for Bio-medical Applications
    Snehanshu Bhattacharjee, Sayak Nandi, Sagnik Chakraborty, Arjab Sengupta, Soumik Kumar Kundu, Arunava Mukhopadhyay, Rintu Kumar Gayen
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Harnessing Machine Learning for Watermarking: A Survey on Robustness and Stealth in Image Protection
    Kunal Routh, Priyanshu Mazumder, Amar Pa, Samit Karmakar, Soumik Kumar Kundu, Sutapa Ray, Pritom Adhikary, Bhaskar Roy
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Development of a Cost-Effective and Portable Digital Storage Oscilloscope Using Raspberry Pi Pico and Mobile App
    Samit Karmakar, Priyanshu Mazumder, Animesh Dutta, Soumyadeep Seth, Prativa Saha, Mili Sarkar, Soumik Kumar Kundu, Sayantan Talukdar, Aparna Biswas
    2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
  • Crystallinity Study of Electrodeposited SnO2 on FTO Substrate
    Uddipan Agasti, Samit Karmakar, Soumik Kumar Kundu, Mili Sarkar, Sayan Chatterjee
    Key Engineering Materials, 2024
  • Crystallinity Study of Cu Thin Film Deposited by Indigenously Developed DC Magnetron Sputtering Setup
    Soumik Kumar Kundu, Samit Karmakar, Gouranga Sundar Taki
    Macromolecular Symposia, 2023
  • Microstructural Characteristics of ECR Plasma Etched and Heat Treated Commercial Copper Foil
    Samit Karmakar, Soumik Kumar Kundu, Sujit Kumar Bandyopadhyay, Gouranga Sundar Taki
    Macromolecular Symposia, 2023
  • Crystallinity and Optical Property Analysis of Magnetron Sputtered Carbon Nitride Thin Films
    Soumik Kumar Kundu, G. S. Taki
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • Performance Analysis of FinFETs with different Fin structures
    Bidyendu Ghoshal, Samit Karmakar, Soumik Kr. Kundu, Mili Sarkar
    Proceedings of IEEE 2023 5th International Conference on Advances in Electronics Computers and Communications Icaecc 2023, 2023
  • In-Situ X-ray Photoelectron Spectroscopy of size-selected Al-Nanoclusters on Si-Substrate
    Uddipan Agasti, Soumik Kumar Kundu, Samit Karmakar, Mili Sarkar, Satyaranjan Bhattacharyya
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • Detection of Blood Glucose Level: A Machine Learning Approach
    Samit Karmakar, Pralay Kumar Ghosh, Debjani Kundu, Sampad Chakraborty, Shantanu Ghosh, Soumik Kumar Kundu
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • Study of Field Distribution and Energy Density in an Indigenous DC Magnetron Sputtering Setup
    Deborshi Banerjee, Soumyadeep Ghosh, Tuhin Manna, Soumik Kumar Kundu, Samit Karmakar, G. S. Taki
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • A Study on Device Properties of High Electron Mobility Transistors
    Prasanga Taki, Pratham Padala, Ritam Panja, Samit Karmakar, Soumik Kumar Kundu, Mili Sarkar, G S Taki
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • Advancements in Schottky Diode Technology: A Comprehensive Review
    Soumik Kumar Kundu, Shreyan Sarkar, Arnab Mondal, Anushka Bandyopadhyay, Soumily Ray, Nayan Kamal, Animesh Ghosh, Samit Karmakar
    2023 7th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2023, 2023
  • Application of Reinforcement Learning for Control of Autonomous Vehicles
    Indranil Basu, Samit Karmakar, Soumik Kumar Kundu, Avishek Saha, G. S. Taki
    2022 International Conference on Interdisciplinary Research in Technology and Management Irtm 2022 Proceedings, 2022
  • Studies on Copper Nanometric-Film Deposited by an In-House Developed DC Magnetron Sputtering System
    Soumik Kumar Kundu, Samit Karmakar, Sujit Kumar Bandyopadhyay, Satyaranjan Bhattacharyya, Gouranga Sundar Taki
    Materials Science Forum, 2022
  • Microstructural Analysis of Copper Foil Etched and Annealed in ECR Plasma Reactor
