S. Ravichandran:
Data Scientist, Adjunct Faculty, Self-learner

Professional Highlights 

Hi, I'm Ravi, a senior data scientist with a passion for using machine learning to solve real-world problems. On this website, you can learn more about my work, skills, and experience.   

About Me 

I  am a data scientist with a passion for using machine learning to solve real-world problems. I have over 20 years of experience in the field, and I have worked on a variety of projects in healthcare, public health, and other fields. I am also an adjunct faculty member at Hood College, where I teach courses in Bioinformatics and Functional Genomics.

My expertise includes machine learning, artificial intelligence, bioinformatics, data modeling, data mining, and data visualization. I am particularly interested in using machine learning to identify social determinants of health and to develop predictive models for healthcare and public health. I am also interested in using biological data modeling techniques to study infectious diseases and cancer.

In my current role at Leidos Inc., I am responsible for developing and applying machine learning solutions to a variety of healthcare and public health problems. I have also worked on projects to develop data pipelines and to harmonize and extract insights from diverse data sources.

I am passionate about mentoring and training others, and I have mentored several data scientists and students. I am committed to lifelong learning and continue to develop my skills in AI/ML in my spare time.

Certifications 

• AWS Cloud Practitioner (since 2022)

• Project Management Professional (PMP; since 2018)

Technical Skills/Experiences 

With proficiency in Python and R programming languages, as evidenced by my GitHub link, I am passionate about utilizing R/RStudio for biocomputing and teaching applications. I also have hands-on experience with cloud computing platforms such as AWS/Google, where I have used SQL to extract data from databases and applied ETL (Extract, Transform, and Load) processes to generate and utilize Data Warehouses. Over the last two decades, I have gained extensive experience working in the Linux OS environment, specializing in compiling, installing, and testing codes within a Linux compute cluster environment. Additionally, I have expertise in writing Shell scripts (Bash and tcsh) for developing bioinformatics pipeline frameworks, as well as creating intricate Portable Batch Systems (PBS) batch job scripts for lengthy jobs and analyses.

Personal Interests 

• Life-long learning (Completed more than 95 online classes); Please check my LinkedIn for details, https://www.linkedin.com/in/sakaravi/ 

• Scientific Journal Reviewing

• Scientific writing/communication 

• Mentoring/Teaching 

Some of my recent publications are shown below:  

Two manuscripts are currently in the process of review at various journals and one is close to the submission stage. Please visit, https://sites.google.com/site/sakaravi/Home/publications, for a complete list:

• Machine learning approach to examine intersectionality and health behaviors (Under preparation, 2023) 

• Joint publication with pFDA on Making Sense of EHR Race and Ethnicity Challenge (Under Preparation; 2023)

• Enhancing Public Health Data Quality: CDC Health Data Innovation Summit, CDC, Sep 27-28, 2023, S.Ravichandran and Chetan Paul, Event Event Link: https://www.fbcinc.com/e/cdcga/speakers.aspx
  Abstract Link: https://www.fbcinc.com/e/cdcga/speakers.aspx 

• Scientific Review Alignment and Knowledge Gap Analysis in Data Multiverse, K.Y. Stephen Ho, V. Sam, J. Shah, L. Benson, Ning Yu, S. Ravichandran, Chetan Paul, Sep 12-12 (2023)
  YouTube link: https://www.youtube.com/watch?v=_pUwQwjpL0c 

• Making Sense of Electronic Health Record (EHR) Race and Ethnicity Challenge, Top Performer Webinar and Roundtable discussion, Precision FDA (Aug 2023)
  Challenge Link: https://precision.fda.gov/challenges/30 

• Prognostic and Predictive Classification Approaches, NIH Long-Covid Computational Challenge, Bethesda, MD 2023.

• Simulating in-silico Clinical Research Using Diverse Real-World Data, S. Ravichandran and Chetan Paul, 2022 Scientific Computing Days, FDA, Poster Presentation,  8/19 2022 (selected in the poster contest for live presentation;
  Poster Link: https://www.fda.gov/drugs/news-events-human-drugs/2022-scientific-computing-days-poster-gallery  ) 

• Simulating in-silico Clinical Research Using Diverse Real-World Data, S. Ravichandran and Chetan Paul, 2022 Scientific Computing Days, FDA, Virtual Presentation,  Sep 7-8, 2022 (selected among top-5 in the poster contest for live presentation)
  FDA Link: https://www.fda.gov/drugs/news-events-human-drugs/2022-scientific-computing-days-09072022#event-materials ) 

• AVIA 3.0: interactive portal for genomic variant and sample level analysis, Bioinformatics, 2021 Aug 25;37(16):2467-2469;
  PubMed Link: https://pubmed.ncbi.nlm.nih.gov/33289511/

Contact Info

S. Ravichandran, PhD, PMP

Email: saka dot ravi at gmail dot com web: https://sites.google.com/site/sakaravi/