- Technology Strategy & Vision: Lead the technological roadmap, driving innovation in UAV design, AI, and autonomous systems to position the company as an industry leader.- Product Development Oversight: Oversee the end-to-end development lifecycle, ensuring efficient R&D, prototyping, and production of cutting-edge drone technology.- Team Leadership & Mentorship: Build and mentor a high-performance engineering and technology team, fostering a collaborative culture focused on excellence… Show more - Technology Strategy & Vision: Lead the technological roadmap, driving innovation in UAV design, AI, and autonomous systems to position the company as an industry leader.- Product Development Oversight: Oversee the end-to-end development lifecycle, ensuring efficient R&D, prototyping, and production of cutting-edge drone technology.- Team Leadership & Mentorship: Build and mentor a high-performance engineering and technology team, fostering a collaborative culture focused on excellence and continuous improvement.- Stakeholder Collaboration: Partner with executive leadership, clients, and industry stakeholders to align technology initiatives with business goals, regulatory standards, and market demands.- Technical Expertise: Stay abreast of emerging technologies in UAVs, robotics, and AI, translating them into scalable solutions that drive competitive advantage. Show less

- Structural Integrity Modeling: Develop and validate computational models to assess structural integrity, load-bearing, and impact resilience for UAVs.- Data-Driven Failure Prediction: Use data analytics and machine learning to predict potential failure modes, ensuring safe, reliable drone operations under diverse conditions.- Materials and Stress Analysis: Conduct material behavior studies under operational stresses to improve durability and performance.- Cross-functional… Show more - Structural Integrity Modeling: Develop and validate computational models to assess structural integrity, load-bearing, and impact resilience for UAVs.- Data-Driven Failure Prediction: Use data analytics and machine learning to predict potential failure modes, ensuring safe, reliable drone operations under diverse conditions.- Materials and Stress Analysis: Conduct material behavior studies under operational stresses to improve durability and performance.- Cross-functional Engineering Collaboration: Work closely with design and aerodynamics teams to integrate structural analysis insights into UAV development.- Technical Proficiency: Skilled in FEA, Python/MATLAB, materials science, and UAV-specific load and stress testing for robust and optimized designs. Show less

- Additive Manufacturing Process Design: Focused on powder-bed fusion process optimization using pyrometer sensors in the AconityMINI metal 3D printer at SUTD’s DManD Lab.- Sensor Data Collection & Analysis: Gathered and analyzed emissivity and temperature data to understand impacts of parameters like power, speed, and layer thickness on maraging steel.- Feature Engineering for Predictive Modeling: Derived statistical time-series features from sensor data to train ML models predicting… Show more - Additive Manufacturing Process Design: Focused on powder-bed fusion process optimization using pyrometer sensors in the AconityMINI metal 3D printer at SUTD’s DManD Lab.- Sensor Data Collection & Analysis: Gathered and analyzed emissivity and temperature data to understand impacts of parameters like power, speed, and layer thickness on maraging steel.- Feature Engineering for Predictive Modeling: Derived statistical time-series features from sensor data to train ML models predicting mechanical properties, including density, porosity, and stress.- Quality Assurance Challenges: Addressed issues of defect control in AM processes such as delamination, porosity, and layer-wise propagation failures.- Predictive Maintenance with Digital Twins: Utilized Digital Twins to simulate AM processes and predict issues, enabling early detection and quality assurance.- Data-Driven Defect Detection: Developed ML-based anomaly detection systems to monitor AM processes and ensure reliability and repeatability.- Industry Day Event: Engaged in IDDAM Workflow Industry Day to exchange insights on process chain optimization and first-time-right manufacturing.- Collaboration with IHPC: Supported IHPC's simulation efforts for virtual testing and process optimization, incorporating manufacturing process simulations.- Publication Contributions: Authored research on density prediction and defect detection using supervised ML techniques with pyrometer sensor data. "International Conference of Additive Manufacturing for a Better Word - 2022"- Research Tools: Skilled in Python, Machine Learning, Point Cloud Library, Image Processing, Signal Processing, Anomaly Detection, and Density Measurement. Show less

- Course Facilitation: Assisted students in mastering statistical, numerical, and computational techniques for solving real-world engineering problems.- Differential Equations: Guided learners through ODE/PDE solving, covering initial/boundary value problems and error analysis.- Root Finding & Optimization: Taught essential root-finding, numerical differentiation, integration, and Monte Carlo approaches.- ANOVA & Statistical Analysis: Enabled students to model complex systems and… Show more - Course Facilitation: Assisted students in mastering statistical, numerical, and computational techniques for solving real-world engineering problems.- Differential Equations: Guided learners through ODE/PDE solving, covering initial/boundary value problems and error analysis.- Root Finding & Optimization: Taught essential root-finding, numerical differentiation, integration, and Monte Carlo approaches.- ANOVA & Statistical Analysis: Enabled students to model complex systems and understand error propagation within designs.- Programming Proficiency: Mentored students in applying Python, Matlab, and Excel to engineer robust solutions.- Project Guidance: Led 1D and 2D application projects, like a Peltier-based vaccine cooling system using Arduino for real-world design experience.- Documentation: Emphasized reporting skills for technical clarity in explaining models, methodologies, and outcomes.- Hands-On Hardware Training: Instructed students in practical implementation with microcontrollers (Arduino) and electronic components.- Outcomes Assessment: Provided actionable feedback on student projects, reinforcing data-driven analysis in engineering design.- Domain Versatility: Prepared students to apply these methods across industries such as automation, aerospace, and healthcare. Show less

