phd data science aim

AIM welcomes second cohort of PhD in Data Science students

THE Asian Institute of Management (AIM), through its Aboitiz School of Innovation, Technology and Entrepreneurship (Asite), officially welcomed the second cohort of its PhD in Data Science program through a virtual convocation held on Sept. 29, 2021.

The PhD in Data Science program of AIM is the first of its kind in the Philippines and among only a handful in Asia. It is focused on pushing the boundaries of data science that includes, among others, artificial intelligence, network science and complex systems.

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Aboitiz and AIM’s pioneering data science program welcomes biggest class since launch

The Asian Institute of Management (AIM) Aboitiz School of Innovation, Technology and Entrepreneurship (ASITE)  — the first graduate data science degree program in the Philippines — officially welcomed the 84 incoming students of its Master of Data Science (MSDS) Class of 2022 through a virtual convocation event last April 19. This is the pioneering program’s largest number of enrollees since ASITE was established through a USD10 million grant from the Aboitiz Group.

In his inspirational message during the program, Aboitiz Group President and CEO Sabin M. Aboitiz  explained that the underlying reasons for the company’s strong advocacy of data science learning and development in the country are deeply rooted in shared value creation.

“Everything we do, whether collectively as a business or as individual members of an organization, is guided by our Group Purpose and Brand Promise—to drive change for a better world by advancing business and communities,” he shared. “Achieving that requires taking advantage of foresight, especially in times like these when everything has been upended. More than ever, the world needs data scientists who will be able to help us navigate through ambiguity and uncertainty.”

In addition to the MSDS program, AIM’s Aboitiz-supported school also offers Masters in Entrepreneurship (ME), Masters of Science in Innovation and Business (MSIB), and the Philippines’ first PhD in Data Science.

 AIM President and Dean Dr. Jikyeong Kang described how ASITE’s MSDS program sets itself apart from other schools, primarily since the institution once known as “the Harvard of Asia” has always been recognized for innovation.

“We want people to be as solidly grounded in data science, but also who can speak the language of business, who can actually sit down with the business leaders, CEOs, and boardroom and discuss issues that are relevant and critical to business decision making,” she said.

Nearly a third of the program’s curriculum is made up of business and management courses, and to Dr. Kang’s knowledge no data science program is designed the same way.

Likewise, data science education in an institution like AIM means students become more well-rounded and adaptable, with the incoming class being composed of people from diverse backgrounds, professions, and experiences that span the Philippines, Hong Kong, China, UK, and Canada. More notably, the batch is made up of 42% female students — significantly higher than the global average of female practitioners in the field of data science, which hovers between 15 to 22%.

Meanwhile, Dr. Chris Monterola, ASITE Head and Aboitiz Chair in Data Science, highlighted to students the enormous potential that data science and innovation can bring to create a better world.

“We are a community of innovators and entrepreneurs, and in this era of Industry 4.0, the most valuable companies in the world is a combination of a mastery of data and an entrepreneurial mindset. Through technology and entrepreneurship, we hope that we can get back, innovate, and build a better society,” he explained.

Since 2018, ASITE has been building the next generation of world-class data scientists in response to the demand for skills and talent in this field. From there, the school quickly rose as one of the region’s premier academic institutions for data science and innovation. By June 2021, the school is expected to have 150 graduates working in many leadership roles in the country and in the region—an impressive feat for such a nascent program.

Mr. Aboitiz commended the MSDS students for taking this bold step towards carving new possibilities not just for themselves, but also for those who may not have the opportunity yet.

“Our hope is that whichever path you follow, it will be one that delivers solutions that address the challenges humanity faces, especially for our most vulnerable communities. We have only begun to scratch the surface of how data science can change the world for the better, so I encourage you to keep experimenting and learning,“ he concluded. #

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As the world finds itself in the midst of the 4 th  Industrial Revolution, technology is evolving faster than ever, and with it, a staggering volume of data is generated each day. This explosion of data has given rise to the huge demand for Data Scientists to extract knowledge and provide insights not only to make fast and robust decisions about the present but also to better prepare for the future.

Spurred by these needs, the Asian Institute of Management (AIM), following its hugely successful MSc in Data Science program, which was launched 2 ½ years ago, is launching a PhD in Data Science program, a first in the Philippines and one of only a handful in Asia. AIM’s new PhD program aims to make original and novel contributions to data science by leveraging data systems, analyzing trends, and building models in a cross-disciplinary and ethically responsible manner for industry, society, and academia.

“This PhD program is specifically designed to push the boundaries of knowledge across multiple disciplines through data. AIM will continue to maintain our leading position and competitive advantage in Data Science, complexity science, and artificial intelligence research,” said AIM’s President and Dean Jikyeong Kang.

