Itilekha podder (Iti)

I am Iti, a Data Scientist at Robert Bosch Kft. and a Doctoral Student at Eötvös Loránd University, Budapest, Hungary. I specialize in leveraging AI and ML applications within the semiconductor manufacturing sector. My role involves implementing advanced analytics to optimize processes and enhance product quality. I am also interested in applying AI to healthcare advancements, aiming to drive significant improvements in medical technologies and patient care. Through my research, I aim to bridge the gap between theoretical advancements and practical applications, driving impactful change in the industry.

Alongside my technical expertise, I also have a passion for business development. With strong communication and writing abilities, I excel in conveying complex concepts effectively, facilitating collaboration and project success.

Work experinece

Data Scientist at Robert Bosch Kft., Budapest, Hungary

(12/2019- Present)

I led the development of data-driven solutions for MEMS sensor manufacturing automation, overseeing a project that reduced production time by 28% and improved efficiency. I also worked on other research projects on early fault prediction and root cause analysis caused by thermal drift in gyroscopes. I developed an unsupervised and semi-supervised wafer map clustering solution to enhance quality control processes.

My role also involved active participation in the Design Review Based on Failure Mode (DRBFM) process, effective stakeholder communication and numerous sprint-related activities. I authored several invention reports and recently submitted a patent for a novel optimization technique in sensor manufacturing.

Researcher in Machine Learning for Signal Processing at Spinal Cord Injury & Artificial Intelligence Lab, ETH Zurich, Switzerland

(02/2023- PrEsent)

My work was to develop a robust multimodal sensor fusion algorithm for blood pressure estimation in Spinal Cord Injury (SCI) individuals. My proposed framework involved data collection, feature extraction, algorithm development (CNN, TL), validation and optimization. Ultimately, my work aimed to enhance patient blood pressure monitoring and clinical decision-making for SCI individuals.

Teaching Assistant, Computer Science at Eötvös Loránd University (ELTE), Budapest, Hungary (09/2021- Present)

I have prepared and taught theoretical and practical courses in software technology and business development, supervised multiple data science-related master theses, and designed and taught practical classes in imperative programming. Additionally, I have mentored bachelor's and master's students, providing guidance and support throughout their academic journeys.

Researcher at Ericsson, Hungary research and development centre (02/2019- 08/2019)

This research work encompassed a comparative analysis of detecting objects in real-time using various object detection models (SSD mobile nets, faster rcnn resnet etc.) and diverse environmental setups (LAN, WIFI , 3G connection, GPU, CPU )to assess the network's computational capacity regarding the accuracy, detection frame, and latency.

Education

Doctoral Student in data science at Eötvös Loránd University (ELTE), Budapest, Hungary (Minor in innovation and Business Development) (09/2020- Present)

In collaboration with Eötvös Loránd University, Budapest, Hungary, Robert Bosch Kft., Budapest, Hungary and the European Institute of Innovation and Technology (EIT) Digital Doctoral School, my research work aims to develop an efficient method for AI-based solution implementation for industrial optimization especially in semiconductor manufacturing. I received the EIT Doctoral Scholarship (2020-Present). I applied design science research and process management to develop a standardized data mining process model in Data Science, facilitating digital transformation initiatives. This approach enabled the creation of a robust framework for data-driven solutions, optimizing workflows and enhancing the efficiency of data mining operations.

Master of Science in computer science (Minor in innovation & entrepreneurship): Double MSc. Degree (08/2017- 01/2020) GPA: 4.64

In collaboration with Delft University of Technology (TU Delft), Delft, Netherlands, Budapest University of Technology and Economics (BME), Budapest, Hungary and the European Institute of Innovation and Technology (EIT) Digital Master School.

Double MSc. degree in digital media technology focusing on Autonomous Vehicles and Innovation and Entrepreneurship knowledge. Attended summer schools in Big Data.