Program overview
The Columbia University Center for Veteran Transition and Integration (CVTI) supports excellence and innovation in transition programming for current and former members of the armed forces.
As a service member in transition, you may face barriers reaching your potential in accessing higher education and beginning meaningful careers, despite the many effective programs offered to this population by the Department of Labor, Department of Defense’s Transition Assistance Program, and other programs offered by the Army, Air Force, Navy, Marine Corps, and Coast Guard. With this in mind, the CVTI is dedicated to creating free courses that will help to break down those barriers to your successful transition. Currently we are offering three courses to meet these demands, with more courses on the way. While these courses are created for veterans and active duty service members, they are free and available for all.
Attaining Higher Education is a course designed to facilitate the successful transition of active duty service members and veterans to postsecondary education, whether at a two- or four-year college for an associate’s or bachelor’s degree, or even graduate school.
University Studies for Student Veterans helps orient veterans to the norms and expectations of the college classroom, along with offering strategies to ease the transition, to help achieve academic goals, and to allow students to optimize their college education.
Find Your Calling: Transition Principles for Returning Veterans will focus on the development of interpersonal, intrapersonal, and intellectual character strengths as they relate to making a successful career transition from military service to the civilian workforce. The course content is meant to provide you with a framework for an iterative process of self-reflection and the development of practical skills that enables you to make career choices that better align with your values, ambitions, and continued service. Ultimately, this course helps you answer the question: What should I do next?
What will you learn
- General and detailed information about colleges and universities.
- Foundational academic and study skills for achieving academic success in college.
- Strategies for more effective reading, writing, test preparation, and time management.
- Practical tips and strategies for making a successful military-to-civilian career transition.
- A framework for how to begin thinking about and exploring new career opportunities.
Program Class List
1Attaining Higher Education
Course Details
1
Prepare to transition to college using intentional decision-making. Aimed at active duty service members and veterans, with this course you will learn about the college admission process, including financial aid, to help you choose a right-fit college.
2University Studies for Student Veterans
Course Details
2
This course helps veterans transition smoothly from military service to college, and helps them maximize their success once they arrive.
3Find Your Calling: Career Transition Principles for Returning Veterans
Course Details
3
This course provides military veterans with a useful roadmap to transition more smoothly from military service to a new and meaningful civilian career.
Meet Your Instructors
Beth E. Morgan
Director of Higher Education Transition and Partnerships at Columbia University
Born in Quantico, Virginia, Beth grew up in a Marine Corps family and was raised around the world, living for periods of time in Hawaii, Germany, and Korea. Professionally, Beth has worked for the Central Intelligence Agency, for several non-profits, as a consultant, and on staff at major universities throughout the United States, including Colgate University, Princeton University, and the University of Southern California. Prior to joining the Center for Veteran Transition and Integration at Columbia University, Beth worked most recently with the non-profit Service to School as Executive Director and previously directed the Marine Corps Leadership Scholar Program (LSP), both of which assisted transitioning service members and veterans with admission to undergraduate and graduate programs. Beth has a Bachelor of Arts degree from the University of Virginia and a Master of Arts degree from Stanford University.
R.J. Jenkins
Curriculum Designer at Columbia University
Before joining the Columbia University Center for Veteran Transition and Integration as a Curriculum Designer in 2016, R.J. served as an Associate Dean of Students at Columbia University’s School of General Studies where he directed the Academic Resource Center and served as the lead instructor for University Studies, a transition course for first-year, non-traditional students. An award-winning teacher, R.J. has advised college students at Columbia, Cambridge, and Harvard Universities, and has taught courses in English and American literature, literary history, close reading, academic skill-building, and English for Speakers of Other Languages. R.J. holds a Bachelor of Arts in English and anthropology from Columbia University (2003), a Master of Letters in English literature from the University of Cambridge (2005), and is currently pursuing doctoral work in English literature.
Skip Bailey
Senior Advisor to the Director of Educational Financing at Columbia University
William ”Skip” Bailey has been a financial aid administrator for more than 34 years. He has been managing financial aid for non-traditional students at the School of General Studies (GS) for over 20 years. Previously he administered financial aid at multiple colleges including the University of San Diego and the University of Michigan. A degree in education from Michigan State University and lots of experience has provided Skip with the tools he uses every day to assist students at GS with the myriad issues involved with college financial aid.
