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Senior Research Engineer, Language Technologies Institute at Carnegie Mellon University | Machine Learning | NLProc | AI
I recently worked with the Machine Learning Department at CMU. Previously developed and re-engineered Artificial Intelligence (AI) systems. Agnostic to programming environments and technologies. MS in CS from Northeastern University, Boston (AI specialization). Masters (M. Tech.) in Mathematical modeling and Statistical simulation from the Centre for Modeling and Simulation, University of Pune, India. Proficient: Java, Python, NumPy, SAS, R, MATLAB, Hadoop, Racket, Linux Shell Script. Familiar: TensorFlow, PyTorch, scikit-learn, MapReduce, Protocol Buffers, Docker, LaTeX.
Northeastern University
Master of Science - MS, Artificial Intelligence, Computer Science
N/A – Present
Savitribai Phule Pune University
Master of Technology - MTech, Data Science, Mathematics and Statistics, Math. Modeling
N/A – Present
Symbiosis Centre For Management and Human Resource Development
Post Graduate Diploma in Business Analytics, Business Analytics
N/A – Present
Centre for Development of Advanced Computing (C-DAC)
Post Graduate Diploma in Advanced Software Technology, Computer Science, AI
N/A – Present
Amity University
Bachelor of Computer Applications, Computer Science
N/A – Present
Carnegie Mellon University
Senior Engineer, Language Technologies Institute - ML, NLProc, AI
March 1, 2019 – Present
Greater Pittsburgh Region
Carnegie Mellon University
ML Research Engineer, Machine Learning Department
May 1, 2017 – March 1, 2019
Greater Pittsburgh Region
Northeastern University
Data Scientist - Statistical Modeling, Causal Inference, Healthcare Research
April 1, 2014 – December 1, 2015
Greater Boston
Northeastern University College of Computer and Information Science
Graduate Student - AI Specialization - MS in Computer Science
September 1, 2013 – December 1, 2016
Greater Boston
Symbiosis Centre For Management and Human Resource Development
Visiting Faculty - Applied Statistics, Data Analytics
January 1, 2013 – April 1, 2013
Pune/Pimpri-Chinchwad Area
SAS Research and Development, India
ML Intern - Advanced Analytics Lab., Stochastic-search Optimization, Risk-based Asset Allocation
December 1, 2011 – June 1, 2012
Pune/Pimpri-Chinchwad Area
Centre for Modeling and Simulation, Savitribai Phule Pune University
Graduate Student - M.Tech., Mathematical Modeling, Statistical Simulations
July 1, 2010 – May 1, 2012
Pune/Pimpri-Chinchwad Area
C-DAC (Formerly NCST)
AI Engineer, R&D - Knowledge-based AI, Data Mining, Relation Extraction
October 1, 2007 – July 1, 2010
Mumbai Metropolitan Region
IRIS Business Services Limited
Software Engineer - Personal Finances, Loans, Equities
August 1, 2007 – September 1, 2007
Mumbai Metropolitan Region
NTPC Limited
Technology Intern - Resource Allocation, Heuristics-based Optimization
March 1, 2006 – May 1, 2006
Noida, Uttar Pradesh, India
Triplebyte Certified Engineering Certificate
Triplebyte
June 24, 2026 – Present
Gaussian Process and Uncertainty Quantification Summer School
The University of Sheffield
June 24, 2026 – Present
Machine Learning Summer School
The University of Texas at Austin
June 24, 2026 – Present
Statistical Modeling for Data Analysis
Indian Institute of Technology, Kharagpur
June 24, 2026 – Present
Stanford Online | OpenEdX | Statistical Learning
Stanford University
June 24, 2026 – Present
Coursera | Computing for Data Analysis
The Johns Hopkins University
June 24, 2026 – Present
SAS Certified Base SAS Programmer for SAS 9
SAS
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background includes work at prestigious academic institutions (Carnegie Mellon, Northeastern) and research organizations (C-DAC, SAS R&D), indicating a strong fit for a culture that values intellectual curiosity, continuous learning, and rigorous analytical approaches. Their involvement in various research projects and teaching roles suggests a collaborative and knowledge-sharing mindset. The breadth of their education and experience across different domains (healthcare, finance, language technologies) demonstrates adaptability and a broad perspective.
Soft Skills & Operational Fit
The candidate's diverse experience across research, academia, and industry, including teaching roles, suggests strong communication and collaboration skills. Their involvement in complex, multi-modal projects indicates an ability to handle challenging problems and adapt to different operational environments. The long tenure at Carnegie Mellon University points to stability and dedication.