The PhD program builds on the success of AIM’s Master of Science in Data Science degree program, which is currently  ranked third in Far East Asia ahead of similar offerings in Japan,   Singapore, and South Korea , according to the international university ranking agency Eduniversal. “We want our graduates to be able to lead at the frontlines and rise to the new challenges of a world powered and governed by data,” said Associate Professor Erika Legara, AIM’s MSc in Data Science Academic Program Director. “AIM’s PhD in Data Science program will specifically stress the creation of new knowledge, insights, and methods with and from data. The program will train individuals to conduct comprehensive and extensive research on cross- disciplinary topics,” she added.

Students who take on AIM’s PhD in Data Science program’s rigorous curriculum will be under the guidance of the Institute’s internationally recognized faculty of data scientists. They will also have access to AIM’s 1.2-petaflop computing facility, one of the most powerful and sophisticated AI supercomputing platforms in Southeast Asia.

All PhD students will be required to serve as instructors or teaching assistants at AIM or elsewhere, allowing them to share the results of their research while giving them leverage, should they wish to pursue academic careers. Upon graduation, graduates are poised to become key players in ethical and responsive Data Science research and policy making, be it in the academia or other public/private sector. They can be expected to lead businesses and societies in a wide range of fields, including finance, economics, urban planning, transportation, medicine and healthcare, and business logistics and supply.

Graduates will be equipped with practical skills on top of a firm understanding of the latest theories and concepts: among the requirements for graduation is the completion of at least three R&D projects, including two first-authored publications in reputable indexed journals and one project that addresses the actual needs of a government, industry, or international organization.

“Most of the top data scientists in big tech firms like Amazon, Google, and Microsoft, and in banks, such as JP Morgan, have PhDs. This makes sense since data scientists are often applied researchers that can drive innovation through data and advanced analytics. Indeed, a PhD in Data Science is one of the few doctoral programs that are exceptionally useful in both academia and industry,” said Professor Christopher Monterola, who also heads the Aboitiz School of Innovation, Technology, and Entrepreneurship and ACCeSs (Analytics, Computing and Complex Systems) Laboratory at AIM.

For more details about the AIM PhD in Data Science program, including scholarship information, please email  [email protected].

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Data Science Is the Career of the Future. Here Are 5 Schools That Offer Courses Related to It

It’s no secret that the demand for data scientists and analysts has been growing exponentially over the last few years. According to Glassdoor , data scientist was the number one job in the US over the last four years. In the Philippines, Glassdoor estimates that the average annual salary for a data scientist is around P432,000, and many companies are now actively recruiting people with that specific job title.   

However, a study last year by the Philippine Institute for Developing Studies (PIDS) noted that higher education institutions are not producing enough graduates to fill the steadily rising need for professionals in the field. According to the report, in 2019, data science and analytics (DSA)-related programs produced 176,597 professionals, but only 38 percent or about 62,583 workers were deemed ready to shift to the more in-demand and specialized DSA field. That year, there was a total of 81,078 DSA job roles that needed to be filled.

“Big data is now considered an economic resource, Rudy H. Tan, Ph.D.  and Lourdes A. Tan, M Stat writes in their paper entitled Need For B.S. Data Science Degree Program In The Philippines . “According to a special report published by the Economist , it is ‘becoming the new raw material of business: an economic input almost on par with capital.’ Data science is the new discipline that can exploit big data for its economic value to transform information into insights needed to create better services and new products in the 21st century and beyond.”

Schools and universities have begun to answer the call to equip students with the right knowledge and skills to prepare them for a world where Big Data is king. If you’re interested, these schools are already offering programs focused on and related to Data Science and Analytics programs in the Philippines: 

1| Asian Institute of Management (AIM)

AIM was the first to offer a Masters degree in Data Science in the country. In 2018 and 2019, the program placed third in Eduniversal’s ranking of the best masters in data analytics in the Far East, besting similar programs in Japan, Singapore, South Korea, and Malaysia. 

“Data science is the fastest-growing and most sought-after specialization worldwide,” said AIM President and Dean Jikyeong Kang during the launch of the MSDS program in 2017. “The Master of Science in Data Science program is our most thought-through, most intelligent, and most appropriate response to prepare for the changes and challenges digitalization throws at us.”

2| University of the Philippines

The UP School of Statistics is actually the first school in Southeast Asia to offer an undergraduate degree program in statistics. The Professional Master in Data Science (Analytics) Program is offered through the School of Statistics. According to the school’s website, the program “is suited for professionals who have quantitative background and are hands-on with processing and/or analyzing data, or those who value the importance of empirical or evidenced-based decision making and see the potentials of using Statistics and/or analytics to achieve their goals.

“The program aims to equip professionals with a solid foundation in the theory and methods of statistical science and to be adept at statistical machine learning to solve real-world problems. Aside from the technical aptitude, students enrolled in the program are expected to have, at the end of the program, improved skills for research, presentation, communication, and decision-making.

3| Ateneo de Manila University

Ateneo’s MS Data Science program “is a research-oriented degree that provides foundation courses and a range of electives to pursue specific areas of interest. It has a six-unit credit capstone referred to as a thesis which requires an artifact as an output, a written report and an oral presentation.” 

