Jobs
Job openings for various research, technical, and administrative positions are announced periodically on the IIT Bombay Development and Relations Foundation (IITB DRF) website and/or the center’s website and LinkedIn page.
February 11, 2026
Current Openings: Project Research Associate/Scientist (Multiple Roles)
Fellowships Available for New Students
Several fellowships available for PhD and MTechs in 2026-27. Please see below for details.
FedEx ALFA Center-supported PhD Fellowship Projects for the July 2026–27 Academic Session
| Federated Prognostics of Mobility Batteries for Enhanced EV Fleet Management (Prof. Vibhor Pandhare, Mechanical Engineering) |
| This research addresses the critical need for accurate battery health forecasting in the rapidly expanding EV fleet market, where privacy concerns and data silos currently hinder the development of robust prognostic models. While centralized data-driven approaches are the current standard, they suffer from significant communication overhead and struggle to generalize across diverse driving environments and battery chemistries without compromising proprietary operator data. To overcome these barriers, this project will aim to propose Federated Learning mechanisms that enable collaborative model training across distributed fleets without the exchange of raw sensor data. The study will specifically investigate how personalized aggregation using hybrid data-driven + physics-informed approaches can manage fleet heterogeneity, whether asynchronous architectures can mitigate connectivity issues in mobile environments, and the extent to which federated transfer learning can resolve “cold-start” challenges for new vehicles. By decentralizing the learning process, this work will aim to enhance the Remaining Useful Life (RUL) predictions of mobility batteries, ultimately optimizing fleet maintenance schedules and total cost of ownership. For more detail on admission process, click here |
| Trusted Electronic Bills of Lading (e‑BL) for India’s Multimodal Logistics Networks (Prof. Archak Mittal, Civil Engineering) |
| Bills of lading remain heavily paper-based in India, creating delays, manual errors, fraud risks, and poor visibility across ports, inland terminals, and road legs of multimodal freight. Recent legal and policy moves towards recognizing electronic trade documents and electronic bills of lading (e‑BL) now create an opportunity to design India-specific digital infrastructure that is interoperable, secure, and scalable for logistics stakeholders. This project aims to develop and pilot a standards-based e‑BL framework tailored to Indian exporters, freight forwarders, carriers, banks, and customs, with emphasis on interoperability with global MLETR-aligned platforms and emerging standards such as ISO 5909. The research will: (i) map current document and data flows for selected export–import corridors, (ii) specify a canonical data model and APIs for e‑BL exchange across trucking, rail, and maritime actors, and (iii) prototype a reference implementation with strong identity, consent, and audit trails leveraging existing trade and logistics systems. Using real shipment pilots, the study will quantify impacts on cycle time, exception rates, financing timelines, and compliance, and identify regulatory and operational enablers for nationwide scale-up, directly supporting more efficient, transparent, and resilient logistics in India. For more detail on admission process, click here |
| Human brain behind the delivery network: Neural Responses to Feedback and Decision Conflict in Logistics Systems (Prof. Rashmi Gupta, Humanities & Social Sciences) |
| With the increasing optimization of logistics systems through algorithms and automation – role of human decision-makers remains critical in managing uncertainty, resolving conflicts, and responding to operational feedback in real time. However, the current logistics research widely assumes cognitively stable decision-makers and overlooks how workers’ emotional and mental health states may shape operational performance. This project aims for an investigation on the neural mechanisms modulated by depressive symptom-severity highlighting underlying emotional feedback processing and cognitive control during logistics decision making. Using electroencephalography(EEG), the study will examine brain responses while participants engage in simulated last-mile delivery and routing tasks involving time pressure, conflicting priorities, and operational feedback such as delivery delays or negative customer-outcomes. Validated clinical scales would be deployed to assess individual differences in depressive symptoms and they will be linked to neural markers of emotional and cognitive processing including feedback-related negativity, error-related negativity, frontal midline theta, and the late positive potential. By integrating affective neuroscience with logistics decision-making, the project aims to uncover how emotional vulnerability influences responses to operational stress, negative feedback. The findings could guide design of human-centered logistics systems, decision-support tools, training-protocols, and workplace interventions that account for cognitive emotional variability in high-pressure logistics environments. For more detail on admission process, click here |
| Environmental Implications of Transportation and Logistics (Prof. Omkar D. Palsule, SJMSoM) |
| Logistics service providers, such as FedEx, DTDC, and Amazon, operate large transportation and logistics networks, moving millions of packages daily by air, ground, and sea. This extensive scale of operations generates significant environmental impacts that require strategic attention and systemic operational intervention. We aim to analyze how logistics service providers’ transportation modes, logistics network design, and operational practices collectively shape environmental outcomes, ultimately informing evidence-based strategies for sustainable logistics transformation in the express delivery industry. We aim to develop operational and strategic frameworks at the interface of logistics and the environment. For more detail on admission process, click here |
| Assessment of national-level freight road corridors (Prof. Gopal R. Patil, Civil Engineering) |
| India is a huge country with a big network of National Highways, Expressways, and State Highways. The road sections on these roads vary significantly with reference, number of lanes, quality of pavement, traffic condition, and geometry. For a transporter, typically, there are alternative routes and modes available. Realistic assessment of these alternatives is of great importance to make an optimal choice. However, it is not possible for an individual transport company to analyze the entire road network. We plan to use field data and road toll data to assess different road sections. It is proposed to develop an index to indicate the efficiency of a given road section. This will be very beneficial to logistics and transport companies to make optimal decisions related to routes and modes of transport. For more detail on admission process, click here |
