About me

Kundan Kumar is an accomplished Data Scientist specializing in AI-Driven Financial Data Analytics, with expertise in Artificial Intelligence and Machine Learning across various domains. He possesses extensive experience in time series data analysis and medical image analysis. Currently, he is dedicated to crafting automated trading systems using advanced machine learning algorithms at Data-Core Systems (India) Pvt. Ltd. Previously, he spent five years as an Associate Professor in academia.

Passionate about simplifying intricate data, especially in finance and healthcare, to yield impactful results, Kundan brings a unique combination of academic rigor and practical industry acumen to the forefront of cutting-edge data science applications.

Always eager to expand his knowledge base, Kundan seeks challenging roles that prioritize innovation, emphasizing machine learning, time-series data analysis, and statistical data mining. He is enthusiastic about contributing his expertise to a dynamic team, driving data-driven decision-making and optimizing strategies to propel the company's success.

What i'm doing

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    AI-ML

    I use AI-ML algorithms to solve different problems in time series and medical image analysis domain.

  • Web development icon

    Time Series Analysis

    I do Time-series prediction, Algorithmic trading, Vibration signal analysis, Structural health monitoring.

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    Statistical Data Mining

    I use it for Portfolio Management, Market Analysis and Forecasting, Algorithmic Trading and Risk Management.

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    Medical Image Analysis

    State-of-the-art algorithm to segment and classify medical image such as Oral Squamous Cell Carcinoma and Retinal Fundus Images.

Certifications

  • Certifications

    Time Series (March 2024)

    Issued by: Kaggle Learn View Certificate

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    Introduction to Large Language Models

    Issued by: Google Cloud Skills Boost (03-2024) View Certificate

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    Learning SQL Programming

    Issued by: Linkedin (03-2024) View Certificate

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    Introduction to Generative AI

    Issued by: Google Cloud Skills Boost (12-2023) View Certificate

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    International Workshop on Deep Learning

    Issued by: BITS Pilani, India (08-2020)

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    Machine Learning and Computer Vision: Applications, Research Challenges

    Issued by: NIT Silchar, India (08-2020)

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    Intelligent Computing in Data Science

    Issued by: Aditya Institute of Technology and Management (Autonomous), Tekkali, Andhra Pradesh, India (06-2020)

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    Deep Learning for Visual Computing - Winter School

    Issued by: IIT Khargarpur (12-2017)

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    Institute Silver Medal for holding First Position in M.Tech.

    Issued by: NIT Rourkela (01-2012)

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    Organizing Committee Member

    IEEE Conference conducted at IIT Kharagpur

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Daniel lewis

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Resume

Education

  1. Doctor of Philosophy (Ph.D.)

    2011 — 2017

    E&ECE Department, IIT Kharagpur, India

    Thesis Title: “Statistical Damage Diagnosis Approach for Vibration-based Structural Health Monitoring” | Supervisor: Prof. P. K. Biswas

    CGPA: 8.27/10

  2. Master of Technology (M.Tech.)

    2009 — 2011

    Electrical Engg. Department, NIT Rourkela, India

    Thesis Title: “Ear Identification using Feature Descriptor and Shadowed Set based Segmentation” | Supervisor: Prof. D. Patra

    CGPA: 9.50/10 (Silver Medalist)

  3. Bachelor of Technology (B.Tech.)

    2005 — 2009

    BPUT, Rourkela, Odisha

    Electronics and Telecommunication Engg.

    CGPA: 8.48/10

Experience

  1. Senior Data Scientist

    Apr 2022-- Present

    AILabs Finance Inc., DCG Data-Core Systems (India) Private Limited, Kolkata

    • Utilized advanced machine learning methodologies, particularly Deep Reinforcement Learning (DRL), to develop automated trading systems and strategies.
    • Developed a risk-managed portfolio strategy aimed at achieving specific volatility targets, leveraging predictive models built using Machine Learning algorithms.
    • Engineered a Dynamic Stock Screener employing technical and fundamental data, integrating GUI using Tkinter for user-friendly interaction, facilitating efficient identification of emerging opportunities in the stock market.
    • Employed Explanatory Data Analysis (EDA) techniques to simplify complex financial data, generating actionable insights for informed decision-making.
    • Managing a real cash portfolio on US exchanges, executing trades automatically through broker APIs such as Interactive Brokers (IBKR) and TradeStation, utilizing Python for seamless integration and execution.

    Key Technologies/Skills: Portfolio management, Trading Strategy, EDA, Time series analysis, Machine Learning, Deep Reinforcement Learning, Pytorch, Python, Scikit-learn, MS Excel, Tkinter.