4| De La Salle University

DLSU has a Data Science Institute that offers programs that include a Minor in Data Science, A Master in Data Science, and a Diploma Course in Data Science. According to the DLSU website , the Minor in Data Science program "aims to produce data literate graduates by equipping the students across the different disciplines with a working knowledge of statistics, probability, and computation enabling them to design and execute precise computational and inferential data analysis for their discipline."

The education arm of listed STI Holdings said it started offering programs related to DSA through the STI Education Services Group (STI ESG) and STI West Negros University (WNU) during school year 2020 to 2021. These programs are a Bachelor of Science degree in Retail Technology and Consumer Science, and a two-year Associate degree in Retail Technology.

According to STI, the programs will teach students to apply data science and business analytics “to drive understanding of the changing market and consumer behavior, as well as to employ disruptive technologies. They will likewise be trained to utilize omnichannel retail marketing strategies to satisfy the changing consumer demands and varying purchasing habits.

“Upon graduation, students of the said programs will be ready for the future of work with specialized skills in the areas of Retail Marketing, Consumer Psychology, Information Technology and Data Science,” it added. “Graduates may become business analytics professionals, big data analysts, consumer analysts, consumer scientists, data scientists, digital marketing e-commerce specialists, and e-business data managers, among others.”

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Asian Institute of Management Launches PhD in Data Science Program

The Asian Institute of Management (AIM) launches a new doctoral Ph.D. in Data Science aimed at meeting the increasing demand for data scientists, who can extract knowledge and provide insights from the huge volume of data being generated every day. The unusual, advanced, and high-level doctoral program is the first of its kind in the Philippines and one of only a few in the rest of Asia.

AIM’s new Ph.D. program focuses on making original contributions to data science by leveraging data systems, analyzing trends, and building models in a clear manner for the interest of industry, society, and academia. “This doctorate Ph.D. program is designed to push the boundaries of knowledge across multiple disciplines and will maintain AIM’s leading position in Data Science, complexity science, and artificial intelligence research,” according to AIM’s President and Dean Jikyeong Kang.

The Ph.D. program builds on the success of AIM’s Master of Science in Data Science degree program which is currently ranked third in Far East Asia ahead of similar offerings inJapan, Singapore, and South Korea.

“We want our graduates to be able to rise to the new challenges of a world powered and governed by data,” said Associate Professor Erika Legara, AIM’s MSc in Data Science Academic Program Director.  “AIM’s Ph.D. in Data Science program will stress the creation of new knowledge, insights, and methods with and from data. The program will train individuals to conduct comprehensive and extensive research on cross-disciplinary topics.”

Students who take AIM’s Ph.D. in Data Science program’s rigorous curriculum will be under the guidance of the Institute’s internationally recognized faculty of data scientists. They will also have access to AIM’s 1.2-petaflop computing facility — one of the most powerful and sophisticated supercomputing platforms in Southeast Asia.

All Ph.D. students will be required to serve as instructors or teaching assistants at AIM, allowing them to share the results of their research. Upon graduation, they are likely to become key players in ethical and responsive Data Science research and policymaking in a wide range of fields, including finance, economics, urban planning, transportation, and medicine. Graduates of this new Ph.D. program will be equipped with practical skills on the latest theories and concepts of data science to satisfy the needs of the government, the various industries and international organizations, as well as the  big tech firms like Amazon, Google, and Microsoft, and the prestigious banks like JP Morgan.

More details about the AIM Ph.D. in Data Science program, including scholarship opportunities, may be obtained by sending an email to [email protected] .

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Data Science is a relatively young scientific discipline aimed at addressing important scientific and societal problems by focusing on obtaining, analyzing, and interpreting data. It has become an indispensable part of both academia and industry. Indeed, Data Science is now widely regarded as the fourth pillar of scientific discovery complementing theoretical, experimental, and computational approaches. 

The PhD Program in Data Science is aimed at preparing aspiring data science professionals for a successful career in academia or industry. To achieve this goal, enrolled students will engage in world-class research at one of the best Universities in Switzerland. They will also have access to a multidisciplinary curriculum and be able to collaborate with experienced faculty members from a large number of departments across the University.

Students have to be offered a PhD position by an individual faculty member of a participating research group. The faculty member together with the PhD candidate can then select an appropriate PhD program that best fits the academic profile of the candidate. The data science PhD program is tailored for students with a strong technical background in machine learning or data science, for example. Decisions regarding enrollment into the PhD program will be made by an admission committee.

Requirements

A Master's degree in Science, Mathematics, or Computer Science or an equivalent degree. Additional requirements may be attached to specific PhD openings. Further requirements may be listed in the regulations of the doctoral program.

Successful applicants have a strong scholastic record, a creative mindset, are able to communicate their work effectively, have a basic knowledge of programming and statistics, and, most of all, enjoy solving problems in Data Science.

