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AI Engineer with 10+ years in Machine Learning & PCB Design Automation
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine learning and AI specialist with nearly nine years of experience developing and deploying advanced algorithms to PCB and Electronic Design Automation (EDA). Proven track record of shaping research strategy, securing innovation funding, establishing academic partnerships, and leading projects from early research through production. Previously held research appointments at KTH Royal Institute of Technology, ETH Zurich, and MIT, providing a strong foundation in optimization, applied mathematics and statistical learning methods.
KTH Royal Institute of Technology
Licentiate of Technology · Automatic Control
August 1, 2011 – June 30, 2011
KTH Royal Institute of Technology
Doctor of Philosophy · Automatic Control
August 1, 2008 – June 30, 2014
KTH Royal Institute of Technology
Master of Science · Electrical Engineering
August 1, 2008 – June 30, 2008
Rashtreeya Vidyalaya College of Engineering
Bachelor of Engineering · Telecommunications
August 1, 2004 – June 30, 2004
Zuken Limited
Senior Machine Learning Engineering Consultant – AI Research Lead
October 1, 2017 – Present
Bath, England, United Kingdom
ETH Zurich
Postdoctoral Researcher, Automatic Control Laboratory, Department of Information Technology and Electrical Engineering (D-ITET)
January 1, 2015 – January 1, 2017
Zürich, canton of Zürich, Switzerland
KTH Royal Institute of Technology
Postdoctoral Researcher, Automatic Control Laboratory, School of Electrical Engineering
June 1, 2014 – December 1, 2014
Stockholm, Stockholm County, Sweden
Lund University
Visiting Researcher, Lund Center for Control of Complex Engineering Systems (LCCC)
October 1, 2012 – October 1, 2012
Lund, Skåne County, Sweden
Massachusetts Institute of Technology (MIT)
Visiting Researcher, Laboratory for Information and Decision Systems (LIDS)
January 1, 2012 – May 1, 2012
Cambridge, Massachusetts, United States
KTH Royal Institute of Technology
Doctoral Student Researcher, Automatic Control Laboratory, School of Electrical Engineering
August 1, 2008 – April 1, 2014
Stockholm, Stockholm County, Sweden
KTH Royal Institute of Technology
Student Researcher, Automatic Control Lab, School of Electrical Engineering
February 1, 2008 – July 1, 2008
Stockholm, Stockholm County, Sweden
KTH Royal Institute of Technology
Student Researcher, ECS Lab, School of Information and Communication Technology
February 1, 2007 – December 1, 2007
Stockholm, Stockholm County, Sweden
Honeywell Technology Solutions Laboratory
Engineer, Aerospace Division
August 1, 2004 – August 1, 2005
Bengaluru, Karnataka, India
Center for Artificial Intelligence and Robotics
Undergraduate student internship
February 1, 2004 – May 1, 2004
Bengaluru, Karnataka, India
O. Hugo Schuck Best Paper Award for Theory
American Control Conference (ACC)
January 1, 2018 – Present
RaMSiS Scholarship
KTH
January 1, 2006 – Present
Award, R.V.College of Engineering
R.V.College of Engineering
January 1, 2003 – Present
Singapore Airlines (SIA) Youth Scholarship
Singapore Airlines
January 1, 2000 – Present
Presidential Honours, Government of India
Government of India
January 1, 1999 – Present
Cultural Fit Analysis
The candidate's extensive academic background and experience across multiple international institutions (KTH, ETH Zurich, MIT, Lund University) demonstrate adaptability and a global perspective. Their involvement in strategic research collaborations and supervision of diverse student projects indicates a collaborative and knowledge-sharing mindset. The breadth of their research interests, from urban traffic control to credit card fraud detection and PCB design, suggests intellectual curiosity and a willingness to tackle varied challenges, aligning well with an innovative and research-driven culture.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentorship, and strategic planning skills through their role as AI Research Lead, establishing teams and academic collaborations. Their extensive research background indicates strong problem-solving, critical thinking, and independent work capabilities. The ability to translate state-of-the-art research into product roadmaps highlights a practical, results-oriented approach. The introduction of MLTRLs suggests a structured and process-oriented mindset for project evaluation and delivery.