  2. Associate Professor

    Oct 2021 — Apr 2022

    Center for the Internet of Things, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar

    Associate Professor

    Jan 2018 — Oct 2021

    ECE Dept., ITER, Siksha 'O' Anusandhan (Deemed to be University),Bhubaneswar

    • Designed and delivered advanced courses including Pattern Classification, Digital Image Processing, and Foundation of Machine Learning.
    • Served as the course coordinator for Pattern Classification and Numerical Methods, overseeing all aspects of course organization, including collaborative learning environment, preparing course materials, assessments, and student support.
    • Orchestrated a hands-on workshop introducing Python programming language to students and research scholars, fostering practical skills essential for modern research and industry.
    • Actively engaged in research endeavors, resulting in the publication of 16 influential research papers across various international journals and conferences.
    • Demonstrated proficiency in Time Series analysis, Machine Learning techniques, and Medical Image Classification and Segmentation, utilizing advanced frameworks such as ResNet, CNN, UNet, and employing tools like including Pytorch, Keras, Tensorflow, Python, Scikit-learn, R, Numpy, Pandas, Matplotlib, MATLAB, NI Multisim, Draw.io.

    Key Technologies/Skills: Pattern Classification, Time Series Analysis, Machine Learning, Computer Vision and Image Processing, Keras, Tensorflow, Pytorch, Python, Scikit-learn, R, Numpy, Pandas, Matplotlib, MATLAB, NI Multisim, Draw.io

  3. Assistant Professor

    Mar 2017 — Jan 2018

    ECE Dept., ITER, Siksha 'O' Anusandhan (Deemed to be University),Bhubaneswar

    • Delivered courses on foundational topics including Digital Signal Processing and Digital Image Processing, fostering a comprehensive understanding among students.
    • Conducted practical sessions utilizing MATLAB, Python, NI Multisim, and GNU Octave, providing hands-on experience to students in signal processing and image analysis.

    Key Technologies/Skills: MATLAB, Python, NI Multisim, GNU Octave

Software Skills

  1. Libraries and tools

    • Pandas
      95%
      Matplotlib
      95%
      Scipy
      95%
      Scikit-Learn
      95%
      Git and Github
      60%
      Backtrader
      80%
    • Pytorch
      80%
      Tensorflow
      70%
      Keras
      70%
      FinRL
      95%
      Tableau
      60%
      Power BI
      60%

  2. Language

    • Python
      90%
      R
      75%
      MATLAB
      80%
    • C++
      50%
      Pine Script
      75%

  3. Packages

    • Excel
      80%
      Word
      90%
    • PowerPoint
      80%
      LaTex
      80%

Technical Skills

  1. Machine Learning

    Convolutional Neural Networks (CNN),

    Recurrent Neural Networks (RNN),

    Deep Reinforcement Learning (DRL),

    Classical approaches for Prediction and Classification.

  2. Finance

    Portfolio Optimization

    Equity and Derivatives

    Technical indicators

    Option Pricing

PhD Thesis

Title: Statistical Damage Diagnosis Approach for Vibration-based Structural Health Monitoring
Supervisor: Prof. P. K. Biswas, IIT Kharagpur
Description: This thesis explored the idea where vibration signals are used for structural health monitoring (SHM) of civil structures such as buildings, bridges, etc. using time series analysis. It explores different features sensitive to the level of damage, and outlier detection approaches based on One-class SVM and optimum residual subspace (ORS) model. The proposed methods detect the severity of damage and location under varying operational and environmental conditions.

Master Thesis

Title: Ear Identification using Feature Descriptor and Shadowed Set based Segmentation
Supervisor: Prof. Dipti Patra, NIT Rourkela
Description: This thesis work is related to develop a novel algorithm for human ear identification. SIFT features are extracted from the segmented ear lobes and conchas, which are invariant to Image scaling, rotation, illumination, and some affine change in object. It enables the correct match for a keypoint to be selected from a large database of other keypoints for identification.

Journals

  1. Classifying histopathological images of oral squamous cell carcinoma using deep transfer learning

    2023

    Panigrahi, Santisudha, Bhabani Sankar Nanda, Ruchi Bhuyan, Kundan Kumar, Susmita Ghosh, and Tripti Swarnkar. "Classifying histopathological images of oral squamous cell carcinoma using deep transfer learning." Heliyon 9, no. 3 (2023). https://doi.org/10.1016/j.heliyon.2023.e13444

  2. Multistage classification of oral histopathological images using improved residual network

    2022

    Panigrahi, Santisudha, Ruchi Bhuyan, Kundan Kumar, Janmenjoy Nayak, and Tripti Swarnkar. "Multistage classification of oral histopathological images using improved residual network." Math Biosci Eng 19, no. 2 (2022): 1909-25. https://doi.org/10.3934/mbe.2022090