In order to graduate, students need to fulfill the following requirements:

• Deposition and defense of a written dissertation about the student's independent research project
• Acquisition of 12 ECTS credits of advanced courses
• Additional requirements imposed by the admission committee, the doctoral committee, or the University

Curriculum 

The program includes a curricular part of at least 12 ECTS credits. Participating students can choose from a broad selection of research topics and classes in coordination with or as stipulated by their doctoral committee. The curricular part of the doctoral studies covers both the specific topic area of the research project and a general education in Data Science and data modeling in Natural Sciences. ECTS credits may also be awarded for active participation in conferences or other activities of relevance for the doctoral study.

Featured Courses

• Academia Industry Modeling (AIM) week
• During AIM week, teams of PhD students and post-doctoral fellows complete a one-week focused research project on applied problems proposed by industry partners. Industry representatives and participating faculty coordinate the formulation of the problem and supervise the research teams. Topics can cover all scientific interests and domains represented in the PhD program and in particular their interfaces.
• Modeling of Complex Systems In this hands-on course, the students learn how mathematical models can be used to describe and understand the dynamics of real-world systems in essentially all applied sciences, such as physics, biology, chemistry, engineering, economics, social sciences etc. The course covers concepts like integration methods, mechanistic and descriptive modeling, stochasticity, and Monte Carlo simulations. On the practical side, students will model and implement dynamical systems, understand the theoretical background and limitations, and practice understanding and communicating of models.

Official PhD regulations for the Data Science Programme:

Doctoral Program Regulations (PDF, 206 KB) Ordnung zum Doktoratsprogramm (PDF, 107 KB)

For PhDs starting after 1 June 2022 the updated regulations apply:

Ordnung zum Doktoratsprogramm (ab 2. Juni 2022) (PDF, 152 KB)

Doctoral Program Regulations (PDF, 93 KB)

Admissions to Promotion - Useful links and documents:

Admission to Doctoral Studies at the University of Zurich

Factsheet Admission to a PhD Program at the Department of Astrophysics (PDF, 621 KB)

Checklist for PhD students

"Confirmation of Supervision for Doctoral Students" (PDF, 242 KB)

"Acceptance Confirmation Structured Doctoral Program" (PDF, 225 KB)

Annual committee meeting minutes (PDF, 1 MB)

Confirmation Sheet - TA Hours (PDF, 224 KB)

Fact sheet PhD Defence (EN) / Merkblatt (DE)

Program Director Prof. Dr. Jan Dirk Wegner [email protected]

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In the world of digitization, data stands as the ultimate catalyst for sustainable businesses and societies. Recognizing the crucial value of data, AIM has launched the Master of Science in Data Science (MSDS) program, the first-ever data science graduate degree program in the country.

AIM’s prestige program is the institute response to the demand for one of the most integral and most sought-after specializations. The pioneering MSDS batch will begin their curriculum in March of next year and will undergo a rigorous 14-month-long program compromised of 10 core data science modules, a minimum of four business management modules, two electives, and a concluding project to exercise professional skill. “This is our most thought-through, most intelligent, and most appropriate response to prepare for the changes and challenges digitalization throws at us,” said Jikyeong Kang president and dean of AIM.

Designed to be holistic, the MS in Data Science curriculum will immerse students in advanced data analytics and technologies. Specially crafted by renowned data scientists and international practitioners, it will likewise enable students to learn from the experts themselves, especially in the area of solving complex dataset problems in the field of research and business.

The program aims to produce data competent individuals capable of leading data-driven initiatives across different industries. “Data science cuts across industries, and the MSDS program AIM offers is strongly tied to the Insitute’s business and management modules,” said Erika Legara, Academic Program director for MSDS. Further stressing on the point, Legara said that the program aims to produce a battalion of competent data scientists fit for today’s data-driven world.

Alongside the MSDS program, AIM also launched the School of Innovation, Technology, and Entrepreneurship (SITE). Trends are always changing, thus, the end goal of the school is to produce versatile students who can readily adapt to today’s tomorrow’s setting. “SITE is where innovators, data scientists, and entrepreneurs become future-ready leaders. They will be comfortable with uncertainty, adept at handling multifaceted issues and be confident about executing decisions in a rapidly evolving environment,” said Christopher Monterola, head of SITE at AIM. Under SITE are three programs: Masters in Entrepreneurship, Master of Science and Innovation and Business, and Master of Science in Data Science.

Applications are currently open. To learn more about the SITE programs, kindly visit AIM.edu

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Aim-ahead data science training core participants.

Data Science Training Core Training Practicum (PRIME)

AIM-AHEAD Training Practicum (PRIME)

The AIM-AHEAD Data Science Training Core Training Practicum (PRIME) is an NIH-funded training program that focuses on developing skills in Artificial Intelligence (AI) and Machine Learning (ML) applications on health disparities. The PRIME cohort of 2022 includes 26 trainees at the graduate and undergraduate level. Throughout their PRIME program, trainees complete a variety of AI/ML courses over the course of their 6-month (graduate) or 8-month (undergraduate) program. Trainees are connected with mentors who are leading experts in their field who support their learning journey. At the end of their program, PRIME trainees also complete a group poster project which highlights their learnings from participating in PRIME. Additionally, select trainees complete an individual extended abstract project which details the AI/ML applications that are directly applies to their research.

