Rana Zeeshan Haider

• Worked closely with R&D scientists in small teams to support ongoing clinical projects.
• Extrapolated test data with both manual and computerised procedures.
• Designed and developed analysis system to extract information from lab information management system (LIMS)
• Developed patient segmentation algorithm
• Automate the decision support system by 50%

• Gathered and organized materials to support research of Graduate and Post-Graduate Students.
• Coached Research Students through day-to-day work and complex problems.
• Created customized applications to make critical predictions, automate reasoning and decisions and calculate optimization algorithms for effective clinical practices.
• Prototyped machine learning applications and quickly determined application viability for hospitals.
• Developed advanced graphic visualization concepts to map and simplify analysis of heavily-numeric data and reports.
• Transformed raw electronic health records (data) to conform to assumptions of machine learning algorithm.
• Identified new healthcare problem areas and researched technical details to build innovative products and solutions.
• Studied new technologies to support machine learning applications.
• Collaborated with multi-disciplinary product development teams to identify performance improvement opportunities and integrate trained models.
• Improved data collection methods by designing surveys, polls and other instruments.
• Modeled predictions with feature selection algorithms.
• Analyzed large datasets to identify trends and patterns in patients therapeutic responses.

• Worked actively with management team to conduct academic and research activities effectively.
• Motivated associates to consistently deliver effective learning behaviors through coaching and recognition.
• Worked with co-principal investigator and sponsors to facilitate research activities and comply with research protocols.
• Supervision on primary research, data collection, bibliographies and model writing assistance.
• Supported curriculum development professionals for healthcare and information systems.
• Assisted candidates in devising tailored Ph.D. title and proposal development, preparation of model upgrade reports demonstrating progress and compilation of collaborative example chapters.
• Researched, published and presented current topics of study at national and international meetings.
• Mentored students, offering advice and support on topic selection, appropriateness and academic value.

• Mentored students and communicated internship and employment opportunities.
• Provided logical integration and continuity of Clinical Machine Learning and Data Science skills training and assessment across whole curriculum.
• Performed research to serve as basis for academic writing for publication.
• Applied innovative teaching methods especially AR/VR/Mixed Reality to encourage student learning objectives.
• Developed independent research program with extramural funding and publication of research in peer-reviewed journals.
• Utilized advanced querying, visualization and analytics tools to analyze and process complex research data sets.
• Discovered stories told by research data to present information to scientists and clinicians.
• Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling.
• Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
• Developed polished visualizations to share results of data analyses.

• Planned and initiated research study protocols, monitored regulatory and subject binders and organized, implemented and administered data collection and analysis systems.
• Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
• Story telling from research and diagnostic data
• Identified, measured and recommended improvement strategies for KPIs across research areas.
• Extracted and assessed data from databases to drive improvement of R & D.
• Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
• Compiled, cleaned and manipulated data for proper handling.
• Applied loss functions and variance explanation techniques to compare performance metrics.
• Ran statistical analyses within software to process large datasets.
• Modeled predictions with feature selection algorithms.

• Extrapolated test data with both manual and computerized procedures.
• Worked closely with R&D scientists in small teams to support ongoing clinical projects.
• Handled preventive maintenance and calibration of laboratory equipment.
• Tested clinical samples according to protocols and reported results within established turnaround time.
• Worked with medical directors, clinical operations, biostatistics and other groups to conduct clinical reviews of study data.
• Followed Good Laboratory Practices (GLP) consistently across daily activities and special products.
• Used correct formulas and procedures to prepare solutions and reagents for testing needs.
• Analyzed and interpreted data, accurately identifying and reporting laboratory results.
• Conducted wide range of laboratory tests and recorded results.

• Received with Research Grant of 100K Turkish Lira

Research Paper: Cell Population Data-Driven Acute Promyelocytic Leukemia Flagging Through Artificial Neural Network Predictive Modeling published in Translational Oncology, Jan 2020

Data Sciences and Machine Learning Project on Diagnostic Research Dataset

Hematology (Research Work: Clinical Machine Learning, Supervisor: Prof. Dr. Tahir Shamsi, Campus- National Institute of Blood Disease)