at Brane Enterprises Pvt. Ltd. , Hyderabad (Feb 2024 - Feb 2025)
Developed and optimized deep learning models using TensorFlow and PyTorch for e-commerce clients, contributing to a 15% increase in sales through product price optimization and segmentation.
Analyzed large datasets to extract actionable insights, driving business decisions and strategy for retail sector clients, which resulted in a 10% sales forecast improvement.
Utilized Python, SQL, and data visualization tools such as Tableau and Superset for comprehensive data manipulation, preprocessing, and trend identification.
Collaborated with cross-functional teams and senior leadership to conduct statistical analyses and present data-driven findings to inform strategic decisions.
Managed multiple data analysis and model development projects concurrently, ensuring timely delivery, high-quality outputs, and alignment with key business objectives.
at the MEMS lab at Department of Metallurgical and Materials Engineering, IIT Madras (Jan 2021 - June 2024)
Conducted comprehensive literature reviews on the friction stir welding of dissimilar metals, focusing on the mechanical and microstructure-property correlation of weld joints.
Designed and executed the experiments using the tools such as on AutoCAD, Fusion 360, FSW CNC machine to weld the dissimilar materials, systematically varied process parameters to gather quantitative data for achieving maximum joint efficiency.
Systematically documented all experimental data, including FSW process parameters, temperature, characterization results, and mechanical testing outcomes. This organized dataset was crucial for building and validating the machine learning models used to predict the ultimate tensile strength of the welds.
Processed and interpreted the data using advanced characterization equipment, including SEM, EDS, XRD, and EBSD, to investigate material mixing and microstructural evolution.
Prepared and presented findings at the Thermec 2023 international conference in Vienna, Austria as well as Amalgum national symposium at IIT Madras.
Assisted the Professor in conducting courses and examinations.
Led weekly lab sessions to demonstrate and clarify the experiment protocols to a batch of 70 students.
at IIT Madras
Placement Coordinator, Institute Placement Team, IIT Madras
Facilitated the annual campus placement drive for the 2022-2023 academic year, managing logistics and communication between students and recruiters.
Collaborated within a 250+ member team to ensure the smooth execution of the institute's largest and longest recruitment event.
Coordinator, Career Development Cell - Research (CDC-R)
Organized various workshops and mentorship programs designed to guide students pursuing careers in research.
As Logistics Team Coordinator for the RSD Fest, managed event planning, scheduling, and operations, coordinating with multiple teams to ensure a timely and successful event.
Department Development Programme
(Metallurgical and Materials Engineering Dept., IIT Madras | Jan 2022 - June 2023)
Supported the Departmental Visibility Program by collaborating with the Head of Department, professors, and stakeholders to enhance the department's profile.
My responsibilities included collecting, compiling, and synthesizing data to create reports and promotional materials showcasing departmental achievements.
at OSN Consulting & Associates, Uttar Pradesh (India) (Oct 2019- Dec 2020)
Contributed to large-scale industrial projects by performing detailed technical and financial valuations of plant and machinery, with asset values ranging from INR 150-200 Cr.
Prepared comprehensive valuation reports that integrated technical specifications, operational condition, and market value to deliver clear and actionable insights.
at Dynamic Infratech Pvt. Ltd., Kota (Rajasthan) (Jul 2018 - Sept 2019)
Led a production team in the fabrication of steel bridge components for key projects with Indian Railways, overseeing operations to ensure timely delivery and adherence to high-quality standards.
Drove a 9-10% increase in the production rate by applying data-driven analysis to optimize machining parameters.
Implemented process optimization techniques to ensure all fabricated components consistently met stringent product quality and safety standards.