Research Assistant Intern

HANZHONG ZHENG

**** ****** Square, *** S Bouquet St. Pi*sburgh, PA 15260-9161

haz78@pi*.edu · 412-***-****

h*ps://scholar.google.com/citaMons?hl=en&user=HLKtCOwAAAAJ EDUCATION

University of Pi9sburgh Pi*sburgh, PA

MS student, Computer Science Sep 2021 - Dec 2021

University of Pi9sburgh Pi*sburgh, PA

Phd student, Computer Science Sep 2017- May 2021

Allegheny College Meadville, PA

Bachelor of Science, Computer Science, Minor: Economics, MathemaMcs Sep 2013 -Dec 2016 Cum Laude

TECHNICAL SKILLS

• Related Areas: Time-series data analysis, MulM-modal learning, Machine Learning, Deep Learning, StaMsMcal Analysis, Natural Language Processing, Soaware engineering, IOS applicaMon development

• Deep learning & ML libraries/libraries: Pytorch, Tensorflow, Keras, scikit-learn, Google Cloud Plaform, AWS

• Efficient Programming languages: Python, Java, Matlab, C; Familiar Language: C++, R

• Web programming: html, php, javascript

• Others: REST API, Java Spring Boot, Sql Database, Agile Methodology, DevOps, Git, Airflow, PySpark, Linux/Unix OS WORKING AND INTERNSHIP EXPERIENCE

• Research Intern, University of Pi*sburgh Medical Center, Hillman Cancer Center, “Linking Cell Surface Proteins to Downstream TranscripMonal Programs in Cells using MulM-Task Learning Affinity Regression”, Under the supervision of Dr. Osmanbeyoglu, (Matlab, Python, R). May 2019-Nov 2019 Preprocessing human cell RNA-sequence and ATAC-sequence for medical dataset quality improvement. Building and training affinity regression ML model for analyzing the signaling coupled TF acMvity states of tumor using mulM-task learning technique.

• Research Intern, Embark, PredicMon and Modeling team, remote. May 2020—Sep 2020 Developing variants of recurrent-based deep learning models to extract learning pa*erns using Tensorflow. Establishing the complete ML pipeline to prevent performance degradaMon and ensure conMnuous model training. RESEARCH EXPERIENCE

• Graduate Research Assistant, University of Pi*sburgh, Department of Computer Science, “Tribal: A TriparMte Model for Group Bias AnalyMcs”, Under the supervision of Dr. Rebecca Hwa. May 2018—Sep 2018 Preprocessing the twi*er data and extract the basic NLP informaMon including POS, syntax tree, name enMty extracMon, and network language translaMon.

Building deep models for senMment analysis on twi*er data and clustering models for diving twi*er data into predefined social groups based on LIWC dicMonary using PyTorch and GCP plaform.

• Graduate Research Assistant, University of Pi*sburgh, Department of Computer Science, under the supervision of Dr. Shi-Kuo Chang. May 2018—Sep 2018

Developing facial expression detecMon applicaMon on IOS plaform; architecMng and implemenMng personal health applicaMons on mobile devices.

Preprocessing personal health data and evaluaMng Mme-series modeling algorithms (ARMA, ARIMA, VAR, RNN, etc.) for human behavior tracing on personal health data.

• Graduate Research Assistant, University of Pi*sburgh, Department of Computer Science, “Auto-modularity Enforcement in Java Using Micro-services”, Under the supervision of Dr. Shi-Kuo Chang. May 2021—Sep 2018 Designing, and evaluaMng the soaware pa*erns in Micro-services architecture within medical applicaMon domain. Enforcing the automated modules generaMon using Java Spring boot framework. PROFESSIONAL ACTIVITIES

• Paper presentaMon, “A Mobile Dietary and EmoMonal Diary System for EaMng Disorder Care on the Smart Phone”, DMSVIVA, Redwood City, San Francisco Bay, California, USA. June 29-30, 2018

• Invited Talk, “ICU PaMent Risk Assessment Model”, the 2nd Lushan Scholar Seminar at Hunan University of Technology and Business, Changsha, Hunan, China. December 27-29, 2018

• Paper presentaMon, “Soaware Design Pa*ern Analysis for Micro-services Architecture using Queuing Networks”, SEKE, virtual conference, KSIR Virtual Conference Center, Pi*sburgh, USA. July 1-10, 2021

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