Lakshmi Krisha Kanumuru, Ph.D.
EPR Application Analyst at Manchester University NHS Foundation Trust- Claim this Profile
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English Native or bilingual proficiency
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Telugu Native or bilingual proficiency
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Hindi Limited working proficiency
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Gujarati Limited working proficiency
Topline Score
Bio
Credentials
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Cupid
Epic -
The Complete SQL Bootcamp
Udemy
Experience
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Manchester University NHS Foundation Trust
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United Kingdom
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Hospitals and Health Care
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700 & Above Employee
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EPR Application Analyst
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Oct 2021 - Present
- Expertise in full-cycle workflow implementation, with a strong focus on design, development, and deployment of custom workflows, integration with various third-party interfaces such as Muse, ISCV, Spacelabs, and registry management - Successfully led workflow analysis sessions, effectively coordinating testing with various stakeholders and third-party vendors to ensure seamless project execution - Spearheaded non-invasive cardiology workflows, including Echo, Stress, Cardiac CT/MR, ECG and Holter procedures, resulting in a streamlined and efficient workflow process - Successfully drove the transition of MFT hospitals from legacy systems to Epic EHR, with a key emphasis on the implementation of the Cardiology module for optimized results - Played a lead role in the Cupid team for ensuring business continuity access and successful cutover implementation - Efficiently managed end-user acceptance testing and design validation meetings, ensuring end-users' needs were met and exceeded
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University of Kent
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United Kingdom
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Higher Education
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700 & Above Employee
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Graduate Teaching Assistant
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Sep 2016 - Oct 2021
- Delivered student labs and workshops in various programming languages including C/C++, MATLAB foundations, LabView, Android, and Arduino, as well as MATLAB's Simulink, Signal processing, and Control systems- Facilitated the delivery of the MATLAB module as a coordinator for three years and supported the digitization of student assessments- Conducted evaluations and graded student submitted work and in-class assessments, providing feedback and support for academic developmentPh.D- Awarded the Vice Chancellor’s Scholarship 2016- Conducted research in the area of Deep Learning models for Electroencephalography (EEG) motor imagery data- Designed a pipeline for transforming EEG data into image data that could be used by deep convolutional networks- Collected bilingual multi-class motor imagery data using medical-grade EEG sensors- Created a Python interface for live EEG data visualization and collection- Co-wrote the Robotics Chapter (pages 311 to 345) in the Handbook of Assistive Technology 2018
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Researcher - RAPPER III Project
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Sep 2016 - Dec 2017
- Collaborated on a study of the effects of physiotherapy on Multiple Sclerosis patients using a robotic exoskeleton and biosensing devices- Synchronized data and developed protocols for wireless EMG, goniometer, foot pressure devices, and pulse rate monitors- Supervised interns in the synchronization of biosensing data using MATLAB and collection of bilingual data using EEG electrodes and python software integration- Worked closely with physicians to support patient data collection and ensure accurate results.
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School of Engineering and Digital Arts Student Ambassador
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Sep 2015 - Aug 2016
- Served as a Student Ambassador for the School of Engineering and Digital Arts- Facilitated student ice-breaker sessions to create a positive learning environment- Prepared and delivered student talks and tours to provide an overview of the program and facilities.
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Project Researcher - BioMedical Research Project
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Jul 2015 - Sep 2015
Improved control of optical laser tweezers using LabVIEW Virtual Instruments (VIs) and Field-Programmable Gate Array (FPGA) technology.
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Mocketts Wood Surgery - NHS England
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Broadstairs, Kent
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IT Lead
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Jan 2014 - Oct 2021
- Created COVID-19 response templates and protocols to facilitate the efficient identification of vulnerable patients by administrative staff, resulting in successful contact with 80% of patients within 2 weeks - Initiated carer templates and search pathways, resulting in a 100% increase in carer prevalence within 3 weeks - Coordinated the digitization of historic patient notes, achieving a 100% paperless system in just 10 days - Led the optimization of IT systems for improved efficiency and operation Assessed and enhanced workflow processes for staff, promoting a culture of swift adoption of efficient IT solutions - Conducted training and provided updates to staff on various NHS IT systems, including EMIS, and Docman, fostering a more efficient and effective workplace - Acted as the main point of contact for IT-related issues, providing support and advice to staff and ensuring timely resolution of problems - Managed hardware procurement and maintenance, ensuring the practice had the latest technology to support their needs and drive forward change - Collaborated with suppliers and outside agencies to resolve complex technical issues, ensuring the surgery had the support it needed to run smoothly and effectively.
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TOPDOC.AI
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United States
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Computer Software
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Machine Learning Intern
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Jan 2018 - Dec 2019
- Conducted an analysis to determine the most suitable Machine Learning algorithms for achieving business goals - Implemented Machine Learning techniques in developing proof of concept - Carried out research in clinical data analytics and handwriting recognition - Utilised Amazon Textract to create smart search indexes and extract clinical data from anonymous patient health records - Designed Excel templates with database models, which allowed for the seamless integration of data and conversion to master data in MySQL databases.
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Education
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2016 - 2022
University of Kent
Doctor of Philosophy (Ph.D.), Electronic Engineering -
2012 - 2016
University of Kent
Bachelor of Engineering (BEng), Electronic and Communications Engineering
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