Tanya Ang
Vice President of Veterans Education Success at Columbia University
Tanya is the Vice President of Veterans Education Success and has more than 17 years of experience in higher education. She has worked at the American Association of State Colleges and Universities and also served as the Director of Veterans Programs at the American Council on Education. Prior to joining ACE, Tanya worked at two universities including working as an Administrative Analyst for the Vice President of Student Affairs Office at California State University - Fullerton and as Associate Registrar at Vanguard University where most her work focused on the non-traditional student including military and student veterans. She was the certifying official at her institution for student veteran GI Bill benefits and worked hand-in-hand with the various offices on-campus to ensure students received the benefits and the support they needed to successfully navigate their academic career. In her current role, she works to ensure military-connected students have access to high-quality education to achieve their long term career goals. Tanya is the first in her family to graduate from college, and earned her BA in Communications at Biola University and an MA in Organizational Leadership at Vanguard University.
Sara Remedios
Associate Dean of Students at Columbia University
Sara is Associate Dean of Students at Columbia University’s School of General Studies where she directs the Academic Resource Center and oversees all academic and learning initiatives. Before coming to Columbia, she worked to restructure the CUNY Pipeline Honors Program, a program dedicated to assisting exceptional undergraduate students from underrepresented backgrounds in gaining admission to doctoral programs. She is also an accomplished teacher. Dean Remedios holds a B.A. in English and political science from Washington University in St. Louis (2009), an M.Phil. in English literature from the City University of New York (2014), and a Ph.D. in English literature from the City University of New York (2016).
Josh Edwin
Senior Assistant Dean of Students at Columbia University
Josh is Senior Assistant Dean of Students at Columbia University’s School of General Studies. His teaching experience at Columbia includes University Studies, academic writing classes, one-on-one writing support, and creative writing workshops for veterans. He has also taught at a public high school in Atlanta and an English language school in Seoul, South Korea. In addition to teaching, he has published widely as a poet, translator, and reviewer. He holds a B.A. in English and creative writing from Emory University and an M.F.A. in poetry and literary translation from Columbia University’s School of the Arts.
Michael Abrams
Executive Director - Center for Veteran Transition and Integration, Marine Corps Veteran at Columbia University
Michael Abrams joined the Marine Corps shortly following the September 11, 2001 attacks and served on active duty for eight years, which included a deployment to Afghanistan with an infantry company as the artillery forward observer. After leaving active duty, Michael attended New York University’s Stern School of Business graduating with an M.B.A. in Finance and Entrepreneurship & Innovation. While attending business school, he founded FourBlock to help bridge the gap between returning service members and the business community. The program is a university accredited, semester-long course that educates and prepares transitioning veterans for meaningful careers in corporate America. FourBlock is in nearly twenty cities across the country, educating and serving hundreds of transitioning veterans each semester. Michael is now serving as the executive director of the Columbia University Center for Veteran Transition and Integration. The newly established center of excellence is dedicated to creating and supporting evidence-based programming that enables returning service members with reaching their academic and career potential.
William Deresiewicz
Best-Selling Author, Award-Winning Essayist at Columbia University
William Deresiewicz is an award-winning essayist and critic, a frequent speaker at colleges and other venues, and the best-selling author of Excellent Sheep: The Miseducation of the American Elite and the Way to a Meaningful Life. He taught English at Yale and Columbia before becoming a full-time writer in 2008. Bill has published over 250 essays and reviews. His work has appeared in The New York Times, The Atlantic, Harper's, The Nation, The New Republic, The American Scholar, and many other publications. He has won the Hiett Prize in the Humanities, the Balakian Citation for Excellence in Reviewing, and a Sydney Award; he is also a three-time National Magazine Award nominee. His work has been translated into 17 languages and anthologized in more than 30 college readers. He has spoken at over 80 colleges, high schools, and educational groups and has held visiting positions at Bard, Scripps, and Claremont McKenna Colleges. Bill’s previous book is A Jane Austen Education. He is working on a book about how artists are making a living in the new economy.
Sheena Iyengar
World-Renowned Expert on Choice, S. T. Lee Professor of Business at Columbia University
Professor Iyengar has taught courses in leadership and entrepreneurial creativity. Her research addresses the implications of offering people, whether they be employees or consumers, choices. She has examined choice in a multitude of contexts ranging from employee motivation and performance in a global organization, Citigroup, to chocolate displays at Godiva, to the magazine aisles of supermarkets, and to mutual fund options in retirement benefit plans. Professor Iyengar received the Presidential Early Career Award for her ongoing work in examining cultural, individual, and situational factors that influence people's choice-making preferences and behaviors.
