Shikhar Srivastava

Aspiring Software Engineer | Machine Learning Specialist

Lucknow, IN.

About

Highly motivated B.Tech student specializing in Computer Science and Engineering, with a strong foundation in AI/ML and full-stack development. Proven ability to engineer real-time solutions, lead project teams, and deliver impactful results, evidenced by multiple hackathon wins and a design patent. Eager to leverage advanced technical skills and problem-solving capabilities in a challenging software engineering or machine learning role.

Work

National Informatics Centre (NIC)

|

Software Development Intern

Lucknow, Uttar Pradesh, India

→

Summary

Developed a UI/UX-friendly e-filing portal for courts, enhancing digital access and efficiency for advocates.

Highlights

Developed a UI/UX-friendly e-filing portal, enabling advocates to digitally file grievances and track real-time updates.

Streamlined judicial processes by creating an intuitive platform, enhancing user experience and access to legal services.

HCLTech

|

Machine Learning Intern

Lucknow, Uttar Pradesh, India

→

Summary

Designed and implemented a high-performance machine learning pipeline for stock price prediction.

Highlights

Designed and implemented a robust stock-price prediction pipeline utilizing Gradient Boosting Regressor (GBR), AdaBoost, and Random Forest algorithms.

Achieved a high R² score of 0.96 on unseen NSE data, demonstrating strong predictive accuracy and model performance.

Education

VIT Bhopal University

Bhopal, Madhya Pradesh, India
→
B.Tech Computer Science and Engineering Grade: CGPA 8.82/10

Dabble College, Lucknow

Lucknow, Uttar Pradesh, India
→
ISC Class XII PCM Grade: 95%

Lucknow Public Schools, Lucknow

Lucknow, Uttar Pradesh, India
→
ICSE Class X Grade: 93.8%

Awards

Top 8 HackerEarth ML Challenge 2024

HackerEarth

Ranked among the top 2% out of 3,000+ participants by developing MAE-reducing ensemble forecasts, showcasing advanced machine learning expertise.

Design Patent for Glaucoma Screening Device

India Patent Office

Co-inventor of a registered design for an innovative glaucoma screening device (Design No. 435863, India), demonstrating contribution to medical technology innovation.

Publications

Real Time Potato Disease detection using FBEWT and customized VGG

MAI Conf.

Published research detailing a novel FBEWT-VGG hybrid model for real-time potato disease detection, combining signal features with VGG embeddings.

Languages

English

Hindi

Certificates

IBM Certified Machine Learning Professional

IBM

Skills

Programming Languages

Java, Python.

Machine Learning & AI

Time-Series Analysis, Computer Vision, Natural Language Processing (NLP), Transfer Learning, Gradient Boosting Regressor (GBR), AdaBoost, Random Forest, ARIMA, XGBoost, LightGBM, Ensemble Forecasting, Model Validation, AI/ML Model Deployment.

Frameworks & Libraries

PyTorch, TensorFlow, Flask, Streamlit, Pandas, NumPy.

Tools & Platforms

Git, Docker, Jupyter, OpenCV, Firebase, Firestore, Gemini API.

Software Development

UI/UX Design, Web Application Development, Database Management, API Integration, Real-time Systems, Data Analysis, Problem Solving, Project Management.

Projects

Arogyati-Real Time Hospital Resource Management System

→

Summary

Developed an AI-powered real-time hospital resource management system, recognized as a SOLVIT '25 winner, to optimize ICU operations.

Swasthya Sanket

→

Summary

Designed an AI-powered care companion for ASHA workers to assess NCD risks in rural women, achieving AIR 4 in CITLX Metaversity Hackathon.

RoomMitra

→

Summary

Developed a Streamlit web application for roommate matching, recognized as Winner TechTrack Case Battle'25.

Real Time Potato Disease detection using FBEWT and customized VGG

→

Summary

Researched and developed a real-time potato disease detection system, published at MAI Conf., leveraging advanced image processing and deep learning.