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Adjunct Faculty

Data Science related professionals outside of UD.

 

Haider Ali
CEO and Founder, Crowdception Inc.
Assistant Professor, Data Science Institute
haiderali1978@gmail.com
https://crowdception.com/about-us/

Helping society through artificial intelligence technologies

Dr. Haider Ali is an Adjunct Faculty (Assistant Professor) in the Data Science Institute at the University of Delaware. He is also a CEO and Founder of the Crowdception Inc. with over 15 years of extensive professional experience (mainly research and development in Computer Vision, Machine Learning, Applied AI, Robotics and Knowledge Based Systems) in Asia, Europe and the United States of America. Prior to joining the University of Delaware, he was an Assistant Research Professor in the Department of Computer Science at the Johns Hopkins University until April, 2019. He was an Associate Research Scientist at Center for Imaging Science (CIS), JHU from 2017-2018 and a Senior Research Scientist at the Institute of Robotics and Mechatronics (RM) of the German Aerospace Center (DLR), Germany from 2011-2017. He received his Ph.D. in Computer Science at Vienna University of Technology, Austria in 2010.


Moumita Bhattacharya
Senior Data Scientist, Etsy Inc.
moumitab@udel.edu
https://sites.google.com/udel.edu/moumitabhattacharya

Class Imbalance, Big Data, Recommendation Systems, Search Ranking

My research interests lie in developing and applying machine learning methods to solve impactful real-world problems. During my PhD, I developed machine learning models for prediction of health outcomes by analyzing highly heterogeneous structured and unstructured patient data. Such models can assist healthcare providers in clinical decision making by predicting onset of disease or an adverse event such as hospitalization. I have obtained a number of promising results, including predicting the risk of hospitalization among kidney patients, detecting chronic kidney disease severity-levels from standard office visit records, developing a recommendation system to identify co-occurring medical conditions among kidney patients, and identifying several novel risk factors of hypertrophic cardiomyopathy. I am a Senior Data Scientist at Etsy, working in the area of optimization and big data. I focus on developing novel recommendations and search ranking methods to improve product relevance.


Hacene Boukari
Adjunct Faculty, Delaware State University
hboukari@desu.edu
https://cast.desu.edu/about/faculty-profiles/hacene-boukari-phd

Imaging, Spectroscopy, biophysics, Nanotransport

Hacene Boukari, PhD, is Professor of physics at Delaware State University (DSU), Dover, Delaware. He obtained his PhD degree in Chemical Physics from the University of Maryland. His career started while working on a 22-million-dollar NASA project (Zeno Experiment) to build a spectrometer for studying superfluid xenon in microgravity aboard the NASA space-shuttle. Before joining DSU (2010), he held several positions, including Scientist at NIH, Guest Researcher at NIST, and Postdoctoral Fellow at University of Maryland. He worked on diverse projects, including understanding the transport properties of supercritical fluids, determining interactions of biopolymers and cells, and probing diffusion of nanoparticles in biological media. His current work focuses on advancing novel optical and imaging techniques to investigate the behavior of biomacromolecules in cellular systems. He received the researcher award from NASA and the DSU research and service awards.


Karthik Devarajan
Associate Research Professor, Fox Chase Cancer Center, Temple University Health System
karthik.devarajan@fccc.edu
http://www.fccc.edu/research/pid/devarajan/

statistical machine learning, bioinformatics, survival analysis, data mining, high-dimensional data analysis

Dr. Devarajan is an Associate Research Professor in the Department of Biostatistics & Bioinformatics at Fox Chase Cancer Center (FCCC) and an affiliated faculty member in the Center for High-dimensional Statistics at Temple University’s Big Data Institute. His primary research interests encompass statistical machine learning & data science with applications in bioinformatics, neuroscience, medicine & natural language processing. It spans unsupervised and supervised learning, as well as survival analysis, and primarily focuses on the development of statistical and computational approaches to analyze massive data sets generated in these areas. Dr. Devarajan is a member of the Research Review Committee and serves as the Vice Chair of the Data Safety and Monitoring Board at FCCC. Prior to joining FCCC, Dr. Devarajan held research positions at Bristol-Myers Squibb Pharmaceutical Research Institute in Princeton, NJ and the Cancer Bioinformatics Group at AstraZeneca Pharmaceuticals in Boston.


Zugui Zhang
Thomas Jefferson University, Research Assistant Professor
Director of Biostatistics, Christiana Care Health System
zuguiz@udel.edu
https://research.christianacare.org/valueinstitute/people/zugui-zhang-ph-d/

Biostatistics, public health, health economics, bioinformatics, data analysis

As director of biostatistics at the Christiana Care Health System, I carried out study design, methodology research, data analysis, writing drafts as the lead author for peer reviewed research papers, and teaching courses. I published manuscripts in New England Journal of Medicine, Journal of American Medicine, JACC, Circulation, Journal of Clinical Hypertension, The Canadian Journal of Cardiology, among others. My work and papers have been widely reported via media and cited in academic journals. I have worked extensively on several large, international, multi-center, randomized clinical trials, including the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation, the Enoxaparin and Thrombolysis Reperfusion for Acute Myocardial Infarction Treatment, American College of Cardiology Foundation-The Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategies, Systolic Blood Pressure Intervention Trial, and Individual Breastfeeding Support with Incentives for Low-income Mothers.


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The Institute aims to accelerate research in data science, serving as a nucleating effort to catalyze interdisciplinary research collaborations across fields impacting our society.