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Lead AI Engineer with 10+ years in Machine Learning & Data Science
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Ph.D. Physicist and Research Scientist with 5+ years of experience building advanced data analysis pipelines, hardware-software automation systems, and mathematical models. Expert in Python and MATLAB, with recent deep-dive certifications across Deep Learning, Generative AI architecture, and AI Agents (RAG/LangChain). Proven track record of translating complex scientific data into actionable insights and high-impact publications. Seeking to leverage strong algorithmic thinking and statistical modeling expertise to build scalable Machine Learning systems.
University of Hyderabad
PhD Physics · Physics
August 1, 2013 – June 30, 2021
University of Hyderabad
M. Sc. Physics · Physics
August 1, 2011 – June 30, 2013
University of Calicut
B. Sc. Physics · Physics
August 1, 2008 – June 30, 2011
Jeevalaya Institute, Bangalore
Diploma- Philosophy · Philosophy
August 1, 2006 – June 30, 2008
University of Notre Dame
Research Scientist / Postdoc
November 1, 2024 – May 1, 2026
USA
St. Joseph's College, Devagiri & Mary Matha College, Mananthavady
Teaching and Academic experience
July 1, 2023 – November 1, 2024
India
University of Notre Dame
Research Scientist / Postdoc
August 1, 2021 – June 1, 2023
USA
St. Joseph's College, Devagiri & Mary Matha College, Mananthavady
Teaching and Academic experience
October 1, 2020 – June 1, 2021
India
University of Hyderabad
Research fellow / Project assistant
August 1, 2013 – September 1, 2020
India
Generative AI Engineering and Fine-Tuning Transformers
IBM, Coursera
June 1, 2026 – Present
Gen AI Foundational Models for NLP & Language Understanding
IBM
June 1, 2026 – Present
Fundamentals of AI Agents Using RAG and LangChain
IBM, Coursera
June 1, 2026 – Present
Machine learning with Python
IBM, Coursera
May 1, 2026 – Present
Introduction to Deep Learning & Neural Networks with Keras
IBM, Coursera
May 1, 2026 – Present
Generative AI and LLMs: Architecture and Data Preparation
IBM, Coursera
May 1, 2026 – Present
Peptide Sequencing With Single Acid Resolution Using a Sub-Nanometer Diameter Pore
Advanced Functional Materials
January 1, 2026 – Present
Data Science with Python
E & ICT Academy, IIT Kanpur
March 1, 2022 – Present
Electron-electron interaction dominated resistivity minimum in quasi-continuous Ag nanocluster films
AIP Advances
December 16, 2020 – Present
Tunable electron transport with intergranular separation in FePt-C nanogranular films
Materials Research Express
April 1, 2020 – Present
JRF + NET
CSIR, India
March 1, 2013 – Present
Cultural Fit Analysis
The candidate's background in academic research and teaching, coupled with recent certifications in cutting-edge AI technologies, suggests a strong drive for continuous learning and intellectual curiosity. The experience in mentoring projects indicates a collaborative spirit. The transition from pure physics research to applied AI demonstrates adaptability and a willingness to embrace new challenges, which are positive indicators for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate's experience in research and teaching suggests strong analytical, problem-solving, and mentoring skills. The ability to translate complex scientific data into actionable insights is valuable. However, direct experience in a fast-paced software engineering product development environment is not explicitly detailed, which might impact operational fit for a pure software engineering role, though it aligns well with research-heavy AI roles.