• Describe, plan, and program algorithms to analyze practical problems in physics, engineering, and related fields.• Use statistical models to optimize a complicated engineering design, and to interpret design interactions in complex engineering systems.• Analyze, evaluate, and apply numerical methods to find roots of an equation, integrate equations, solve sets of ordinary differential equations and partial differential equations (both explicit and implicit)• Use numerical and… Show more • Describe, plan, and program algorithms to analyze practical problems in physics, engineering, and related fields.• Use statistical models to optimize a complicated engineering design, and to interpret design interactions in complex engineering systems.• Analyze, evaluate, and apply numerical methods to find roots of an equation, integrate equations, solve sets of ordinary differential equations and partial differential equations (both explicit and implicit)• Use numerical and analytical methods to design, analyze, and evaluate complex engineering systems. Show less

"One who is mild rather than forceful has greater capacity for outreach" - I look forward to engaging Graduate Students through advancing outreach partnerships and opportunities by strengthening their coordination with a multitude of diverse education and outreach initiatives.

Machine Learning Assisted Process Inspection and Adaptive Quality Control for Metal Additive Manufacturing- Aspects of Machine Learning in Additive Manufacturing and the techniques involved to detect process defection.- Machine Learning tools utilized to detect anomaly during the in-process monitoring for quality control can potentially improve the reliability and repeatability of the printed parts- Additive Manufacturing processes suffer from various defects such as cracks… Show more Machine Learning Assisted Process Inspection and Adaptive Quality Control for Metal Additive Manufacturing- Aspects of Machine Learning in Additive Manufacturing and the techniques involved to detect process defection.- Machine Learning tools utilized to detect anomaly during the in-process monitoring for quality control can potentially improve the reliability and repeatability of the printed parts- Additive Manufacturing processes suffer from various defects such as cracks, delamination, distortion, rough surface, lack of fusion, porosity, etc Show less

- Data analysis of overall vendor orders data and liaising with SAP team to visualize using TABLEAU dashboard and automate the process using Machine Learning in UiPath- Guide the team in technical related activities, such as preparation, setup, testing, and continuous improvement, and maintain Key Performance Improvement.

- To study the effect of different soil type on heat transfer and thermal efficiency inside the Earth-Pipe-Air Heat Exchanger (EPAHE) system- Designing of pipe-domain and soil-domain has been modeled using SOLIDWORKS cad software.- Defining inlet boundary condition as air, material like PVC for the pipe-domain and soil types like dry soil and clay for soil-domain used for the flow transfer analysis at different velocities and different side-wall temperatures.- Fine mesh domain has… Show more - To study the effect of different soil type on heat transfer and thermal efficiency inside the Earth-Pipe-Air Heat Exchanger (EPAHE) system- Designing of pipe-domain and soil-domain has been modeled using SOLIDWORKS cad software.- Defining inlet boundary condition as air, material like PVC for the pipe-domain and soil types like dry soil and clay for soil-domain used for the flow transfer analysis at different velocities and different side-wall temperatures.- Fine mesh domain has been done for predicting the heat transfer interaction between air and soil and the overall flow simulation has been carried out using k-ε turbulence model with energy equation (to solve heat transfer problem) in ANSYS-FLUENT FEA software. Show less

UAV Collison severity evaluation with aircraft engine @ Air Traffic Management Research Institute (ATMRI)- FE Analysis of bird and drone ingestion with aircraft engine fan blade and stress analysis at different rpm and environmental conditions.- CFD simulation of airflow over a engine fan blade with nacelle and wake formation behind the engine.

Master Research Thesis on "Modal Analysis, Development and Modal Testing of a Nanosatellite Structure"• Fine-tuning design and assembly process of structural parts using SOLID WORKS CAD tool to verify the tolerance while stacking the subsystems. • Modal analysis to obtain 6 modal frequencies, sine vibration (5-100Hz), and random response spectrum (0-2000 Hz) analyses were performed to investigate the structural integrity of proposed design using ABAQUS/Standard FEA tool. • The… Show more Master Research Thesis on "Modal Analysis, Development and Modal Testing of a Nanosatellite Structure"• Fine-tuning design and assembly process of structural parts using SOLID WORKS CAD tool to verify the tolerance while stacking the subsystems. • Modal analysis to obtain 6 modal frequencies, sine vibration (5-100Hz), and random response spectrum (0-2000 Hz) analyses were performed to investigate the structural integrity of proposed design using ABAQUS/Standard FEA tool. • The modal analysis results obtained with less than 0.1mm deformation and confirmed that the 3D printed and Aluminum materials selected for structure.• Modal testing conducted for the verification and validation of CubeSat structure with dummy subsystems using Vibration shaker and carried out outgassing test for 3D printed material and examined for the defects using electronic microscope. Show less

Aerodynamics Team Lead for Blended Wing Body Unmanned Aerial Vehicle Design- Design and finalise of BWB wing dimensions- Selection of three supercritical airfoils for wing and one symmetric airfoil for tail - Aerodynamic analysis of airfoils and their aerodynamic performance

Aerodynamic and Structural Analysis of Hexacopter - Designing a modular type of Hexacopter for heavy payload carrying purpose- Structural Analysis of Hexacopter design and evaluation of loading carrying capacity using ANSYS 18.1- Material selection and dimension finalising with the results obtained

> Generated data models, performed computational analysis and helped produce reports outlining results.> Coordinate with students and team meet regulatory requirements for checking the verification and document filings.> Provided tutorials on design and simulation using CAD/CAE software and taught the engineering drawings and calculations for students.