S. Ravichandran
Data Scientist | Innovator | Mentor

Professional Highlights 

Hi, I'm Ravi, a senior data scientist passionate about using machine learning to solve real-world problems. You can find more information about my work, skills, and experience on this website.

About Me 

I'm a data scientist with over 23 years of experience, passionate about unlocking insights from complex data and creating innovative solutions for real-world problems in healthcare, public health, and beyond. I specialize in healthcare-focused work, particularly in data science within genomics and computational biology. My expertise is further evidenced through my innovative approach to creating and implementing concepts, including R&D, implementation, and expertise in collaboration with esteemed colleagues. This is evidenced by my publications and presentations in these areas. As an adjunct faculty member at Hood College, I cultivate the next generation of data scientists by teaching/mentoring Bioinformatics and Functional Genomics courses.

My expertise encompasses:

• Computational Biochemistry/Informatics: I leverage my knowledge in both domains to effectively manage structured/unstructured data. I write codes (e.g., Python and R) to extract valuable insights, build robust models (ideas captured in several of my publications/presentations), and automate data processing tasks.

• AI/ML & Large Language Models (LLMs): I utilize these powerful techniques to automate processes, communicate insights effectively (demonstrated through my published work and presentations), and ensure data interoperability and standardization, fostering sustained collaboration across teams.

Beyond my core skills in:

• Machine Learning

• Artificial Intelligence

• Bioinformatics

• Data Modeling

• Data Mining

• Data Visualization

My areas of interest encompass:

• Machine Learning for Healthcare: I'm passionate about developing machine learning models to extract valuable insights from healthcare data. These insights can then be used to improve healthcare outcomes and personalize treatment approaches.

• Real-World Data/Real-World-Evidence (RWD/RWE) for Healthcare: Building effective models relies on high-quality data. I'm particularly interested in creating high-quality healthcare RWD (as defined by the FDA) using multimodal approaches. This involves integrating data from various sources, including electronic health records, patient surveys, X-ray images, and wearable devices.

• Semantic Modeling in Healthcare: Accurately extracting meaning from both structured and unstructured data is crucial for gaining deeper insights. I'm fascinated by the potential of semantic modeling techniques, such as Natural Language Processing (NLP) and Large Language Models (LLMs), to unlock valuable information from text-based and numerical data in the healthcare domain.

Certifications 

• Over 100 licenses and online Certifications from Coursera, Udemy, Edx, Stanford  OpenCourseware, including:    

  • AWS Cloud Practitioner (since 2022)

  • Project Management Professional (PMP; since 2018)

  • Several Udacity Nanodegrees 

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/Azure, where I have used SQL to extract data from databases and applied ETL and ELT (E:Extract, T:Transform, and L:Load) processes to generate and utilize Data Warehouses. Additionally, I have expertise in Anaconda and Google Colab environments for efficient Python/R development and data analysis, with Github integration for version control and collaboration. 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. Moreover, I have skills in semantic modeling and LLM.

Personal Interests 

• Life-long learning (Completed more than 100 online classes); Please check my LinkedIn for details, https://www.linkedin.com/in/sakaravi/details/certifications/ 

• 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, S. Ravichandran; participated and represented the team (Aug 2023)
  Challenge Link: https://precision.fda.gov/challenges/30 

• Prognostic and Predictive Classification Approaches, NIH Long-Covid Computational Challenge, Bethesda, MD, S. Ravichandran (team lead) 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/