SBI – Department of Systems Biology and Bioinformatics
Faculty of Computer Science and Electrical Engineering
University of Rostock
Ulmenstrasse 69 | 18057 Rostock
Germany
+49 381 498-7571
olaf.wolkenhauer@uni-rostock.de

Prashant Srivastava

Research interest

Machine Learning, Deep Learning, Image Analysis, NLP, Time Series Analysis

Academic background

2020	Master's Thesis Dept. of Computer Science, Royal Holloway University of London Statistical risk methods in financial markets. EWMA and GARCH Volatility models. Monte-Carlo and Historical simulations. Basel Committee on Banking Supervision models including Expected Shortfall and Value at Risk.
2017-2020	Master's Thesis Dept. of Physics, Indian Institute of Science Education and Research, Kolkata Extraordinary transmission in silicon-based micro-meter wire grid polarizers. FDTD simulations. Quarter and half waveplates in Terahertz region.
2018 - 2020	MSc Data Science and Analytics Royal Holloway, University of London Field(s) of study Principles of Computation and Programming : 97/100 Programming for Data Analysis : 89/100 Individual Project : 82/100 Deep Learning : 76/100 Data Analysis: 76/100 Machine Learning: 75/100 Grade Average: 78.3/100, Pass with Distinction
2013-2018	Integrated B.S.-M.S. Indian Institute of Science Education and Research, Kolkata (Nature Index rank 9 in India) Field(s) of study Physics

Skills

Programming in Python (numpy, scipy, pandas, matplotlib, seaborn, scikit-learn, tensorflow, keras, mlflow).
Library development in Python (https://github.com/srivastavaprashant/mgarch).
Programming in R, C++ and MATLAB.
State-of-the-art machine learning technologies (CNN, RNN, GAN, NLP,
Auto-encoders).
Web development (HTML, CSS, JavaScript, PHP).
Distributed/Cloud computing (PySpark, Microsoft Azure).
Database systems (SQL, PostgreSQL, NoSQL)
Latex, Git, Bash

Education and Work Experience

2020 -

Research Assistant
University Rostock, Germany

2019 - 2020

Data Scientist
London, United Kingdom, Elevate Credit International Limited

Built and implemented machine learning pipelines to support business
strategies and automate processes.

Projects: Open Banking Data, Fraud Detection, Credit Risk.

Achievements:

Reduced company’s operation costs by automating underwriting
manual processes.
Prevented fraudulent applications by 80%.
Developed a time series credit scoring model.

2017-2018

Teaching Assistant
Indian Institute of Science Education and Research, Kolkata

Teacher for scientific programming in Python.
Tutored a batch of 200 M.S. students.

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