  3. Optimal residual subspace model for structural damage diagnosis: an approach independent of operational and environmental variations

    2022

    Kumar, Kundan, and Sumanshu Agarwal. "Optimal residual subspace model for structural damage diagnosis: an approach independent of operational and environmental variations." International Journal of Structural Engineering 12, no. 1 (2022): 44-61. https://doi.org/10.1504/IJSTRUCTE.2022.119285

  4. Antimony chalcogenide-based thin film solar cells: Device engineering routes to boost the performance

    2021

    Agarwal, Sumanshu, Vikas Nandal, Harekrishna Yadav, and Kundan Kumar. "Antimony chalcogenide-based thin film solar cells: Device engineering routes to boost the performance." Journal of Applied Physics 129, no. 20 (2021). https://doi.org/10.1063/5.0047429

  5. Time series-based SHM using PCA with application to ASCE benchmark structure

    2020

    Kumar, Kundan, Prabir Kumar Biswas, and Nirjhar Dhang. "Time series-based SHM using PCA with application to ASCE benchmark structure." Journal of Civil Structural Health Monitoring 10 (2020): 899-911. DOI - https://doi.org/10.1007/s13349-020-00423-2

  6. Damage Diagnosis of Steel Truss Bridges under Varying Environmental And Loading Conditions

    2019

    Kumar, Kundan, Prabir Kumar Biswas, and Nirjhar Dhang. "Damage diagnosis of steel truss bridges under varying environmental and loading conditions." Int J Acoust Vibr 24, no. 1 (2019): 56-67. DOI: https://doi.org/10.20855/ijav.2019.24.11255

  7. Statistical Damage Detection Approach in SHM Based on Error Prediction Model

    2019

    Kumar, Kundan, Prabir Kumar Biswas, and Nirjhar Dhang. "Statistical damage detection approach in SHM based on error prediction model." Int J Struct Civ Eng Res 5, no. 5 (2016): 300-307. DOI: https://doi.org/10.18178/IJSCER.5.4.300-307

  8. Fast leukocyte image segmentation using shadowed sets

    2012

    Mohapatra, Subrajeet, Dipti Patra, and Kundan Kumar. "Fast leukocyte image segmentation using shadowed sets." International journal of computational biology and drug design 5, no. 1 (2012): 49-65. DOI: https://doi.org/10.1504/IJCBDD.2012.045951

  9. Unsupervised leukocyte image segmentation using rough fuzzy clustering

    2012

    Mohapatra, Subrajeet, Dipti Patra, and Kundan Kumar. "Unsupervised leukocyte image segmentation using rough fuzzy clustering." International Scholarly Research Notices 2012 (2012). https://doi.org/10.5402/2012/923946

Conferences

  1. Application of Top-hat Transformation for Enhanced Blood Vessel Extraction

    2021

    Das, Tithi Parna, Sheetal Praharaj, Sarita Swain, Sumanshu Agarwal, and Kundan Kumar. "Application of Top-hat Transformation for Enhanced Blood Vessel Extraction." arXiv preprint arXiv:2203.10005 (2022). https://doi.org/10.48550/arXiv.2203.10005

  2. Parametric Scaling of Preprocessing assisted U-net Architecture for Improvised Retinal Vessel Segmentation

    2021

    Kumar, Kundan, and Sumanshu Agarwal. "Parametric Scaling of Preprocessing assisted U-net Architecture for Improvised Retinal Vessel Segmentation." arXiv preprint arXiv:2203.10014 (2022). https://doi.org/10.48550/arXiv.2203.10014

  3. Development of conceptual framework for reinforcement learning based optimal control

    2021

    Gupta, Smriti, Sabita Pal, Kundan Kumar, and Kuntal Ghosh. "Development of conceptual framework for reinforcement learning based optimal control." In Innovation in Electrical Power Engineering, Communication, and Computing Technology: Proceedings of Second IEPCCT 2021, pp. 339-348. Singapore: Springer Singapore, 2021. https://doi.org/10.1007/978-981-16-7076-3_29

  4. Process design to self-extract text from images for similarity check

    2021

    Sharmeen, Adiba, Nidhi Agarwal, Arpit Suman, Sumanshu Agarwal, and Kundan Kumar. "Process Design to Self-extract Text from Images for Similarity Check." In Advances in Intelligent Computing and Communication: Proceedings of ICAC 2021, pp. 109-117. Singapore: Springer Nature Singapore, 2022. https://doi.org/10.1007/978-981-19-0825-5_11