PRIME Trainees of 2022

Aaryn DuBose

Tuskegee University

Amir Reza Sadri

Case Western Reserve University

Artificial Intelligence, Medical Imaging, System Identification

Benjamin Corriette

Howard University

Human-Computer Interaction, Accessibility, Wearables

Brittany Taylor

Columbia University School of Nursing

Christopher Andrews

Health Disparities, Triple Negative Breast Cancer, and Artificial Intelligence

Darryl Parsons

Natural Language Processing, Machine Learning, Human Computer Interactions

Daryllynn Nelson

Morehouse School of Medicine

Health Equity, Prostate Cancer, Increase in data representation of minority men

Dedrionna Wilson

Benedict College

Biological Sciences, Human Disease and Health Inequity

Eduardo Figueroa

University of Puerto Rico Medical Science Campus

Bioinformatics, Machine Learning and Data Science

Frances Marie Aponte Caraballo

University of Puerto Rico, Medical Sciences Campus

ALS, infectious diseases, and health disparities

Howard Prioleau

Machine Learning, Computer Vision, natural language processing

Iyinoluwa Tugbobo

ML, Cybersecurity, IoT

Janae McCloud

Innovative, Disparity, Health

Jeannette Tsuei

Pardee RAND Graduate School

Health technology effectiveness, health equity, mental health disparities

Jerry Diabor

Bowie State University

Global Warming, Viruses, Medicines

Jose Irizarry

Tulane University School of Medicine

Social and environmental determinants of health, Electronic health record data, Public health informatics

Kakuyon Mataeh

Princeton University

Qualitative, medication, marginalization.

LaToya McDonald

Clemson University

Machine Learning EHRs

Lindsey J. Hyppolite

Delaware State University

Biomedical, Technological, & Innovative

Maruful Sumon

Jackson State University in Mississippi

Data Science, Machine Learning, and EHR Data

Muna Mohammed

Meharry Medical College

Cancer Immunotherapy/ Logical Prediction

Olivia Heath

University of New Mexico Health Sciences Center

Prathyush Chirra

Case Western Reserve

MRE/CTE, Machine Learning, Crohns

Siumukuka Faaiuaso

American Samoa Community Cancer Coalition, Chaminade University

Health Disparities, Data Science, and AI/ML

Teanna Barrett

ML Fairness, Social Computing, and Digital Activism

William Edwards

Machine Learning Education, AI/ML Fairness and Bias Elimination

PRIME Team of 2022

Nawar Shara (MPI) MedStar Health Research Institute Data Science Training Core and Data and Research Core

Dr. Shara is Director of the Center of Biostatistics, Informatics and Data Science (CBIDS), Associate Professor of Medicine at Georgetown University in the Division of Endocrinology and Metabolism, serves as Director of the Biostatistics, Epidemiology and Research Design (BERD) Core and is co-Director of the Biomedical Informatics (BI) Core for the Georgetown-Howard Universities Clinical and Translational Science Center (GHUCCTS). She received her undergraduate degree in Economics from Damascus University and her master’s and Ph.D. degrees in Applied Statistics from American University in Washington, D.C.

Dr. Shara’s area of specialty includes Big Data analytics, predictive modeling, leveraging electronic medical records for translational research, AI and ML solutions in healthcare. Dr Shara has extensive experience as Principal Investigator of several NIH, industry and foundation funded studies. Her earlier work examined correlates of kidney and cardiovascular disease including oxidative Stress and surrogates of kidney function. She is the principal investigator of NIH NCATS supplements leveraging AI and ML tools in the form of voice activated technology to help patients with Heart Failure to better manage their disease, leverage AI to identify factors associated with maternal mortality and morbidity and the mapping of COVID-19 data into a national registry maintained by NCATS/NIH.

Dr. Shara conducts, supports, and oversees translational research across MedStar hospitals and is involved in teaching and education at Georgetown University. She is course Director for many offerings at GU including, Biostatistics in Medical Research, Research Methodology and Analytic Approaches in Regulatory Science, a course offered as part of the Master of Science in Regulatory Science program at Georgetown University (CERSI). Dr Shara served as Chair for a session on AI in medicine at the First International Conference in Systems and Network Medicine at Georgetown University, Washington DC, September 2019 as well as one of the key speakers at the 2020 Spring Regulatory Update and Hot Topics in Clinical Research COVID-19: The Virus, Preparedness in the time of Crisis, and Clinical Research aimed at informing the community about the significance and complexity in the sharing of data from human subjects.

