Hi, I am Souradip !!

I am currently pursuing MS in Electrical and Computer Engineer at Purdue University (West Lafatyette). I completed my bachelor's degree from Indian Institute of Technology Guwahati in 2019 with major in Electronics and Communication Engineering. My passion is Computer Science. My interests include statistical machine learning, deep learning, high performance computing, cloud computing, optimization and algorithm design and analysis. Previously, I have worked as a software developer at Adobe Inc. India in the Business Platform Engineering group which is a part of Adobe's e-commerce tribe.

Education

Purdue University - West Lafayette

Degree: Master of Science (August 2022 - Present)

Major: Electrical & Computer Engineering

Courses

  • Computational Models and Methods
  • Introduction to Artifical Intelligence
  • Elements of Stochastic Processes
  • Random Variables and Signals
  • Deep Learning

Indian Institute of Technology Guwahati

Degree: Bachelor of Technology

Major: Electronics & Communication Engineering

Courses

  • Data Structures and Algorithms
  • Probability and Random Processes
  • Pattern Recognition and Machine Learning
  • Introduction to Parallel Computing
  • Speech Technology

Experience

Software Engineering Intern - SLB (Schlumnberger Ltd.)

I worked as a Software Engineering Intern at SLB in the Pressure, Pumping, and Chemistry Unit in Sugar Land, Texas where I developed a light-weight data simulator for automation testing of a well-site orchestration platform using .NET Core. The orchestration platform provides real-time and look-ahead visibility to help coordinate different stages of wellsite activities thus reducing non-pumping time. I created a CLI and a web UI in Angular to run simulations based on data generated by user-defined simulation parameters to reduce the cost of using hardware simulators for testing.

Software Development Engineer - Adobe Inc. India

I worked as a Software Development Engineer I and II at Adobe Inc. India(Bangalore). Here, I was involved in the design, development and maintenance of java based micro-services under a cloud-based internal e-commerce platform used for creation and management of offers or products released/to be released to market. My primary area of expertise was in the prepurchase section of the transactional journey which includes merchandising, pricing and other related components of the product offering. I have contributed in multiple business initiatives and worked on areas of data pipeline automation in product cataloguing, business rule management system, enhancing catalogue search using natural language processing etc.

Student Trainee - Samsung R&D Institute India

I attended Samsung R&D Institute India(Bangalore) in 2018 as a summer research intern where I worked at the Advanced Technology Lab. Here, I worked on a deep learning model for predicting the stress on a glass surface of a mobile device based on the different 3D parameters of the glass (thickness, radius of curvature, etc). The model was based on the state-of-the-art PointNet architecture by Charles R. Qi et. al. The model was trained using transfer learning and modified to predict stress data in point cloud form obtained from Four-Point Bending simulations of glass in CAD.

Summer Fellowship - FOSSEE, IIT Bombay

I worked as an Software intern in the summer of 2017 at the open source organization FOSSEE (Free/Libre and Open Source Software for Education) based at Indian Institute of Technology Bombay. The organization is part of the National Mission on Education through Information and Communication Technology(NMEICT), which promotes the use of open source software tools to improve the quality of education and research. I worked on building software packages for a simulation tool called OpenModelica which helps in interfacing electrical circuits with Arduino UNO boards. I also provided GUI based modelling and simulation support for different types of AVR architectures.

Research

Triple Pendulum Based Nonlinear Chaos Generator and its Applications in Cryptography

Author(s): Bikram Paul, Souradip Pal, Abhishek Agrawal, Dr. Gaurav Trivedi
This research explores post-quantum cryptography methods and proposes a novel approach to design an encryption scheme based on the chaotic dynamic physical system, which is derived from a mechanical model of a triple-pendulum system depicting nonlinear dynamics. The proposed cryptography scheme exhibits resistance against various attacks and is validated using benchmark tests, such as Lyapunov exponents test, bifurcation diagrams, sensitivity to parametric and to initial values, ergodicity, collision test, NIST, diehard randomness test etc. The proposed algorithm is implemented on an FPGA using System-Verilog.

Projects

Reinforcement Learning via. Sequence Modeling using Decision Transformer

This project involved studying the effect of context length on the variances of the expected returns of the Decision Transformer model in OpenAI Gym environments and Atari games in both online and offline settings.

Box Regression using KL Loss

This project includes several experiments to reproduce the results of the paper "Bounding Box Regression with Uncertainty for Accurate Object Detection" by He et al. The paper introduces a new regression loss function called KL-Loss for accurately predicting the bounding box locations for object detection using localization variances. The methods in the paper were reimplemented in PyTorch and tested on PASCAL-VOC dataset.

Automatic Speech Segmentation

The aim of this project was to segment speech sequences based on speaker transitions, where the number of speakers is not known beforehand. Additionally, it can identify the number of speakers along with the zones where single or multiple speakers are active. Both supervised and unsupervised diarization approaches on LPC(Linear Predictive Coding) features were performed and tested on synthesized audio clips.

Large-Scale Black Box Optimization

This project shows a comparison between the serial and parallel versions of two evolutionary strategy algorithms which uses sparse plus low rank model for large-scale black box optimization [Rank-One evolution strategy(R1-ES) & Rank-m evolution strategy(Rm-ES)]. Both of these algorithms were parallelized using OpenMP and their convergence and speedup were analysed with respect to some critical parameters.

OpenModelica HIL Simulation

The problem involves building a hardware-in-the-loop simulation with a DC motor as a software plant, and a proportional control algorithm running on the Arduino. The process is expected to run in real time which means that a delay should not be used. An OpenModelica package was built which is able to conduct such Arduino involving HIL simulation using interprocessing communication.

Skills

Languages

Web Technologies

Libraries & Frameworks

Software Tools

Contact

If you have any questions, or if you just want to say hi, please feel free to send a message or email me.
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