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Hi, I'm Subhankar Mandal

Data Scientist & Machine Learning Engineer

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M.Tech AI/ML candidate at LPU with 87.2% grade, specializing in weather forecasting, computer vision, and time-series analysis. Proven track record in deploying end-to-end ML solutions with 95%+ accuracy. Passionate researcher and hackathon winner focused on real-world AI applications.

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Subhankar Mandal

About Me

Getting to know the person behind the code

Professional Background

Currently pursuing Master of Technology in Machine Learning & Artificial Intelligence at Lovely Professional University (87.2% grade). Completed BTech in CSE with Data Analytics specialization from Neotia University with 84% grade.

Passionate about applying deep learning to real-world problems, particularly in weather forecasting and computer vision. Driven by the potential of AI to solve complex environmental and business challenges.

Areas of Expertise

Deep Learning
Computer Vision
Time-Series Forecasting
Model Deployment

Education

M.Tech - ML & AI

Lovely Professional University

2024 – 2026 | 87.2%
Advanced ML Deep Learning Computer Vision

B.Tech - CSE (Data Analytics)

The Neotia University

2019 – 2023 | 84%
Data Structures Statistics ML Foundations

Skills Overview

Technical Skills

Technologies and tools I work with

Programming Languages

Python 95% 4 years
8 projects | Advanced
SQL 85% 3 years
5 projects | Intermediate
C 75% 2 years
3 projects | Intermediate

ML/AI Frameworks

TensorFlow 90% 2 years
4 projects | Advanced
Scikit-Learn 95% 3 years
6 projects | Expert
OpenCV 80% 1 year
2 projects | Intermediate
Pandas 95% 3 years
8 projects | Expert

Development Tools

Jupyter Notebook 95% 3 years
8 projects | Expert
Streamlit 90% 2 years
3 projects | Advanced
Power BI 80% 1 year
2 projects | Intermediate

Featured Projects

A showcase of my machine learning and data science work

Completed

Face Authentication Attendance System

Real-time AI-based face recognition system with anti-spoofing detection for fully automated attendance tracking

Python OpenCV Deep Learning FaceNet
Recognition Accuracy 99%
Anti-Spoofing 97%
Case Study
Deployed

Text to Image Generation

Streamlit-based generative AI application that converts natural language text prompts into high-quality images using diffusion models

Python Streamlit Diffusion Models Generative AI
Generation Time <5s
Resolution 512×512
Case Study
Completed

LLM-Based Agentic AI HR Automation System

Agentic AI workflow using FLAN-T5 for intelligent resume screening, JD generation, and end-to-end HR task automation

Python FLAN-T5 Agentic AI LangChain
Screening Time Saved 70%
HR Tasks Automated 3+
Case Study

Professional Experience

My journey in data science and machine learning

Data Science Intern

Skill Academy by TestBook Apr 2023 - May 2023
  • Integrated and cleaned multi-source datasets with advanced preprocessing techniques
  • Identified Gradient Boosting as top performer with 92% R² score through comprehensive model comparison
  • Deployed Streamlit model improving planning efficiency by ~20% with automated forecasting capabilities
Python Streamlit Machine Learning Gradient Boosting
20% Efficiency Gain 92% R² Score

Data Science Intern

Corizo Feb 2023 - Mar 2023
  • Processed road images using OpenCV with advanced computer vision techniques
  • Achieved 87% accuracy in lane detection for ADAS systems under diverse conditions
  • Applied Canny edge detection and Hough Transform for robust detection algorithms
Python OpenCV Computer Vision Image Processing
87% Accuracy ADAS Systems

Certificates & Achievements

Continuous learning and professional development

Advanced Learning Algorithms

Coursera - Stanford University

Apr 2024
Grade: 98.5% 40 hours

Supervised Machine Learning

Coursera - Stanford University

Apr 2024
Grade: 96.8% 35 hours

Data Science with Python Career Program

TestBook

Jul 2023
Grade: 92% 120 hours

Data Science Industrial Training

Corizo

Mar 2023
Industry Exposure 60 hours

Python Programming

Coursera - University of Michigan

May 2021
Grade: 94% 25 hours

Achievements & Recognition

Celebrating milestones and accomplishments

3rd Place in ML Build-A-Thon Hackathon

Lovely Professional University

November 2024

Participants: 200+
Duration: 48 hours
Prize Money: ₹10,000

Developed an innovative real-time fraud detection system using machine learning algorithms with real-time processing capabilities, demonstrating excellent problem-solving skills and technical implementation.

