Shyamal Parikh
About Shyamal Parikh
Shyamal Parikh is a Senior Software Engineer at HSBC, specializing in machine learning and natural language processing. He has a diverse background in engineering and research, with experience in various organizations and expertise in deep learning techniques.
Work at HSBC
Shyamal Parikh has been employed at HSBC as a Senior Software Engineer since 2021. His role involves leveraging his expertise in software engineering to contribute to various projects within the organization. His tenure at HSBC is marked by a focus on developing and optimizing software solutions that meet the needs of the financial sector.
Previous Experience in Software Development
Prior to his current position at HSBC, Shyamal Parikh worked at L&T Technology Services Limited as an Engineer from 2018 to 2021. He also held a position as a Machine Learning Developer at Technostacks Infotech Pvt. Ltd. for three months in 2018. His earlier roles include serving as a Research Associate at Navrachana University from 2017 to 2018 and as an Executive at SEFORGE LTD INDIA in 2017.
Education and Expertise
Shyamal Parikh holds a Master’s Degree in Engineering Physics/Applied Physics from The Maharaja Sayajirao University of Baroda, which he completed from 2014 to 2016. He also earned a Bachelor’s Degree in Physics from the same institution from 2011 to 2014. His academic background supports his specialization in machine learning, natural language processing, and image processing.
Technical Skills and Specializations
Shyamal Parikh specializes in sequence modeling techniques, including LSTM and Bi-Directional LSTM, as well as Dilated Convolution. He applies natural language processing using libraries such as NLTK, Spacy, and gensim, and incorporates speech processing capabilities with tools like Audacity and Librosa. His expertise extends to image classification and deep learning frameworks, utilizing Mxnet and Tensorflow.
Projects and Contributions
In his career, Shyamal Parikh has developed algorithms for extracting locations of document units in projects focused on data extraction from banking documents. He optimizes computational processes using CUDA and MKL libraries, enhancing performance in deep learning applications. His work also involves advanced image and signal processing techniques using tools like OpenCV and Scikit-Image.