  5. Performance Evaluation of Perovskite Solar Cells at Elevated Temperatures

    2021

    Agarwal, Sumanshu, Archana Kumari Munda, Vedika Pandey, and Kundan Kumar. "Performance Evaluation of Perovskite Solar Cells at Elevated Temperatures." In Proceedings of International Conference on Communication, Circuits, and Systems: IC3S 2020, pp. 127-133. Springer Singapore, 2021. https://doi.org/10.1007/978-981-33-4866-0_16

  6. Automated retinal vessel segmentation based on morphological preprocessing and 2D-Gabor wavelets

    2020

    Kumar, Kundan, Debashisa Samal, and Suraj. "Automated retinal vessel segmentation based on morphological preprocessing and 2D-Gabor wavelets." In Advanced Computing and Intelligent Engineering: Proceedings of ICACIE 2018, Volume 1, pp. 411-423. Springer Singapore, 2020. DOI https://doi.org/10.1007/978-981-15-1081-6_35

  7. A Comprehensive Study of MeanShift and CamShift Algorithms for Real-Time Face Tracking

    2019

    Gupta, Smriti, Kundan Kumar, Sabita Pal, and Kuntal Ghosh. "A Comprehensive Study of MeanShift and CamShift Algorithms for Real-Time Face Tracking." In Intelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 1, pp. 801-811. Springer Singapore, 2021. DOI https://doi.org/10.1007/978-981-15-5971-6_86

  8. Blood Vessel Detection using Modified Multiscale MF-FDOG Filters for Diabetic Retinopathy

    2019

    Mallick, Debojyoti, Kundan Kumar, and Sumanshu Agarwal. "Blood vessel detection using modified multiscale MF-FDOG filters for diabetic retinopathy." In 2019 International Conference on Applied Machine Learning (ICAML), pp. 82-86. IEEE, 2019. DOI: https://doi.org/10.1109/ICAML48257.2019.00024

  9. Statistical Damage Detection Approach in SHM Based on Error Prediction Model

    2016

    Kumar, Kundan, Prabir Kumar Biswas, and Nirjhar Dhang. "Statistical damage detection approach in SHM based on error prediction model." Int J Struct Civ Eng Res 5, no. 5 (2016): 300-307. DOI: https://doi.org/10.18178/IJSCER.5.4.300-307

  10. Structural Health Monitoring of Web Girder Bridge using Vibration Signal Analysis

    2016

    Kumar, Kundan and Prabir Kumar Biswas. "Structural Health Monitoring of Web Girder Bridge using Vibration Signal Analysis", International Conference on VLSI and Signal Processing. (2014)

  11. Blood microscopic image segmentation using rough sets

    2011

    Subrajeet Mohapatra; Dipti Patra; Kundan Kumar. (2011). "Blood microscopic image segmentation using rough sets." International Conference on Image Information Processing. pp. 1-6. IEEE, DOI: https://doi.org/10.1109/ICIIP.2011.6108977

  12. Combining GLCM Features and Markov Random Field Model for Colour Textured Image Segmentation

    2011

    J. Mridula; Kundan Kumar; Dipti Patra. (2011). "Combining GLCM Features and Markov Random Field Model for Colour Textured Image Segmentation."International Conference on Devices and Communications (ICDeCom)". pp. 1-5. IEEE, DOI: https://doi.org/10.1109/ICDECOM.2011.5738494

Contents

Teaching is an art to deliver the complex thing in the simplest way in the classroom. I have taught undergraduate and postgraduate courses. You can find a selection of my teaching materials including all of the labs. ## Undergraduate Courses - Pattern Classification (EET3053)) - [Syllabus](/files/pdf/teaching/PC-Syllabus.pdf) - [Materials](/pattern-classification.md) - Foundation of Machine Learning using R (CSE4032) - [Syllabus](/files/pdf/teaching/FML-Syllabus.pdf) - [Materials](/Foundation_of_ML.md) - Numerical Methods (MTH4002) - [Syllabus](/files/pdf/teaching/NM-Syllabus.pdf) - [Materials](/numerical-methods.md) - Digital Filter Design (EET3134) - [Syllabus](/files/pdf/teaching/DFD-Syllabus.pdf) - [Materials](/digital-filter-design.md) - Analog Filter Design (EET3132)) - [Syllabus](/files/pdf/teaching/AFD-Syllabus.pdf) - [Materials](/analog-filter-design.md) ## Postgraduate Courses - Digital Image Processing (Spring 2017) - [Syllabus](/files/pdf/teaching/DIPSyllabus.pdf) - [Materials](/digital-image-processing.md)

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