FedEx ALFA Center-supported MTech Fellowship Research Projects for the July 2026–27 Academic Session
| Hybrid drone–Ground vehicle Logistics for Warehouse and Last-Mile Operations (Prof. Jayendran Venkateswaran, IEOR) |
| Hybrid drone–ground vehicle logistics systems for two complementary operational contexts: intra-warehouse logistics and last-mile delivery scenarios. The objective is to understand how aerial and ground robots can coordinate to improve efficiency, flexibility, and responsiveness in modern logistics systems. Inside a warehouse, The research will develop a small experimental platform where drones and ground robots coordinate tasks such as item retrieval, shelf scanning, and delivery to packing stations. In last-mile setting, the system will model a hybrid delivery approach in which a ground vehicle acts as a mobile depot while drones perform short-range deliveries to nearby destinations. The research will experimentally evaluate delivery strategies. |
| Two Legged Walking Robot for Last Mile Delivery (Prof. Vivek Sangwan, Mechanical Engineering) |
| Last mile delivery in logistics is hard to automate. Flying and Walking robots are a potential solution depending on scenarios. The focus of this project is (1) to explore novel control algorithms for two legged walking, and also (2) to develop a lab scale 2-D (planar) hardware prototype of a two legged walking robot as a test bed for research (walking on a treadmill for continuous experiments). |
| Planning and Operational Toolkit for Transition to E-mobility Resources (POTTER) (Prof. Avijit Maji, Civil Engineering) |
| Recent policy and regulatory interventions initiated by the Government of India to promote Electric Vehicle (EV) are expected to play a key role in carbon emission reduction. However, the freight industry involved in last-mile delivery needs to assess available charging stations, variability in electricity demand and pricing, and the economic viability of adopting renewable energy for EV adoption. At present, there is no single decision-making tool that understands the requirements of delivery-vehicle fleet owners and assists them in making scientifically driven, informed decisions for all these factors. The Indian freight industry can be the major driving force behind the sustainability goal – SDG 11. The primary objective of the project is to develop a dashboard that helps determine the optimal investment for the charging system, identify the minimum-cost charging schedule without impacting consignment delivery assignments, and maximize revenue through charging-station renting and solar power adoption. The developed tool will be applicable for both the micro level (delivery-vehicle fleet owner) and the macro level (Smart Cities). |
| AI-Enabled Digital Twin for Intelligent Infrastructure Logistics Systems (Prof. Saurabh Jain, IEOR) |
| Large-scale infrastructure logistics systems such as ports, multimodal freight terminals, and oil and gas transportation networks are becoming increasingly complex due to rising trade volumes, demand variability, infrastructure constraints, and evolving regulatory requirements. These systems operate as tightly coupled physical networks where flow dynamics, capacity limits, storage constraints, and operational workflows interact in non-trivial ways. Despite their importance, decision-making in such environments often remains fragmented and reactive, with limited integration of physics-based modeling and data-driven analytics. This research aims to develop an integrated digital twin framework that combines first-principles, physics-based modeling of infrastructure behavior with advanced simulation and AI-driven analytics. The objective is to create a robust decision-support environment capable of representing material flows, congestion propagation, asset utilization, and network-level interactions under uncertainty. The framework will enable scenario analysis for demand surges, infrastructure expansion, maintenance planning, and disruption response. By bridging physical system modeling with intelligent analytics, the proposed research seeks to improve operational efficiency, throughput, and resilience across critical logistics infrastructure systems. The outcomes are expected to contribute to scalable methodologies for modernizing large-scale trade and energy transport networks. |
| Development and Validation of Contactless Internet of Things based Frameworks for Fatigue Detection and Tracking in Warehouse Environments (Prof. Ambarish Kunwar, BSBE) |
| There are currently 22M+ warehouse workers in India with minimal OHS protocols. They often work in 40°C+ temperatures, 10-12 hour shifts with roughly 26,800+ incidents/year. Many for the wearables fail due to heat discomfort, surveillance anxiety, signal degradation from sweat. Self-reporting is unreliable for continuous monitoring. Driver-centric fatigue models are not transferable to physically dynamic warehouse workflows. The Contactless sensing technologies have matured individually (CV, LiDAR, mmWave, thermal). However, no existing study fuses these modalities for industrial worker fatigue. This project is focused on addressing key questions such as whether multi-modal fusion (gait + vitals + thermal) significantly outperform individual modalities for fatigue detection? What is the correlation between the contactless Fatigue Risk Score and gold-standard assessments (PVT, KSS) in an warehouse? Can a privacy-preserving edge-first architecture achieve real-time processing while complying with India’s DPDP Act 2023? The aim of this project is to design and develop a contactless IoT sensor node integrating edge-AI cameras, LiDAR, 60 GHz mmWave radar, and thermal imaging with synchronized edge processing for fatigue marker detection at 1-5 metres. Engineer a fusion model with multi-head attention that aggregates gait, cardiopulmonary, and thermal features into a real-time Fatigue Risk Score (0-100), benchmarked against single-modality baselines. Validate the framework in an operational Indian warehouse (30-50 workers, 5+ shifts) against PVT and KSS gold standards, with a formal DPDP Act 2023 privacy audit. |
Current Students of IIT Bombay
Current PhD and MTech students of IIT Bombay can apply for FedEx Fellowships available through the center. Please see the details of PhD and MTech fellowships.
Faculty
Interested faculty from within IIT Bombay and other institutes can contact the Center-in-Charge for possible avenues of participating in the center activities.