Sebastian Junger
NYT Best-Selling Author, Documentary Filmmaker at Columbia University
Sebastian Junger is the #1 New York Times Bestselling author of THE PERFECT STORM, FIRE, A DEATH IN BELMONT, WAR and TRIBE. As an award-winning journalist, a contributing editor to Vanity Fair and a special correspondent at ABC News, he has covered major international news stories around the world, and has received both a National Magazine Award and a Peabody Award. Junger is also a documentary filmmaker whose debut film "Restrepo", a feature-length documentary (co-directed with Tim Hetherington), was nominated for an Academy Award and won the Grand Jury Prize at Sundance.
What is a bootcamp?
Our facilitated bootcamps focus on rapid skill acquisition by progressing you through a standard course on an accelerated schedule with peers who are committed to progressing on pace. Our bootcamps include:
- Live kick-off event
- Instructor facilitated Q&A for expert feedback and coaching
- Learner Success Support: welcome call, advising sessions, personalized pace reminders
- 24/7 help desk
About This Course:
In this bootcamp you will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.
This course can be used towards completion of a Professional Certificate in Data Science for Executives.
What You Will Learn:
- Data collection, analysis and inference
- Data classification to identify key traits and customers
- Conditional Probability-How to judge the probability of an event, based on certain conditions
- How to use Bayesian modeling and inference for forecasting and studying public opinion
- Basics of Linear Regression
- Data Visualization: How to create use data to create compelling graphics
Professional Certificate in Data Science for Executives
Learn the foundations and power of data science
Statistical Thinking for Data Science and Analytics
Machine Learning for Data Science and Analytics
Enabling Technologies for Data Science and Analytics: The Internet of Things
Meet Your Instructors:
Andrew Gelman
Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.
David Madigan
David Madigan received a bachelor’s degree in Mathematical Sciences and a Ph.D. in Statistics, both from Trinity College Dublin. He has previously worked for AT&T Inc., Soliloquy Inc., the University of Washington, Rutgers University, and SkillSoft, Inc. He has over 100 publications in such areas as Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance and probabilistic graphical models. He is an elected Fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently completed a term as Editor-in-Chief of Statistical Science.
Lauren Hannah
Lauren Hannah is an Assistant Professor in the Department of Statistics at Columbia University. Dr. Hannah received a Ph.D. in Operations Research and Financial Engineering from Princeton University, and an A.B. in Classics, again from Princeton University. After completing her Ph.D., Dr. Hannah completed a postdoc at Duke in the Statistical Science Department. Her interests include machine learning, Bayesian statistics, and energy applications.
Eva Ascarza
Eva Ascarza is an Assistant Professor of Marketing at Columbia Business School. She is a marketing modeler who uses tools from statistics and economics to answer marketing questions. Her main research areas are customer analytics and pricing in the context of subscription businesses. She specializes in understanding and predicting changes in customer behavior, such as customer retention and usage. Another stream of her research focuses on developing statistical methodologies to be used by marketing practitioners. She received her PhD from London Business School (UK) and a MS in Economics and Finance from Universidad de Navarra (Spain).
Meet your instructor
Daniel Wolfenzon
Daniel Wolfenzon is the Stefan H. Robock Professor of Finance and Economics at Columbia Business School. He received a Masters and a PhD in economics from Harvard University and holds a BS in economics and a BS in mechanical engineering from MIT. He is also a Faculty Research Fellow at the National Bureau of Economic Research.
Areas of Research:
His research interests are in corporate finance and organizational economics. He has studied control sharing in small firms, the effects of investor protection on ownership concentration, and the structure of business groups around the world. His most recent research focuses on family firms. He has examined the consequences of family succession on firm performance and also the importance of managerial talent in family controlled firms.
Course Overview
The skills you learned in the military will go a long way toward helping you succeed in college, but if you’re looking for some extra support – or an academic tune-up – then you’ll find it in this course. We know that the culture of higher education is different from the culture of the military in meaningful ways, and we also know that one of the keys to excelling in college – especially for student veterans – is learning to navigate these differences successfully, right from the very start.
This course aims to help you do just that. First, the course will orient you to the norms and expectations of the college classroom. The quicker you know what is expected of you, the quicker you can start learning. Second, the course will offer you strategies to ease your transition, to help you achieve your academic goals, and to allow you to make the most of your college education.
While this course is open to everyone, the content has been tailored specifically for student veterans currently pursuing higher education, active duty servicemembers who aspire to start school or return to school soon, and higher education professionals who work to support student veterans at their schools. If this sounds like you, and if you’re ready to learn how to make your transition easier and more successful, then we hope you’ll join us.