She is a member of the American Statistical Association (ASA), the Royal Statistical Society (RSS), the American Society of Nephrology (ASN), the Women in Statistics Caucus, and serves on the ASA Scientific and Public Affairs Advisory Committee. She served as the President of the National Arab American Medical Association (NAAMA DC Chapter) as well as the chair of the Science and Research Committee for NAAMA.

MedStar Health Research Institute

Alexander V. Libin, PhD Co-Director MedStar Health Research Institute, Georgetown University

Dr. Alexander V. Libin is an internationally recognized scientist with the expertise in cyberanthropology and human-robot interactions, psychosocial trials and culturally-tailored interventions for underrepresented populations. He holds a joined position at the Center for Biostatistics, Informatics and Data Science (CBIDS) at the MedStar Health Research Institute, the Biostatistics, Epidemiology and Research Design Core at the Translational Science Consortium (GHUCCTS), and the Department of Rehabilitation Medicine at the Georgetown University. Dr. Libin is an experienced PI on projects ranging from RCT with vulnerable groups, including military Veterans, to implementation studies focusing on multimedia-based self-management, and AI/ML applications aimed at optimizing Big Data for individual personal acquisition. In partnership with Dr. Elena Libin, a leading practitioner in coping intelligence as a training framework for cross-disciplinary decision-making competencies, he established a Scopus and WoS indexed online journal on Coping with Pandemic and Infodemic Stress { hyperlink - https://www.frontiersin.org/research-topics/19940/coping-with-pandemic-and-infodemic-stress-a-multidisciplinary-perspective }. Dr. Libin’s research is funded by the DOD, VA R&D, NIDDR, as well as private foundations. As a Lead Knowledge Translation (KT) Scientist he will coordinate and oversee communication and outreach efforts at the DSTC, working in coordination with A-CC on dissemination strategy and bringing his expertise in psychosocial digital technology to the team of AIM-AHEAD investigators. Dr. Libin’s outcomes on real-world AI applications and psychosocial challenges in digital world wwere featured in Washington Post, Time magazine, Wired, IEEE special issue on person-robot interactions, Army magazine and national and international radio and tv networks.

Co-Director

MedStar Health Research Institute, Georgetown University

Sara is a skilled project manager and researcher who leverages business acumen and scientific background to provide structure and support to cutting-edge research projects. Sara is a highly experienced technical writer with budgeting skills and team management skills honed through years of collaborative research and programmatic efforts. Sara received her M.S. Degree in Biology from Bowling Green State University and her Master of Business Administration (MBA) from The Ohio State University. Sara’s academic special interests are in Artificial Intelligence, Machine Learning, healthcare, environmental, sustainability, and governance (ESG) business strategy, programmatic development, and health equity.

Project Manager

Tom Whitfield , Program Manager MedStar Health Research Institute

Tom Whitfield is a Research Analyst with MedStar Health Research Institute. He has a passion for suicide prevention and mental health advocacy. Tom is interested in research applying AI/Ml to address mental health inequities. Tom earned a B.S. in Psychology from University of Central Florida. He is also a Pilot and Certified Flight Instructor (CFI).

Program Manager

Alyssa Parham Program Manager Howard University

Omar Aljawfi Curriculum Development Medstar Health Research Institute

Currently, Omar serve as Informatic Analyst at the Center for Biostatistics, Informatics and Data Science (CBIDS) MedStar Health Research Institute (MHRI). In these positions, I Conducts Electronic Health Record (EHR) reviews per project-specific criteria. Abstracts and accurately records data from specified records. Omar is supporting and collaborating with many investigators from across the MedStar network and the Georgetown University in building forms and data extractions. The purpose of the data extraction from the MedStar electronic health record data base is to support research studies, and quality improvements projects. Omar collaborated on several projects aimed at using large scale data from EHR to examine several models of diseases including the application of artificial neural networks, decision trees and several predictive analytics techniques to identify predictors from MedStar’s EHR. Furthermore, he provide training on tools and systems as needed and participate in meetings and on committees and represents the department and hospital in community outreach efforts. Also, Omar participate in multi-disciplinary quality and service improvement teams. Omar have authored and co-author many of the research work generated by CDS&E program to merge domains of Artificial Intelligence, Data Science, and health care.

Curriculum Development

Medstar Health Research Institute

PhD Programme in Data Science

Admission requirements.

Applicants seeking admission to the PhD programme should satisfy the following minimum entrance requirements.

be a current MPhil student in the University who is seeking transfer to a PhD programme; or hold a higher research degree (or equivalent qualification) from a recognised university; or hold a Master’s degree (or equivalent qualification) from a recognised university; or hold a Bachelor’s degree with first-class honours (or equivalent qualification) from a recognised university.

English Proficiency Requirements

Applicants from an institution where the language of teaching is not English should satisfy the minimum English proficiency requirements as follows:

• a minimum TOEFL total score of 550 (paper-based test) or 79 (Internet-based test); or 59 (revised Paper-delivered test); or
• a minimum overall band score of 6.5 in IELTS; or
• other test scores that may be regarded as equivalent to TOEFL 550 (paper-based test) or 79 (Internet-based test); or 59 (revised Paper-delivered test).

