Gajendra Nagar
AI Research EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Research Engineer with less than a year in Industrial Engineering with expertise in Data Science,
My Ph.D. research at IIT Delhi focuses on applying data science and optimization techniques to public transport systems. I have worked on diesel bus scheduling by eliminating overlapping trips, driver scheduling to reduce overtime costs, and electric bus planning with efficient charging strategies. Using real-world operational data and analytical models, my work improves fleet utilization and charging efficiency. The developed solutions support cost reduction, service reliability, and sustainable mobility. This work provides data-driven solutions that help transit agencies improve both operational effectiveness and financial efficiency.
Indian Institute of Technology Delhi
Doctor of Philosophy · Industrial Engineering and Operation Research
August 1, 2020 – June 30, 2026
Govt. Sec. School, Chandresal
10th
N/A – May 31, 2013
MNIT Jaipur
B. Tech · Mechanical Engineering
N/A – June 30, 2020
Sagar Bal Sr. Sec. School
12th
N/A – May 31, 2015
INDIAN RAILWAY
Apply predictive maintenance using sensors in service of wagons
May 1, 2019 – June 1, 2019
Vadodara, Gujarat, India
GAN-Augmented Deep Learning Framework for Electric Bus Route Prioritization (Self Project)
July 1, 2025 – December 1, 2025
This study proposes a fully data-driven framework where route electrification priorities are learned using backpropagation-based deep neural networks, with data scarcity addressed through generative adversarial networks (July-Dec 2025).
Optimization of Electric Bus Operations: Scheduling, Charging, and Infrastructure Planning (BMTC-IITD)
July 1, 2022 – January 1, 2024
Proposed integrated planning models for electric bus scheduling and charging infrastructure that minimize total initial investment and improve operational efficiency (July 2022-Jan 2024).
Bus Optimization Toolkit (BMTC-IIT Delhi)
June 1, 2021 – July 1, 2022
Built reusable Python-based optimization modules supporting scheduling, routing, and resource allocation (June 2021- July 2022).
Predictive Analysis for Retail Demand (Voylla Fashion)
January 1, 2020 – April 1, 2020
Demand Estimation Using Machine Learning Models (ANN): A Case of Jewelry Industry (VOYLLA FASHION PVT.LTD. (Jan-April 2020).
Reducing Fleet Replacement Requirements through Energy- Aware Electric Bus Deployment in Urban Transit Systems
Journal of Public Transport (Under review)
January 1, 2026 – Present
Efficient and Sustainable Electric Bus Operations through Joint Scheduling, Charging Infrastructure Utilization and Driver Planning
Working paper
January 1, 2026 – Present
Optimization of charging infrastructure and battery size for efficient electrification of diesel bus Network
5th Indian International Conference on Industrial Engineering and Operations Management
November 1, 2025 – Present
Optimization of Bus Schedule: An Integrated Approach to Mitigate the Bus Overlapping
Institute for Operations Research and the Management Sciences (INFORMS 2025) International Meeting
July 1, 2025 – Present
Designing a decision support system for optimal allocation of drivers and reducing the overtime costs for bus transportation system
Transportation Research Interdisciplinary Perspectives (Under review)
January 1, 2025 – Present
Design and Implementation of a Network- Aware Automated Bus Scheduling System for Optimizing Operational Efficiency and Financial Performance
Case Studies on Transport Policy
January 1, 2025 – Present
Design and Implementation of an Integrated Optimization Framework for Electric Bus Scheduling and Charging Infrastructure in Urban Transport Systems
Journal of Transport Policy (Under Review)
January 1, 2025 – Present
An Integrated Approach to Electric Bus Timetabling and Scheduling for Sustainable Urban Mobility
33rd European Conference on Operational Research (EURO 2024)
June 1, 2024 – Present
IIT Delhi Grant: Received International Research Travel Grant from IIT Delhi for presenting a research paper in EURO 2024 conference
IIT Delhi
January 1, 2024 – Present
Bus Crew Schedule Optimization in Bus Transit Network: Impact on Overtime Cost of Drivers
56th Operational Research Society of India (ORSI 2023) Conference
December 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic background and extensive research in optimization and AI for public transport systems indicate a strong alignment with roles requiring deep technical expertise and a research-oriented mindset. Their involvement in multiple academic projects and publications suggests a collaborative approach to problem-solving. The diversity of projects, from academic to professional and personal, shows initiative and a broad interest in applying AI/ML. However, without psychometric test results, a comprehensive assessment of cultural fit regarding teamwork, stress handling, and work attitude is not possible.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their academic research and project work. Their focus on optimization and data-driven solutions aligns well with operational efficiency. The numerous publications suggest strong communication of complex technical concepts, which is crucial for a research role. However, direct experience in a corporate R&D setting is limited, and the psychometric and English test scores are not available, making a full assessment of soft skills and operational fit challenging.