What You’ll Learn
- Foundational academic and study skills for achieving academic success in college
- Strategies for more effective reading, writing, test preparation, and time management
- Proven tips for students taking STEM and other technical courses
- Metacognition and academic mindset
Veteran Transition: Academic Excellence and Career Readiness
Transition from active service to college and the workforce
Attaining Higher Education
University Studies for Student Veterans
Find Your Calling: Career Transition Principles for Returning Veterans
Meet Your Instructors
R.J. Jenkins
Curriculum Designer at Columbia University
Before joining the Columbia University Center for Veteran Transition and Integration as a Curriculum Designer in 2016, R.J. served as an Associate Dean of Students at Columbia University’s School of General Studies where he directed the Academic Resource Center and served as the lead instructor for University Studies, a transition course for first-year, non-traditional students. An award-winning teacher, R.J. has advised college students at Columbia, Cambridge, and Harvard Universities, and has taught courses in English and American literature, literary history, close reading, academic skill-building, and English for Speakers of Other Languages. R.J. holds a Bachelor of Arts in English and anthropology from Columbia University (2003), a Master of Letters in English literature from the University of Cambridge (2005), and is currently pursuing doctoral work in English literature.
Sara Remedios
Associate Dean of Students at Columbia University
Sara is Associate Dean of Students at Columbia University’s School of General Studies where she directs the Academic Resource Center and oversees all academic and learning initiatives. Before coming to Columbia, she worked to restructure the CUNY Pipeline Honors Program, a program dedicated to assisting exceptional undergraduate students from underrepresented backgrounds in gaining admission to doctoral programs. She is also an accomplished teacher. Dean Remedios holds a B.A. in English and political science from Washington University in St. Louis (2009), an M.Phil. in English literature from the City University of New York (2014), and a Ph.D. in English literature from the City University of New York (2016).
Josh Edwin
Senior Assistant Dean of Students at Columbia University
Josh is Senior Assistant Dean of Students at Columbia University’s School of General Studies. His teaching experience at Columbia includes University Studies, academic writing classes, one-on-one writing support, and creative writing workshops for veterans. He has also taught at a public high school in Atlanta and an English language school in Seoul, South Korea. In addition to teaching, he has published widely as a poet, translator, and reviewer. He holds a B.A. in English and creative writing from Emory University and an M.F.A. in poetry and literary translation from Columbia University’s School of the Arts.
What you will learn
- The history of data science, tangible illustrations of how data science and analytics are used in decision making across multiple sectors today, and expert opinion on what the future might hold
- A practical understanding of the fundamental methods used by data scientists including; statistical thinking and conditional probability, machine learning and algorithms, and effective approaches for data visualization
- The major components of the Internet of Things (IoT) and the potential of IoT to totally transform the way in which we live and work in the not-to-distant future
- How data scientists are using natural language processing (NLP), audio and video processing to extract useful information from books, scientific articles, twitter feeds, voice recordings, YouTube videos and much more
Program Class List
1Statistical Thinking for Data Science and Analytics
Course Details
1
Learn how statistics plays a central role in the data science approach.
2Machine Learning for Data Science and Analytics
Course Details
2
Learn the principles of machine learning and the importance of algorithms.
3Enabling Technologies for Data Science and Analytics: The Internet of Things
Course Details
3
Discover the relationship between Big Data and the Internet of Things (IoT).
Meet your instructors
Tian Zheng
About Me
Tian Zheng is associate professor of Statistics at Columbia University. She obtained her PhD from Columbia in 2002. Her research is to develop novel methods and improve existing methods for exploring and analyzing interesting patterns in complex data from different application domains. Her current projects are in the fields of statistical genetics, bioinformatics and computational biology, feature selection and classification for high dimensional data, and network analysis. Especially, Dr. Zheng have been developing statistical and computational tools for high dimensional data, searching for genetic interactions associated with complex human disorders, quantifying social structure and studying hard-to-reach populations using survey questions, with more than 40 peer-reviewed publications in journals including JASA, AOAS and PNAS. Her work was recognized with the 2008 Outstanding Statistical Application Award from the American Statistical Association, The Mitchell Prize from ISBA and a Google research award. She is on the editorial board of Statistical Analysis and Data Mining and Frontier in Genetics. She was Associate Editor for JASA from 2007 to 2013.
Kathy McKeown
About Me
A leading scholar and researcher in the field of natural language processing, McKeown focuses her research on big data; her interests include text summarization, question answering, natural language generation, multimedia explanation, digital libraries, and multilingual applications. Her research group's Columbia Newsblaster, which has been live since 2001, is an online system that automatically tracks the day's news, and demonstrates the group's new technologies for multi-document summarization, clustering, and text categorization, among others. Currently, she leads a large research project involving prediction of technology emergence from a large collection of journal articles. McKeown joined Columbia in 1982, immediately after earning her Ph.D. from University of Pennsylvania. In 1989, she became the first woman professor in the school to receive tenure, and later the first woman to serve as a department chair (1998-2003).