College English Test (CET) is  NOT  accepted as an equivalent English proficiency test for Hong Kong PhD Fellowship Scheme (HKPFS).  For applicants with strong academic and research potential who have only taken CET-6 with a minimum score of 490, special consideration may be made on a case-by-case basis during normal round admission. 

Applications for the Master of Philosophy (MPhil) programme are not considered.

Hong Kong PhD Fellowship Scheme (2024/25)

The Hong Kong PhD Fellowship Scheme , established by the Research Grants Council (RGC) of the HKSAR government, aims to recruit the brightest students in the world to pursue their PhD studies in Hong Kong. 300 PhD Fellowships will be awarded in the 2024/25 academic year. While academic excellence is the primary consideration, applicants should demonstrate research ability/potential, communication and interpersonal skills, and leadership abilities. The result of the HKPFS 2024/25 will be announced in April/May 2024 by RGC.

The Fellowship awardee will receive:

• an annual stipend of HK$331,200 (~US$42,460).
• conference and research-related travel allowance of HK$13,800 (~US$1,760) per year for a maximum of three years.
• Chow Yei Ching School of Graduate Studies Entrance Scholarships around HK$89,496 (~US $11,473) which covers student's full-time tuition fees and on-campus hostel accommodation expenses in the 1st year of research studies.

For Fellowship awardees who are admitted to a 4-year PhD programme, CityU will provide a monthly studentship at the same level as the RGC Fellowship for their fourth year of study.

Click here to download leaflet

How to Apply

1.  Getting Started Select area of interest, contact  potential supervisor  and seek consent Observe application deadlines

2.  Prepare Take required tests before application deadline Prepare supporting documents (example: transcript, research proposal) Academic referee reports

3.  Apply Apply Now   (You are required to list all post-secondary institutions you have attended.)

• Submit initial application as early as possible to ensure that you have sufficient time to submit application to CityU.
• Applications which are not selected for the Hong Kong PhD Fellowship Scheme will be considered as normal applications.

Application Timeline

Supporting Documents

Remarks: Hard copies of the documents are required for further verification only if you are given an offer. Documents which are not in English should be accompanied by a formally translated version in English.

Selection Criteria

While the academic excellence is of prime consideration, the Review Panels will take into account, but not limited to, the following yardsticks for the selection of candidates:

• Academic excellence;
• Research ability and potential;
• Cultural diversity;
• Communication and interpersonal skills;
• Leadership abilities and societal responsibility;
• Institutional support.

Shortlisted candidates will be invited to admission interview (either face-to-face or via online means e.g. Zoom, Skype, etc.).

Programme Structure

1) Coursework Plan To be eligible to be awarded an MPhil/PhD degree, students are required to complete the following coursework requirements and to submit a thesis. MPhil: 7 credit units (including at least 2 credit units of research methodology and ethics course at postgraduate level); --> PhD: 20 credit units (including at least 9 credit units of core courses and at least 2 credit units of research methodology and ethics course at postgraduate level) And 1 credit unit compulsory course: Teaching Students: First Steps (SG8001). Individual students with insufficient English proficiency may be required to take a 1 credit unit course English as Medium for Instruction (SG8002) before they are allowed to enrol in SG8001. The credit unit earned from SG8001 will not be counted towards the minimum coursework requirement. And Training on Research Integrity (CITI Programme) .

Please refer to the programme requirements for PhD in Data Science at http://www.cityu.edu.hk/catalogue/pg/202324/programme/DS_P.htm. https://www.cityu.edu.hk/catalogue/pg/202223/programme/DS_M.htm . --> 2) Credit Transfer and Exemption Students who possess postgraduate qualifications of relevance to their research studies may apply for credit transfer or coursework exemption. At least half the coursework (4 credit units for MPhil and 7 for PhD) should be taken at CityU or other local institutions recognised under the Cross-institutional Course Enrolment Scheme. Credit transfer/coursework exemption should be limited to a maximum of 3 credit units for MPhil and 7 for PhD. Recommendations on credit transfer/coursework exemption require the approval of the School Dean.

3) Cross-departmental Course Registration Students who wish to take courses offered by Departments/Schools outside their host School should obtain approval from the offering Department/School before submitting the Form SGS16A/SGS16B to their host School for endorsement and approval. A list of approved courses and the syllabi are available for reference on the  Chow Yei Ching School of Graduate Studies (SGS)  website.

Scholarship and Funding

Chow Yei Ching School of Graduate Studies Entrance Scholarships  (Applicable to government-funded students only)

CityU offers Chow Yei Ching School of Graduate Studies Entrance Scholarships to encourage outstanding international students to undertake MPhil or PhD studies at the University with a view to promoting academic exchange and enhancing the international mix of the University’s student population.

