Mohammed Tousif Zaman

Happy to share my latest research work titled Resilient electric bus system design considering charger failure. This was the first problem I tackled in my PhD, along with my senior Pranav Gairola and supervisor Nezamuddin N. Here, we formulated a two-stage stochastic mixed-integer program and solved it using Ancestral Benders’ decomposition, given the presence of integer variables in the second stage. The primary contribution of this work is the modeling of charger failures as decision-dependent uncertainty (making it a function of charger utilization time). Link to the article: https://rdcu.be/e4I03 Hope that this work provides insight regarding the design of reliable electric transit systems.

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We are happy to inform that SRM MTS STUDENT CHAPTER AND DEPT. OF EEE is organizing a workshop on Industrial Robotics and RoboDK Simulation which will provide a comprehensive introduction to the fundamentals of industrial robots, covering types, applications, robot anatomy, kinematics, and industry safety standards. Participants explore various robot configurations—Cartesian, SCARA, Articulated, Delta, and Collaborative—and gain practical experience visualizing degrees of freedom and coordinate systems using RoboDK’s 3D simulation environment.  The program advances to hands-on training in RoboDK software, including robot path programming, CAD model integration, and offline program generation for major industrial robot brands. Additionally, Python scripting is incorporated for enhanced robot control and simulation, enabling tasks such as pick-and-place operations and basic sensor integration, effectively bridging theoretical concepts with industrial automation applications. Register early to avoid last time rush and limited seats only due to intense physical training in the workshop.

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🚀 Pleased to share my recent blog on: Vehicle-to-Grid (V2G) Optimization Using Machine Learning: Driving the Future of Smart Energy As electric vehicles (EVs) become an integral part of the clean energy ecosystem, Vehicle-to-Grid (V2G) technology is emerging as a breakthrough innovation. By enabling EVs not only to consume power but also to feed stored energy back into the grid, V2G can transform energy management, grid reliability, and sustainability. In this blog, I discuss how Machine Learning (ML) is unlocking new possibilities in V2G by: ⚡ Predicting energy demand and renewable generation ⚡ Optimizing charging and discharging schedules ⚡ Enhancing grid stability and efficiency Together, V2G and ML represent a powerful step toward smart, flexible, and carbon-free energy systems. 🌍🔋 👉 Read the full blog here: https://lnkd.in/gJFGGanv #VehicleToGrid #MachineLearning #EV #SmartGrid #ArtificialIntelligence #Sustainability #CleanEnergy #RenewableEnergy #ElectricVehicles #FutureOfEnergy #sruniversity #sru SR University CS&AI -SRU

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𝐒𝐞𝐯𝐞𝐫𝐚𝐥 𝐏𝐡𝐃/𝐌𝐚𝐬𝐭𝐞𝐫’𝐬 𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐬, 𝐂𝐀𝐍𝐀𝐃𝐀 deep reinforcement learning (explainability, world models) foundation models (computational pathology, medical imaging) large-language models (fairness, mathematical reasoning) generalization and shortcut learning (RL or DL)

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🚀 Diving Deep into R&D! Just three days into my journey as an Embedded System Engineer in the R&D Department at Karban Envirotech, and the experience has already been transformative. 🧪 R&D—Research and Development—is not just a department; it's a mindset. A continuous cycle of 🔍 analyze → 📚 research → 🧠 learn → 🛠️ implement → 👀 observe → ⚙️ optimize. You're constantly thrown into unfamiliar territory, learning things you might never have imagined using—and yet, they make all the difference. It's not just about knowing things—it's about figuring out what you don’t know, and pushing boundaries to build something meaningful. 💼 From day one, I was fortunate to contribute to an ongoing product development effort. In just a few days, I’ve learned things I might’ve overlooked for months before—especially how small ignored details can have a huge impact when it comes to optimization. 💡 One key factor: R&D demands precision, curiosity, and trust. You're often exposed to confidential information, and the responsibility to handle it ethically and securely is as important as the technical work itself. Maintaining this trust is a top priority. 🔐 🙏 Grateful to the team for trusting me early on and giving me the space to explore, fail, learn, and improve. 💭 One realization that truly hit me: During engineering, almost everyone wonders "What’s the use of this subject? We’re never going to use it." Well… that’s absolutely wrong. 🚫 📖 What you study or learn never goes to waste. Even just having a basic understanding that a concept exists can become a game-changer when architecting systems. And when it’s time to go deep—you’re ready. ✅ 🧠 A personal moment that truly blew me away: There was a subject called ISS (Information Security System) which I always thought was useless—“It’s cyber security stuff, I’m not going into that line.” But recently, while designing the firmware and application layer, security became a major concern. And guess what I had to implement? 🔐 ➡️ A Key Exchange Algorithm 🔐 ➡️ A Universal AES Encryption System for secure data communication. 😲 That moment was shocking. The subject I once found most irrelevant turned out to be the most crucial. It made me realize: even a basic understanding can guide important architectural decisions. 📚 This applies across the board—Operating Systems (RTOS), Networking, Security, and more. You don’t need to master everything from the start. But knowing they exist? That’s what builds your problem-solving mindset. 🧩 📈 Looking forward to sharing more as I grow in this exciting journey! 🙌 #EmbeddedSystems #ResearchAndDevelopment #LearningByDoing #TrustAndResponsibility #IoT #FirmwareDevelopment #RND #Grateful

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🚀 Thrilled to share that our latest research has been published in the European Journal of Operational Research! Paper Title: Robot-Aided Electric Vehicle Routing Problem with Lockers and Prime Customer Prioritization 🔍 What is it about? This study introduces a novel last-mile delivery model that integrates: ✅ Electric Vehicles (EVs) ✅ Sidewalk Autonomous Delivery Robots (SADRs) ✅ Parcel Lockers ✅ Priority service for high-value (Prime) customers We formulated the Robot-Aided Electric Vehicle Routing Problem with Lockers and Prime Customer Prioritization (REVRP-LPCP) as a mixed-integer linear programming model. We developed a tailored metaheuristic (LNS-SA) to solve large-scale instances effectively. 💡 Key Contributions: - Proposes an innovative multi-modal delivery strategy combining EVs, robots, and lockers. - Introduces customer prioritization (e.g., Prime customers) into the routing and assignment decisions. - Demonstrates significant efficiency improvements over EV-only systems (up to ~53% reduction in routing costs). - Outperforms exact solvers in large-scale scenarios and discovers 44 new best-known solutions. - Provides extensive sensitivity analysis offering practical guidance for logistics planners. 🌱 Practical Implications: This approach helps logistics providers: - Reduce operational costs. - Offer flexible delivery options (home delivery or self-pickup) to improve customer satisfaction. - Prioritize high-value customers while ensuring sustainability and service reliability. 🔗 Download the paper free here:  https://lnkd.in/dARrezMC 🙏 A big thanks to professors Fereshteh Mafakheri, Chun Wang, and Roberto Baldacci for their guidance and tremendous effort on this project! https://lnkd.in/djT5YdVS #LastMileDelivery #ElectricVehicles #Robots #OperationalResearch #Sustainability #LogisticsInnovation

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