Ansaf Salleb-Aouissi
Ansaf is a Lecturer in discipline of the Computer Science Department at the School of Engineering and Applied Science at Columbia University. She received her her BS in Computer Science in 1996 from the University of Science and Technology (USTHB), Algeria. She earned her masters and Ph.D. degrees in Computer Science from the University of Orleans (France) in 1999 and 2003 respectively.
Cliff Stein
About Me
His research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and computational biology. Professor Stein has published many influential papers in the leading conferences and journals in his field, and has occupied a variety of editorial positions including the journals ACM Transactions on Algorithms, Mathematical Programming, Journal of Algorithms, SIAM Journal on Discrete Mathematics and Operations Research Letters. His work has been supported by the National Science Foundation and Sloan Foundation. He is the winner of several prestigious awards including an NSF Career Award, an Alfred Sloan Research Fellowship and the Karen Wetterhahn Award for Distinguished Creative or Scholarly Achievement. He is also the co-author of the two textbooks. Introduction to Algorithms, with T. Cormen, C. Leiserson and R. Rivest is currently the best-selling textbook in algorithms and has sold over half a million copies and been translated into 15 languages. Discrete Math for Computer Scientists , with Ken Bogart and Scot Drysdale, is a new text book which covers discrete math at an undergraduate level.
David Blei
About Me
David Blei joined Columbia in Fall 2014 as a Professor of Computer Science and Statistics. His research involves probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference. He works on a variety of applications, including text, images, music, social networks, user behavior, and scientific data. Professor Blei earned his Bachelor's degree in Computer Science and Mathematics from Brown University (1997) and his PhD in Computer Science from the University of California, Berkeley (2004). Before arriving to Columbia, he was an Associate Professor of Computer Science at Princeton University. He has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), and Blavatnik Faculty Award (2013).
Itsik Peer
About Me
Itsik Pe’er is an associate professor in the Department of Computer Science. His laboratory develops and applies computational methods for the analysis of high-throughput data in germline human genetics. Specifically, he has a strong interest in isolated populations such as Pacific Islanders and Ashkenazi Jews. The Pe’er Lab has developed methodology to identify hidden relatives — primarily in such isolated populations — that involves inferring their past demography, detecting associations between phenotypes and genetic segments co-inherited from the joint ancestors of hidden relatives, and establishing the exceptional utility of whole-genome sequencing in population genetics. With the arrival of high-throughput sequencing methods, Pe’er has focused on characterizing genetic variation that is unique to isolated populations, including the effects of such variation on phenotype.
Mihalis Yannakakis
About Me
He studied at the National Technical University of Athens (Diploma in Electrical Engineering, 1975), and at Princeton University (PhD in Computer Science, 1979). He worked at Bell Labs Research from 1978 until 2001, as Member of Technical Staff (1978-1991) and as Head of the Computing Principles Research Department (1991-2001). He was Director of Computing Principles Research at Avaya Labs (2001-2002), and Professor of Computer Science at Stanford University (2002-2003). He joined Columbia University in 2004. His research interests include design and analysis of algorithms, complexity theory, combinatorial optimization, game theory, databases, and modeling, verification and testing of reactive systems.
Peter Orbanz
About Me
Before coming to New York, he was a Research Fellow in the Machine Learning Group of Zoubin Ghahramani at the University of Cambridge, and previously a graduate student of Joachim M. Buhmann at ETH Zurich. His main research interests are the statistics of discrete objects and structures: permutations, graphs, partitions, and binary sequences. Most of his recent work concerns representation problems and latent variable algorithms in Bayesian nonparametrics. More generally, he is interested in all mathematical aspects of machine learning and artificial intelligence.
Fred Jiang
Assistant Professor in the Electrical Engineering Department at Columbia University
Fred received his B.Sc. (2004) and M.Sc. (2007) in Electrical Engineering and Computer Science, and his Ph.D. (2010) in Computer Science, all from UC Berkeley. Before joining SEAS, he was Senior Staff Researcher and Director of Analytics and IoT Research at Intel Labs China. Fred’s research interests include cyber physical systems and data analytics, smart and sustainable buildings, mobile and wearable systems, environmental monitoring and control, and connected health & fitness. His ACme building energy platform has been widely adopted by universities and industries, including Lawrence Berkeley National Laboratory, National Taiwan University, and several commercial companies. His project on wearable and mobile fitness, in collaboration with University of Virginia, was featured on New Scientist and the Economist magazine. His air-quality monitoring project has been featured on China Central Television and People’s Daily, and was successfully incubated into a startup. He is actively serving on several technical and organizing committees including ACM SenSys, ACM/IEEE IPSN, and ACM BuildSys. He was a National Science Foundation (NSF) Graduate Fellow and a Vodafone-US Foundation Fellow.