The Scholarship covers students’ tuition fees and on-campus hostel accommodation expenses in their first year of their research studies (equivalent to approximately HK$89,496 (~US$11,474)). If granted a Scholarship, the above-mentioned expenses will be off-set by the award.

Tuition Waiver for Local Research Postgraduate (RPg) Students

The University Grants Committee (UGC) has introduced a ‘Tuition Waiver Scheme’ (‘The Scheme’) for all local students enrolled in full-time UGC-funded Research Postgraduate (RPg) programmes in local institutions, to cover their tuition fees with effect from the academic year 2018-19 (i.e. from July 1, 2018).

This Scheme provides non-means-tested funding to all current and new local students from all disciplines of study enrolled in full-time UGC-funded RPg programmes. Eligible students do not need to apply for the Scheme.

For more information of Tuition Waiver Scheme for Local Research Postgraduate Students, please refer to  http://www.ugc.edu.hk/eng/rgc/funding_opport/tws.html

For the full list of scholarships and financial aid, please visit  https://www.cityu.edu.hk/pg/research-degree-programmes/scholarships-financial-aid-and-fees .

Tuition/Continuation Fees

(normally adjusted in September every year)

Potential Supervisors: Potential applicants are encouraged to contact a  potential supervisor  prior to submitting an application to our University, though it is not compulsory.

Research Degree Coordinator: Professor Qi WU

General Enquiries: Tel: 3442 7887 Email:  [email protected]

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Master of Engineering in Data Science & Decision Analytics

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There are complex algorithmic frameworks behind most online platforms deciding which vehicle to assign to a passenger in a ride sharing system depending on the geographical allocation of the vehicle supply, what price to charge for a product depending on the inventories or which fulfillment center to use to store an incoming shipment. Cornell Tech’s Master’s in Decision Science and Decision Analytics (DSDA) will provide you the tools to understand the data-to-algorithms-to-decisions pipeline by drawing from tools in machine learning, optimization and statistics.

Introduction to Cornell Tech

About the master of engineering in data science and decision analytics degree.

Cornell Tech’s DSDA Masters allows you to develop a theoretical and practical understanding of the data-to-models-to-decisions pipeline in entrepreneurial environments by drawing from tools in machine learning, optimization and statistics. After going through the program, you will be able to develop and deploy algorithms to drive the decisions of online business such as e-retailers, ride-sharing systems and ad exchanges. Working with the faculty that are world leaders in optimization, statistics, causal analysis and machine learning, as well as being immersed in the tech start-up community of New York City, you will get comfortable with analyzing data, building decision models that turn data into decisions and deploying these models at large scale. In parallel with your academic technical courses, you will also complete Studio courses – an essential component of every Cornell Tech program that allow you to solve real business problems faced by tech companies and launch your own startups. During the course of Studio courses, you will work in cross-disciplinary teams with students in computers science, electrical engineering, business and law programs to study all facets of the problem you are focusing on.

Who Should Apply?

Cornell Tech’s DSDA Masters is ideal for students with a passion for data analysis that create insights to drive business decisions. The technical requirements are that you have completed one course on linear algebra, one course on intermediate-level probability and statistics, and one course on programming before applying. Cornell Tech offers another Masters degree in Operations Research and Information Engineering (ORIE). As is the case with all Masters programs at Cornell Tech, both DSDA and ORIE programs have an entrepreneurial focus, but DSDA emphasizes the intersection of optimization, machine learning and probabilistic analysis with computing, whereas ORIE emphasizes the intersection of optimization, machine learning and probabilistic analysis with business.

Technical Topics Covered

• Optimization for AI
• Statistics for Data Science
• Probabilistic Analysis
• Machine Learning
• Modeling Under Uncertainty

Studio Topics Covered

• Entrepreneurship
• Law for Non-Lawyers
• Leadership for Digital Transformation
• Product Management
• Startup Funding & Pitching

Next Data Science Strategy Seminar Set

NIH’s Office of Data Science Strategy (ODSS) hosts a seminar series to highlight exemplars of data sharing and reuse on the second Friday of each month at noon ET. This monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings.

The next seminar will feature Drs. Charles Schmitt and Danielle Braun. On Sept. 13 at noon, they will present “Climate and Health Outcomes Research Data Systems (CHORDS).” The CHORDS project aims to support biomedical researchers in finding and using the data sets, tools and models needed to conduct environmental health research.

Schmitt is director of the office of data science, NIEHS, and a senior scientist in the NIEHS Division of Translational Toxicology. Braun is director of data science for environmental and climate health in the department of biostatistics at the Harvard T.H. Chan School of Public Health. She is also a research scientist at the Department of Data Science at Dana-Farber Cancer Institute.

The series is open to the public; registration is required. For more information, including how to register, visit: go.nih.gov/ kSJr9NH

Individuals who need interpreting services and/or other reasonable accommodation should call Janiya Peters at (301) 670-4990. Make requests at least five days in advance of the event.

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