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Huma Lodhi

Data Scientist, Manager @ Cognizant

Artificial Intelligence, Machine Learning, Data Science

United Kingdom

Ranked #713 out of 14,260 for Data Scientist, Manager in United States

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Huma Lodhi's Email Addresses & Phone Numbers

Huma Lodhi's Work Experience


Data Scientist, Manager

April 2015 to Present

London, United Kingdom

IMS Health

Consultant, Advanced Analytics, RWES, HEOR

January 2014 to April 2015

London, United Kingdom

University of Warwick

Research Fellow

July 2013 to January 2014

Huma Lodhi's Education

Royal Holloway, University of London

PhD Computer Science

1998 to 2002

Huma Lodhi's Professional Skills Radar Chart

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Huma Lodhi's Estimated Salary Range

About Huma Lodhi's Current Company


Data science solutions for problems in oil and gas sector.

Frequently Asked Questions about Huma Lodhi

What company does Huma Lodhi work for?

Huma Lodhi works for Cognizant

What is Huma Lodhi's role at Cognizant?

Huma Lodhi is Data Scientist, Manager

What is Huma Lodhi's personal email address?

Huma Lodhi's personal email address is hu****[email protected]

What is Huma Lodhi's business email address?

Huma Lodhi's business email address is h****[email protected]

What is Huma Lodhi's Phone Number?

Huma Lodhi's phone +44 ** **** *326

What industry does Huma Lodhi work in?

Huma Lodhi works in the Oil & Energy industry.

Who are Huma Lodhi's colleagues?

Huma Lodhi's colleagues are John Stansel, Nitin Gupta, David Hayes, John Phillips, Belal Atiyyah, Ellen Kuplic, Ben Teusch, Carl Mountford, Emily Murray, and Amy Peloza

About Huma Lodhi

📖 Summary

An expert in machine learning and data science. Highly experienced academic and commercial researcher in analytics, and professional software developer. Ability to provide effective solutions for complex business problems. Specialised in developing and extending novel machine learning methodologies and algorithms. Proven skills in applying computational techniques for solving challenging problems in wide range of areas including health care, pharmaceutical, text mining and computer vision. Specialities Machine learning - Kernel methods (e.g. support vector machines) - Deep learning (e.g stacked auto encoders, deep belief nets) - Statistical relational learning - Ensemble method (bagging, boosting) Big data analytics Healthcare and PharmaceuticalsData Scientist, Manager @ Data science solutions for problems in oil and gas sector. From April 2015 to Present (9 months) London, United KingdomConsultant, Advanced Analytics, RWES, HEOR @ - Design and development of an intelligent system for rare disease identification. - Uplift modeling for patient-level data segmentation. - Enhancement of propensity score analysis and covariate shift correction through Machine Learning. - Providing training and guidance for Machine Learning and Data Science methods. From January 2014 to April 2015 (1 year 4 months) London, United KingdomResearch Fellow @ - Co-development of an innovative system, based on graph-based kernel methods, for human activity recognition in video surveillance. From July 2013 to January 2014 (7 months) Research Fellow @ - Research and development of novel deep learning algorithms for learning meaningful representations. - Utilisation of these methods for solving predictive problems: - video based activity recognition for industrial work support - predictive toxicology in drug development and environmental protection. From December 2011 to December 2012 (1 year 1 month) Leeds, United KingdomResearch Fellow @ - Development of regression techniques for parameter estimation in dynamic systems described by Ordinary Differential Equations. From December 2009 to November 2011 (2 years) Post-doctoral Researcher @ - Development of multi-class classification algorithms within large margin learning framework - Development of dimensionality reduction techniques - Bias-variance analysis of statistical relational learning algorithms - Application of these techniques to challenging problems: . Predictive toxicology in drug design and environmental protection . Protein fold identification in structural genomics. From November 2006 to November 2009 (3 years 1 month) London, United KingdomPost-doctoral Researcher @ - Development of structured kernels based methodology for human motion analysis. From April 2006 to October 2006 (7 months) Sheffield, United KingdomPost-doctoral researcher @ - Development of a novel framework for integrating statistical and relational learning. - Co-invention of a methodology for solving predictive problems that are characterized by uncertainty and relational information. The general-purpose technique is at the intersection of two areas of Machine Learning namely Kernel Methods and Inductive Logic Programming. Application of the method to Quantitative Structure Activity Relationship Analysis for drug discovery. - Development of bagging-type methods for learning networks and pathways. Development of methods for for measuring confidence in statistical relational learning models. Co-development of a text mining approach. Development kernel-based approach for Structure Activity Analysis in drug development. From January 2002 to March 2006 (4 years 3 months) London, United KingdomPhD, Computer Science @ Royal Holloway, University of London From 1998 to 2002 Huma Lodhi is skilled in: Artificial Intelligence, Machine Learning, Data Mining, R, Computer Vision, Data Science, Algorithms, Predictive Analytics, C++, Matlab, SAS, Python, STL, LaTeX, Statistical Data Analysis

Huma Lodhi’s Personal Email Address, Business Email, and Phone Number

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In a nutshell

Huma Lodhi's Personality Type

Extraversion (E), Intuition (N), Thinking (T), Judging (J)

Average Tenure

1 year(s), 8 month(s)

Huma Lodhi's Willingness to Change Jobs



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