    Samit Karmakar, Soumik Kumar Kundu, Aditya Mukherjee, Sujit Kumar Bandyopadhyay, Satyaranjan Bhattacharyya, Gouranga Sundar Taki
    Materials Science Forum, 2022
  • Bandgap Study of Defect Induced Graphene Structures
    Samit Karmakar, Soumik Kumar Kundu, G. S. Taki
    2021 5th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2021, 2021
  • Elemental Composition Analysis of DC Magnetron Sputter Deposited Various Cu Thin Films
    Soumik Kumar Kundu, Samit Karmakar, G. S. Taki
    2021 5th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2021, 2021
  • Analysis of Dislocation Density and Pair Distribution Function for Annealed and ECR Plasma Etched Copper Foils
    Samit Karmakar, Soumik Kumar Kundu, Mili Sarkar, G. S. Taki
    2021 5th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2021, 2021
  • Study of Magnetic Field Distribution in an Indigenous DC Magnetron Sputtering Setup
    Soumik Kumar Kundu, Samit Karmakar, Mili Sarkar, G. S. Taki
    2021 5th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2021, 2021
  • Electronic effects on optical properties of graphitic Carbon Nitride towards its superiority
    Soumik Kumar Kundu, Samit Karmakar, Sujit Kumar Bandyopadhyay, Malay Gangopadhyaya, G. S. Taki
    2020 4th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2020, 2020
  • Importance of transition metal modified graphene-based non-enzymatic blood glucose sensors
    Samit Karmakar, Soumik Kumar Kundu, Sujit Kumar Bandyopadhyay, Malay Gangopadhyay, G. S. Taki
    2020 4th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2020, 2020
  • Comparative Study of Sextupole and Quadrupole Magnetic Field in an ECR-PE Sputtering System
    Shankha Mukherjee, Shubham Majee, Suman Kundu, Soumik Kumar Kundu, Samit Karmakar, G.S. Taki
    2019 3rd International Conference on Electronics Materials Engineering and Nano Technology Iementech 2019, 2019
  • Microwave Heating Study of Dielectric Material Placed at the Injection Port of an E-Plane Bend
    Samit Karmakar, Soumik Kumar Kundu, Aditya Mukherjee, Arpan Dutta, Soumyadeep Bose, Saptarshi Mukherjee, G. S. Taki
    2019 3rd International Conference on Electronics Materials Engineering and Nano Technology Iementech 2019, 2019
  • Progress in submicron device technology
    Soumik Kumar Kundu, Samit Karmakar, G. S. Taki, Aishwarya Roy, Chayanika Dhar Choudhuri, Megha Basu, Ankan Basak, Rishav Upadhyay, Abhinav Raj, Satyaki Mandal
    2017 8th Industrial Automation and Electromechanical Engineering Conference Iemecon 2017, 2017
  • Conceptual design of a double antenna fed ECR plasma enhanced nano-film deposition system
    Samit Karmakar, Shamik Mukherjee, Soumik Kumar Kundu, Deepantee Jha, G.S. Taki
    2017 1st International Conference on Electronics Materials Engineering and Nano Technology Iementech 2017, 2017
  • Design study of a portable permanent magnet ECR plasma source for thin film deposition
    Soumik Kumar Kundu, Samit Karmakar, Shamik Mukherjee, Shubham Majee, Suman Kundu, G. S. Taki
    2017 1st International Conference on Electronics Materials Engineering and Nano Technology Iementech 2017, 2017
  • Determination of window thickness for efficient microwave injection into ECR plasma
    Tuhin Kumar Das, Indrani Mukherjee, Vivek Prateek, Soumik Kumar Kundu, Samit Karmakar, G. S. Taki, Sayak Dutta Gupta
    7th IEEE Annual Information Technology Electronics and Mobile Communication Conference IEEE Iemcon 2016, 2016
  • A study on high-κ gate stack for MOS-FET
    Soumik Kumar Kundu, Samit Karmakar, Md. Samim Reza, Arindam Dutta, G.S. Taki
    2015 International Conference and Workshop on Computing and Communication Iemcon 2015, 2015