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AI/ML Researcher at UT Austin
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Creative and self-motivated AI/ML researcher with experience in organizing and leading technical teams. Thrives in group environments and enjoys thinking strategically to find pragmatic solutions to domain-specific problems. Possesses applied knowledge in deep learning (generative models, NLP, imitation learning), data mining (topic modeling, network science), and cybersecurity (AI red teaming, countering AI misuse, network security). Adept at bridging theory and practice and in communicating results to stakeholders effectively.
Brown University
Doctor of Philosophy (Ph.D.), Applied Mathematics
January 1, 2004 – January 1, 2009
Worcester Polytechnic Institute
Bachelor of Science (BS), Mathematics
January 1, 2000 – January 1, 2004
The University of Texas at Austin
Research Scientist, Applied Research Laboratories
July 1, 2025 – Present
The University of Texas at Austin
Research Associate, Applied Research Laboratories
November 1, 2015 – July 1, 2025
The University of Texas at Austin
Research Fellow, Statistics and Data Sciences, Meyers Lab
February 1, 2014 – November 1, 2015
The University of Texas at Austin
Visiting Scholar, Mathematics
September 1, 2013 – January 1, 2014
The University of Texas at Austin
Postdoctoral Fellow and Instructor, Mathematics, ICES
January 1, 2010 – August 1, 2013
Duke University
Visiting Scholar
September 1, 2009 – December 1, 2009
Durham, NC
Statistical and Applied Mathematical Sciences Institute (SAMSI)
Researcher
September 1, 2009 – December 1, 2009
Research Triangle Park, NC
Cultural Fit Analysis
The candidate's extensive academic and research background, particularly within a university setting, suggests a strong fit for environments that value deep analytical thinking, research, and continuous learning. Their experience with government-sponsored projects indicates an ability to work within structured frameworks and manage complex deliverables. However, the transition from a purely academic/research environment to a corporate data analyst role might require adaptation to different operational rhythms and business objectives. The target role 'Data Analyst' might be a slight mismatch for their extensive research and PI experience, which leans more towards Data Scientist or Applied Research Scientist.
Soft Skills & Operational Fit
The candidate demonstrates strong project management, leadership, and communication skills through their PI and project manager roles. Their experience in establishing collaborations and organizing research meetings suggests good teamwork and initiative. The academic background and research focus indicate a strong analytical mindset and problem-solving abilities, which are critical for a senior data analyst role.