cv2023

cv.txt

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+C.J. DUAN
+Data Scientist. Ph.D
+@Data.Scientist@dulun.com ♂phone757-742-3896 ♂¶ap-¶arkerDRC Lab, Virginia /gl⌢bewww.dulun.com
+/linkedincj-duan-3ab27a191 /githubhublun
+EXPERIENCE
+Data Scientist (contract)
+Fortune 500 Company (CPG), Research Data Science
+Ὄ52021 - 7.2022 ♂¶ap-¶arkerRemote
+•Input Data (Snowflake on AWS): Time-series of weekly sales data and
+weekly media (advertising) spend and GRP (Impression)s
+•Model: State-Space Bayesian Media Mix Model using R and RStan
+•Output Results: ROI effectiveness in terms of MC (media contribution)
+over MS (media spend)
+Chief Research Data Scientist
+DRC Lab @ Dulun Research & Consulting
+Ὄ52016 - Now ♂¶ap-¶arkerFreelance
+Completed Projects :
+•(2020-2021) Algorithmic Trading Robot, coded in Python, digests recent
+(commodity future) prices and execute order composition and routing
+automatically.
+FFT, Risk Control, Trading
+•(2016-2017) Develop the best distribution routing model, which saved
+an Alabama flower-growing farmer thousands fuel dollars on monthly
+basis.
+Transportation Scheduling, Constraint Programming, OR
+Replication & Learning Projects (2016 - now) :
+•Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations
+associated with fitness (Obermeyer, et. al. , 2022, Science )
+Bayesian multinomial logistic regression model using Pyro
+•Survival analysis in Stan (Filipe S. Dias, 2022, Web Blog )
+Survival Analysis
+•Deep learning recommendation model for personalization and
+recommendation systems (Naumov, et. al. 2019, ArXiv )
+TorchRec
+•Bayesian Inference for a Generative Model of Transcriptome Pro-
+files from Single-cell RNA Sequencing (Lopez, et. al. , 2018, Na-
+ture Methods )
+Variational Inference for Generative Model of scRNA seq using PyTorch and Pyro
+•Bayesian aggregation of average data: An application in drug de-
+velopment (Weber, et. al. , 2018, Annals of Applied Statistics )
+Pharmacometric Model using RStan
+Assistant Professor of Quantitative Methods
+Troy University
+Ὄ5March 2009 – May 2017 ♂¶ap-¶arkerTroy, Al
+Research Projects :
+•Research Paper (2021): Team Contingent or Sport Native? A Bayesian
+Analysis of Home Field Advantage,
+•Research Paper (2021): Exposing model bias in machine learning revisit-
+ing the boy who cried wolf in the context of phishing detectionWORK PHILOSOPHY
+“Modeling in the sciences is in fact al-
+most always generative modeling”
+Kingma and Welling (2019)
+MOST PROUD OF
+/gavelHidden Markov Model (HMM)
+state space, transition, and emission
+/binocularsMarkov Decision Process (MDP)
+states, actions, rewards
+/cogsPyro & PyTorch
+SVI (stochastic variaitonal inference) based
+Variational Autoencoder
+⌛Multi-Arm Bandit (MAB) and RL
+𝜋policy mapping actions to contexts
+/meetupMedia Mix Modeling
+ROAS, mROAS, Adstock, Hill function
+ἲ1A/B Testing and MCI
+multiple causal (treatment) inference
+ὖELDA / Mixture / Clustering
+Latent Dirichlet Allocation, Topic Models
+Ὠ0Stan & Bayesian Modeling
+data, parameters, model, and prediction
+Ἴ6Servire Est Vivere
+helping Braydon Farm LLC in Alabama opti-
+mize their daily flower delivery routes using
+Transportation Model
+EDUCATION
+Ph.D in Industrial Management
+Clemson University
+Ὄ52000 – 2007
+REMARKS
+"...On behalf of my wife and I, we would like to sin-
+cerely thank Dr. Duan, Mrs. Amy Hu, and you for the
+time you spent developing a distribution plan for our
+new floral operation. We have incorporated it into our
+operation and it appears to have significantly reduced
+our travel time and expenses in distribution our prod-
+ucts to the Marvin Stores chain. Hopefully this will bePUBLICATIONS
+/file-altJournal Articles
+•(Chaojie), D. C. J., & Chakravarty, A. (2021). Team contingent
+or sport native? a bayesian analysis of home field advantage in
+professional soccer. Journal of Business Analytics ,4(1), 67–75.
+doi:10.1080/2573234X.2020.1854625
+•(Chaojie), D. C., & Gaurav, A. (2021). Exposing model bias in ma-
+chine learning revisiting the boy who cried wolf in the context
+of phishing detection. Journal of Business Analytics ,4(2), 171–
+178. doi:10.1080/2573234X.2021.1934128. eprint: https:
+/ /doi.org/10.1080/2573234X.2021.1934128
+•Duan, C. [C.J.], & Pierce, G. S. (2017). Starting operations man-
+agement with a ‘Big Bang’: Using sitcom to introduce OM con-
+cepts to students. Operations Management Education Review ,11,
+115–122.
+•Duan, C. [CJ], Hu, J., Garrott, S., et al. (2016). Using excel solver
+to solve Braydon Farms’ truck routing problem: A case study.
+South Asian Journal of Management Sciences (SAJMS) ,10(1), 38–
+47. doi:10.21621/sajms.2016101.04
+•Duan, C. [Chaojie], Grover, V., Roberts, N., & Balakrishnan, N. (
+(2014). Firm valuation effects of the decision to adopt relation-
+ally governed business process outsourcing arrangements. In-
+ternational Journal of Production Research ,52(15), 4673–4694.
+doi:10.1080/00207543.2014.884289. eprint: https:/ /doi.org/
+10.1080/00207543.2014.884289
+•Kronenburg, M. A., Shetterly, D. R., Duan, C., Krishnamoorthy,
+A., & Loutzenhiser, K. (2013c). The impact of contract design
+on contract performance satisfaction. International Journal of
+Management Research and Reviews ,3(4), 2673.
+•Duan, C. [Chaojie], Grover, V., & Balakrishnan, N. ( (2009). Busi-
+ness process outsourcing: An event study on the nature of pro-
+cesses and firm valuation. European Journal of Information Sys-
+tems ,18(5), 442–457. doi:10.1057/ejis.2009.38
+/usersConference Proceedings
+•Duan, C. [C.J.]. (2013). Retrieving hypothesis parameters from
+real life events. In The 43rdsoutheast decison sciences institute
+conference proceedings . SE DSI.
+•Kronenburg, M. A., Shetterly, D. R., Duan, C., Krishnamoorthy,
+A., & Loutzenhiser, K. (2013a). Public management skills needed
+in contract development. In The southeastern conference for pub-
+lic administration . SECoPA.
+•Kronenburg, M. A., Shetterly, D. R., Duan, C., Krishnamoorthy,
+A., & Loutzenhiser, K. (2013b). Public management skills needed
+in contract development. In The southeastern conference for pub-
+lic administration . SECoPA.
+•Kronenburg, M. A., Shetterly, D. R., Duan, C., Krishnamoorthy,
+A., & Loutzenhiser, K. (2012). The impact of contract design on
+contractor performance - a second look. In 5thinternational pub-
+lic procurement conference . IPPC.
+•Duan, C. [C.J.]. (2004). Teams in TQM: An knowledge based
+view. In The 35thdsi.
+•Duan, C. [C.J.]. (2001). One machine scheduling of jobs to min-
+imize total weighted tardiness. In The 37thsoutheast informs . SE
+INFORMS.an on-going study and we will be able to “tweak” or al-
+ter the system based on your recommendations as our
+business grows..."
+Stephen (Brad) Bradshaw Garrott
+Owner, Braydon Farms, 2015
+"...I work on projects focused on educating high school
+students in Mississippi in entrepreneurship opportu-
+nities and what resources are available to start-ups. I
+use Excel frequently and I am thankful for being familiar
+with excel formula’s like vlookup and IF. ... I wish there
+was an Operations Management class because that
+was my favorite in undergrad and where I find myself
+passionate. I am considering entering the workforce
+aiming for an Operations Management position based
+on my success in your class and how much I enjoyed it.
+I think your class is very important and I’m glad I had
+the opportunity to learn from you. I am also open to
+entrepreneurship opportunities as I am so active in the
+entrepreneurship ..."
+Russell, QM 3345, 2016