Julia Hirschberg
Percy K. and Vida LW Hudson Professor of Computer Science at Columbia University
Julia Hirschberg does research in prosody, spoken dialogue systems, and emotional and deceptive speech. She received her PhD in Computer Science from the University of Pennsylvania in 1985. She worked at Bell Laboratories and AT&T Laboratories -- Research from 1985-2003 as a Member of Technical Staff and as a Department Head, creating the Human-Computer Interface Research Department at Bell Labs and moving with it to AT&T Labs. She served as editor-in-chief of Computational Linguistics from 1993-2003 and as an editor-in-chief of Speech Communication from 2003-2006. She is on the Editorial Board of Speech Communication and of the Journal of Pragmatics. She was on the Executive Board of the Association for Computational Linguistics (ACL) from 1993-2003, have been on the Permanent Council of International Conference on Spoken Language Processing (ICSLP) since 1996, and served on the board of the International Speech Communication Association (ISCA) from 1999-2007 (as President 2005-2007). She is currently the chair of the ISCA Distinguished Lecturers selection committee. She is on the IEEE SLTC, the executive board of the North American chapter of the Association for Computational Linguistics, the CRA Board of Directors, and the board of the CRA-W. She has been active in working for diversity at AT&T and at Columbia. She has been a fellow of the American Association for Artificial Intelligence since 1994, an ISCA Fellow since 2008, and became an ACL Fellow in the founding group in 2012. She received a Columbia Engineering School Alumni Association (CESAA) Distinguished Faculty Teaching Award in 2009, received an honorary doctorate (hedersdoktor) from KTH in 2007, is the 2011 recipient of the IEEE James L. Flanagan Speech and Audio Processing Award and, also received the ISCA Medal for Scientific Achievement in the same year.
Michael Collins
Vikram S. Pandit Professor of Computer Science at Columbia University
Michael J. Collins is a researcher in the field of computational linguistics. His research interests are in natural language processing as well as machine learning and he has made important contributions in statistical parsing and in statistical machine learning. One notable contribution is a state-of-the-art parser for the Penn Wall Street Journal corpus. His research covers a wide range of topics such as parse re-ranking, tree kernels, semi-supervised learning, machine translation and exponentiated gradient algorithms with a general focus on discriminative models and structured prediction.
Shih-Fu Chang
Richard Dicker Chair Professor at Columbia University
Shih-Fu Chang’s research interest is focused on multimedia retrieval, computer vision, signal processing, and machine learning. He and his students have developed some of the earliest image/video search engines, such as VisualSEEk, VideoQ, and WebSEEk, contributing to the foundation of the vibrant field of content-based visual search and commercial systems for Web image search. Recognized by many best paper awards and high citation impacts, his scholarly work set trends in several important areas, such as compressed-domain video manipulation, video structure parsing, image authentication, large-scale indexing, and video content analysis. His group demonstrated the best performance in video annotation (2008) and multimedia event detection (2010) in the international video retrieval evaluation forum TRECVID. The video concept classifier library, ontology, and annotated video corpora released by his group have been used by more than 100 groups. He co-led the ADVENT university-industry research consortium with the participation of more than 25 industry sponsors. He has received IEEE Signal Processing Society Technical Achievement Award, ACM SIGMM Technical Achievement Award, IEEE Kiyo Tomiyasu award, IBM Faculty award, and Service Recognition Awards from IEEE and ACM. He served as the general co-chair of ACM Multimedia conference in 2000 and 2010, Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), Chairman of Columbia Electrical Engineering Department (2007-2010), Senior Vice Dean of Columbia Engineering School (2012-date), and advisor for several companies and research institutes. His research has been broadly supported by government agencies as well as many industry sponsors. He is a Fellow of IEEE and the American Association for the Advancement of Science.
Zoran Kostic
About Me
Zoran Kostic completed his Ph.D. in Electrical Engineering at the University of Rochester and his Dipl. Ing. degree at the University of Novi Sad. He spent most of his career in industry where he worked in research, product development and in leadership positions. Zoran's expertise spans mobile data systems, wireless communications, signal processing, multimedia, system-on-chip development and applications of parallel computing. His work comprises a mix of research, system architecture and software/hardware development, which resulted in a notable publication record, three dozen patents, and critical contributions to successful products. He has experience in Intellectual Property consulting. Dr. Kostic is an active member of the IEEE, and he has served as an associate editor of the IEEE Transactions on Communications and IEEE Communications Letters.
