Innovator, Data Scientist, and AI enthusiast. Creating smarter solutions for the world through Machine Learning and AI. Two patents in Big Data and ML for the agriculture sector. Let's make the world a better place!
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I'm a generalist in data science that is striving to accelerate Digital transformation through building an effective data science to business value generation workstream.
Washington University in St. Louis
Doctor of Philosophy (Ph.D.)
January 1, 2009 – January 1, 2014
Tsinghua University
Bachelor's degree, Electrical and Electronics Engineering
January 1, 2005 – January 1, 2009
The Hartford
Director, AI Corporate Functions
January 1, 2026 – Present
The Hartford
Director, GenAI Solution Delivery
March 1, 2025 – Present
Object Computing, Inc.
Distinguished Scientist
January 1, 2024 – March 1, 2025
Object Computing, Inc.
Director of AI/ML and Data Insights
July 1, 2023 – March 1, 2025
Object Computing, Inc.
Principal Data Scientist
January 1, 2023 – July 1, 2023
Object Computing, Inc.
Machine Learning Strategy Lead
November 1, 2021 – July 1, 2023
The Climate Corporation
Lead Data Scientist-Machine Learning
November 1, 2019 – October 1, 2021
The Climate Corporation
Senior Data Scientist-Machine Learning
September 1, 2017 – October 1, 2019
The Climate Corporation
Imaging Scientist
September 1, 2016 – August 1, 2017
Monsanto Company
Imaging Scientist
January 1, 2015 – September 1, 2016
Chesterfield, Missouri
Elekta
Research Intern
October 1, 2014 – December 1, 2014
Greater St. Louis Area
Washington University in St. Louis
Graduate Research Assistant
August 1, 2009 – August 1, 2014
Greater St. Louis Area
Tsinghua University
Student
August 1, 2005 – July 1, 2009
Image based deep sequence modeling using LSTM
May 1, 2018 – August 1, 2018
Using LSTM in combination with CNN for end-to-end deep image sequence model.
Disease Generative Model
September 1, 2017 – December 1, 2017
Build on top of generative adversarial networks (GAN) to estimate diverse disease imagery distributions.
Deep Learning based Crop Disease Detection
November 1, 2016 – April 1, 2017
A combination of fast R-CNN like model with HOG feature extraction from computer vision can achieve near real time disease detection method. That's less than 1 second run time per image with 1600 by 1200 pixels.
Ensemble Prediction using Deep Learning
January 1, 2015 – October 1, 2016
Integrate large scale imaging and environment data and built ensemble prediction models using deep learning algorithms for better product placement.
Implementation of Statistical Image Reconstruction for Better Segmentation
October 1, 2014 – Present
Using MATLAB, implemented statistic reconstruction algorithms and applied on simulated data as well as patient data, in order to get a better segmentation results compared to conventional analytical algorithm method.
4D PET/CT reconstruction
April 1, 2013 – Present
Develop novel 4D PET/CT reconstruction algorithm that can simultaneously reconstruct images corresponding to different time frames, and may have the advantage of lowering the dose or radiation exposed to patients.
Sparse coding in neuron networks
February 1, 2013 – May 1, 2013
Lead the team of developing a novel approach for dynamic sparse coding in term of short term firing rates, particularly on visual cortex and olfactory system of insects.
Dual-energy X-ray CT imaging
September 1, 2011 – Present
Develop and optimize statistical iterative cross-section mapping algorithms and evaluate performance of CT cross-section mapping techniques for Proton therapy dose planning as well as assess the potential clinical impact of accurate radiological quantity mapping.
Analysis of multiplexed SERS microscopy of Ag nanocubes using alternating minimization (AM) algorithm
April 1, 2011 – December 1, 2013
Design a robust and accurate multiplex spectral fitting method using an AM algorithm to extract individual constituent Raman spectra with very small overall fitting error.
Computation of Berger-Tung bounds for lossy distributed source coding
October 1, 2010 – August 1, 2011
Developed an optimization and computational approach for characterizing the inner and outer bounds for the achievable rate regions for Berger-Tung coding.
Design of Backplane Interface (BPIF) model
October 1, 2010 – December 1, 2010
Lead a team to design BPIF model for the Front Board using PCI Express technology.
Analysis on Impulse Characteristics of Independence Grounding Devices
April 1, 2008 – June 1, 2009
Developed software for simulating impulse characteristics of grounding devices.
Academy Accreditation - Generative AI Fundamentals
Databricks
June 24, 2026 – Present
Graduate Certificate in Imaging Science & Engineering
Washington University in St. Louis
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience in research and development, coupled with leadership roles in diverse industries, suggests a strong adaptability and a proactive approach to problem-solving. The variety of projects, from academic research to industry applications in AI/ML, indicates a broad interest and ability to work in different technical and business contexts. The progression through various leadership roles at Object Computing, Inc. and The Climate Corporation demonstrates a commitment to growth and taking on increasing responsibilities. The target role of 'Data Analyst' seems to be a significant step down from the candidate's current and past leadership roles in AI/ML and Data Science, which might indicate a potential mismatch in expectations or a desire for a more focused, hands-on role. However, the core skills in data analysis, modeling, and interpretation are strongly present.
Soft Skills & Operational Fit
The candidate's experience as a Director and Lead in various organizations suggests strong leadership, strategic thinking, and team management skills. The descriptions of leading teams, driving strategy, and collaborating with sales indicate good communication and operational fit for roles requiring cross-functional interaction and project ownership. The focus on 'platform thinking' and 'framework thinking' implies an understanding of scalable and reusable solutions.