prompt_cv.ipynb

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+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## [ChatGPT Prompt Engineering for Developers](https://learn.deeplearning.ai/chatgpt-prompt-eng/)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from auth import API_KEY\n",
+    "import openai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai.api_key = API_KEY"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_completion(prompt, model='gpt-3.5-turbo'):\n",
+    "    messages = [{'role':'user', 'content': prompt}]\n",
+    "    response = openai.ChatCompletion.create(\n",
+    "        model=model,\n",
+    "        messages = messages,\n",
+    "        temperature = 0, # this is the degree of randomness of the model's output\n",
+    "    )\n",
+    "    return response.choices[0].message['content']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text = f\"\"\"\n",
+    "You should express what you want a model to do by \\ \n",
+    "providing instructions that are as clear and \\ \n",
+    "specific as you can possibly make them. \\ \n",
+    "This will guide the model towards the desired output, \\ \n",
+    "and reduce the chances of receiving irrelevant \\ \n",
+    "or incorrect responses. Don't confuse writing a \\ \n",
+    "clear prompt with writing a short prompt. \\ \n",
+    "In many cases, longer prompts provide more clarity \\ \n",
+    "and context for the model, which can lead to \\ \n",
+    "more detailed and relevant outputs.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prompt = f\"\"\"\n",
+    "Summarize the text delimited by triple backticks \\ \n",
+    "into a single sentence.\n",
+    "```{text}```\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Clear and specific instructions should be provided to guide a model towards the desired output, and longer prompts can provide more clarity and context for the model, leading to more detailed and relevant outputs.\n"
+     ]
+    }
+   ],
+   "source": [
+    "response = get_completion(prompt)\n",
+    "print(response)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}