Andrew Gelman
Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.
David Madigan
David Madigan received a bachelor’s degree in Mathematical Sciences and a Ph.D. in Statistics, both from Trinity College Dublin. He has previously worked for AT&T Inc., Soliloquy Inc., the University of Washington, Rutgers University, and SkillSoft, Inc. He has over 100 publications in such areas as Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance and probabilistic graphical models. He is an elected Fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently completed a term as Editor-in-Chief of Statistical Science.
Lauren Hannah
Lauren Hannah is an Assistant Professor in the Department of Statistics at Columbia University. Dr. Hannah received a Ph.D. in Operations Research and Financial Engineering from Princeton University, and an A.B. in Classics, again from Princeton University. After completing her Ph.D., Dr. Hannah completed a postdoc at Duke in the Statistical Science Department. Her interests include machine learning, Bayesian statistics, and energy applications.
Eva Ascarza
Eva Ascarza is an Assistant Professor of Marketing at Columbia Business School. She is a marketing modeler who uses tools from statistics and economics to answer marketing questions. Her main research areas are customer analytics and pricing in the context of subscription businesses. She specializes in understanding and predicting changes in customer behavior, such as customer retention and usage. Another stream of her research focuses on developing statistical methodologies to be used by marketing practitioners. She received her PhD from London Business School (UK) and a MS in Economics and Finance from Universidad de Navarra (Spain).
James Curley
About Me
Dr. Curley has very broad interests in behavioral development. He has conducted and published research at molecular, systems, organismal and evolutionary levels of analysis in both animals and humans. The focus of Dr. Curley’s lab at Columbia is on the development of social behavior. Dr. Curley is interested in how both inherited genetic variability and social experiences during development can shift individual differences in various aspects of social behavior and what the neuroendocrinological basis of these differences may be. He also researches the reliability and validity of social behavioral tests conducted in the laboratory and whether it is possible to utilize alternative statistical and methodological approaches to more appropriately assess social behavior. Dr Curley believes that it is critical to understand how the 'social brains' of humans and other animals have been differentially shaped by evolution and to acknowledge how this should better inform translational research.
About This Course:
Professional Certificate in Data Science for Executives
Learn the foundations and power of data science
Statistical Thinking for Data Science and Analytics
Machine Learning for Data Science and Analytics
Enabling Technologies for Data Science and Analytics: The Internet of Things
Meet Your Instructors:
Ansaf Salleb-Aouissi
Ansaf is a Lecturer in discipline of the Computer Science Department at the School of Engineering and Applied Science at Columbia University. She received her her BS in Computer Science in 1996 from the University of Science and Technology (USTHB), Algeria. She earned her masters and Ph.D. degrees in Computer Science from the University of Orleans (France) in 1999 and 2003 respectively.
Cliff Stein
About Me
His research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and computational biology. Professor Stein has published many influential papers in the leading conferences and journals in his field, and has occupied a variety of editorial positions including the journals ACM Transactions on Algorithms, Mathematical Programming, Journal of Algorithms, SIAM Journal on Discrete Mathematics and Operations Research Letters. His work has been supported by the National Science Foundation and Sloan Foundation. He is the winner of several prestigious awards including an NSF Career Award, an Alfred Sloan Research Fellowship and the Karen Wetterhahn Award for Distinguished Creative or Scholarly Achievement. He is also the co-author of the two textbooks. Introduction to Algorithms, with T. Cormen, C. Leiserson and R. Rivest is currently the best-selling textbook in algorithms and has sold over half a million copies and been translated into 15 languages. Discrete Math for Computer Scientists , with Ken Bogart and Scot Drysdale, is a new text book which covers discrete math at an undergraduate level.
David Blei
About Me
David Blei joined Columbia in Fall 2014 as a Professor of Computer Science and Statistics. His research involves probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference. He works on a variety of applications, including text, images, music, social networks, user behavior, and scientific data. Professor Blei earned his Bachelor's degree in Computer Science and Mathematics from Brown University (1997) and his PhD in Computer Science from the University of California, Berkeley (2004). Before arriving to Columbia, he was an Associate Professor of Computer Science at Princeton University. He has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), and Blavatnik Faculty Award (2013).
