CV

## Vidhi Lalchand

Born in India

Lives & works in Cambridge, UK

###### Education

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###### University of Cambridge (Christ's College), UK

Dept. of Physics

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###### 2017 - Doctoral Researcher in Machine Learning. (Ph.D expected in 2020).

2015 - 2016 M.Phil in Scientific Computing (Distinction)

###### London School of Economics, LSE

2009 - 2010 M.Sc in Applicable Mathematics (Distinction).

2005 - 2008 B.Sc. Mathematics (First).

Thesis and Reports

Computing Skills

Scripting: Python, R

ML Libraries: scikit-learn, tensorflow

GPU Programming: CUDA

Databases: SQL

Others: Unix, Shell and Latex

Industry

2014-2015 High Frequency Trader at Citadel Investment Group (Quantitative Strategies).

2012-2014 Quantitative Analyst at Credit Suisse Securities, Europe (Electronic Market Making).

Honors & Awards

2008 University of London Award for Academic Excellence for External Students.

2016 Alan Turing Doctoral Fellowship for International Students.

2017 Asian Voice - An Unconventional Journey from Banking to Science.

Talks and Posters

CogX 2018, Research Stage, June 2018

Talk on 'Deconstructing Gaussian Processes'

YouTube link

The Scientific Advisory Board, The Alan Turing Institute, June 2018.

Poster on A meta algorithm using random recursive tree ensembles: A high energy physics application.

Publications & Pre-prints

V.R. Lalchand, A.C. Faul. A progressive framework for Gaussian Process Regression.

38th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.

August 2018.

Presentation

Vidhi Lalchand, A.C. Faul. A greedy approximation scheme for Sparse Gaussian Process regression.

Maxwell Center, University of Cambridge, Oct 2017

Talk on 'A gentle introduction to Gaussian Processes'

P Treleavan, M Galas and V Lalchand. Algorithmic Trading Review

Association of Applied Computing Machinery, November 2013.