Python TensorFlow Streamlit

Research & Publications

Contributing to the advancement of AI and machine learning

Research Interests

Weather Forecasting & NWP Bias Correction
Disease Vector Identification using Deep Learning
Computer Vision & Autonomous Systems
Time-Series Analysis & LSTM Networks
Large Language Models & Agentic AI
Bias Correction in ML / Deep Learning Models

IEEE Publications

Bias Correction in NWP Temperature Forecasts using LSTM-Based Deep Learning Models

S. Mandal, et al. — 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO), IEEE, Noida NCR, India.

Published — IEEE Sep 18–19, 2025

DOI: 10.1109/ICRITO66076.2025.11241393

AI and ML Approaches for Automated Mosquito Species Identification: A Review

S. Mandal, P. Singh — 5th International Conference on Innovative Practices in Technology and Management (ICIPTM), Noida NCR, India.

Accepted — IEEE Xplore (In-Press) Feb 19–20, 2026

Automated Identification of Zika Virus Mosquito Vectors Using Ensemble Deep Learning

S. Mandal, P. Singh — 5th International Conference on Innovative Practices in Technology and Management (ICIPTM), Noida NCR, India.

Accepted — IEEE Xplore (In-Press) Feb 19–20, 2026

Blog & Articles

Sharing knowledge and insights from my journey

Mar 2025 Deep Learning 8 min read

Understanding LSTM Networks for Weather Forecasting

A comprehensive guide to implementing LSTM networks for time-series weather prediction with practical examples and code implementation.

LSTM Weather Forecasting Time Series Deep Learning
Read Article
Feb 2025 Computer Vision 6 min read

Computer Vision in Autonomous Vehicles

Exploring lane detection algorithms and their applications in ADAS systems with OpenCV implementation and performance optimization.

Computer Vision Autonomous Vehicles OpenCV ADAS
Read Article
Jan 2025 Machine Learning 10 min read

Bias Correction Techniques in Machine Learning Models

Deep dive into systematic bias correction methods for improving model accuracy and reliability in production environments.

Bias Correction Model Optimization Machine Learning Production ML
Read Article

Testimonials & Recommendations

What colleagues and mentors say about my work

"Subhankar demonstrates exceptional analytical skills and innovative thinking in his research work. His approach to weather forecasting using LSTM networks is both methodical and creative."

Dr. Rajesh Kumar

Research Supervisor, Lovely Professional University

"During his internship, Subhankar showed remarkable problem-solving abilities and quickly mastered complex ML algorithms. His Streamlit deployment improved our planning efficiency significantly."

Priya Sharma

Senior Data Scientist, TestBook

"Subhankar's work on computer vision and lane detection was outstanding. He achieved excellent results in a short time and demonstrated strong technical implementation skills."

Amit Patel

ML Engineer, Corizo

Downloadable Resources

Access my professional documents and project materials

Professional Resume (PDF)

Comprehensive resume highlighting technical skills and project experience

2.4 MB 1,247 downloads
Download PDF

Project Portfolio Summary

Detailed overview of all major projects with technical specifications

5.1 MB 892 downloads

Research Papers Collection

Academic publications and research contributions

12.7 MB 445 downloads

Certificate Compilation

All professional certifications and achievements

8.3 MB 723 downloads

Get In Touch

Let's discuss opportunities and collaborations

Contact Information

subhankarmandal242@gmail.com
www.linkedin.com/in/06neel
https://github.com/06Neel
Kolkata, West Bengal, India
IST (UTC+5:30)

Response Time

Within 24 hours

Preferred: Email and LinkedIn

Collaboration Opportunities

Research Collaboration
Industry Projects
Consultancy

Send a Message