Itsik Peer
About Me
Itsik Pe’er is an associate professor in the Department of Computer Science. His laboratory develops and applies computational methods for the analysis of high-throughput data in germline human genetics. Specifically, he has a strong interest in isolated populations such as Pacific Islanders and Ashkenazi Jews. The Pe’er Lab has developed methodology to identify hidden relatives — primarily in such isolated populations — that involves inferring their past demography, detecting associations between phenotypes and genetic segments co-inherited from the joint ancestors of hidden relatives, and establishing the exceptional utility of whole-genome sequencing in population genetics. With the arrival of high-throughput sequencing methods, Pe’er has focused on characterizing genetic variation that is unique to isolated populations, including the effects of such variation on phenotype.
About This Course:
The Internet of Things is rapidly growing. It is predicted that more than 25 billion devices will be connected by 2020.
In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors. You will also examine ways of analyzing event data, sentiment analysis, facial recognition software and how data generated from devices can be used to make decisions.
What You’ll Learn:
- Networks, protocols and basic software for the Internet of Things (IoT)
- How automated decision and control can be done with IoT technologies
- Discuss devices including sensors, low power processors, hubs/gateways and cloud computing platforms
- Learn about the relationship between data science and natural language and audio-visual content processing
- Study research projects drawn from scientific journals, online media, and novels
- Review fundamental techniques for visual feature extraction, content classification and high-dimensional indexing
- Techniques that can be applied to solve problems in web-scale image search engines, face recognition, copy detection, mobile product search, and security surveillance
- Examine data collection, processing and analysis
Prerequisites:
- High school math
- Some exposure to computer programming
Professional Certificate in Data Science for Executives
Learn the foundations and power of data science
Statistical Thinking for Data Science and Analytics
Machine Learning for Data Science and Analytics
Enabling Technologies for Data Science and Analytics: The Internet of Things
Meet Your Instructors:
Fred Jiang
Assistant Professor in the Electrical Engineering Department at Columbia University
Fred received his B.Sc. (2004) and M.Sc. (2007) in Electrical Engineering and Computer Science, and his Ph.D. (2010) in Computer Science, all from UC Berkeley. Before joining SEAS, he was Senior Staff Researcher and Director of Analytics and IoT Research at Intel Labs China. Fred’s research interests include cyber physical systems and data analytics, smart and sustainable buildings, mobile and wearable systems, environmental monitoring and control, and connected health & fitness. His ACme building energy platform has been widely adopted by universities and industries, including Lawrence Berkeley National Laboratory, National Taiwan University, and several commercial companies. His project on wearable and mobile fitness, in collaboration with University of Virginia, was featured on New Scientist and the Economist magazine. His air-quality monitoring project has been featured on China Central Television and People’s Daily, and was successfully incubated into a startup. He is actively serving on several technical and organizing committees including ACM SenSys, ACM/IEEE IPSN, and ACM BuildSys. He was a National Science Foundation (NSF) Graduate Fellow and a Vodafone-US Foundation Fellow.
Michael Collins
Vikram S. Pandit Professor of Computer Science at Columbia University
Michael J. Collins is a researcher in the field of computational linguistics. His research interests are in natural language processing as well as machine learning and he has made important contributions in statistical parsing and in statistical machine learning. One notable contribution is a state-of-the-art parser for the Penn Wall Street Journal corpus. His research covers a wide range of topics such as parse re-ranking, tree kernels, semi-supervised learning, machine translation and exponentiated gradient algorithms with a general focus on discriminative models and structured prediction.
Shih-Fu Chang
Richard Dicker Chair Professor at Columbia University
Shih-Fu Chang’s research interest is focused on multimedia retrieval, computer vision, signal processing, and machine learning. He and his students have developed some of the earliest image/video search engines, such as VisualSEEk, VideoQ, and WebSEEk, contributing to the foundation of the vibrant field of content-based visual search and commercial systems for Web image search. Recognized by many best paper awards and high citation impacts, his scholarly work set trends in several important areas, such as compressed-domain video manipulation, video structure parsing, image authentication, large-scale indexing, and video content analysis. His group demonstrated the best performance in video annotation (2008) and multimedia event detection (2010) in the international video retrieval evaluation forum TRECVID. The video concept classifier library, ontology, and annotated video corpora released by his group have been used by more than 100 groups. He co-led the ADVENT university-industry research consortium with the participation of more than 25 industry sponsors. He has received IEEE Signal Processing Society Technical Achievement Award, ACM SIGMM Technical Achievement Award, IEEE Kiyo Tomiyasu award, IBM Faculty award, and Service Recognition Awards from IEEE and ACM. He served as the general co-chair of ACM Multimedia conference in 2000 and 2010, Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), Chairman of Columbia Electrical Engineering Department (2007-2010), Senior Vice Dean of Columbia Engineering School (2012-date), and advisor for several companies and research institutes. His research has been broadly supported by government agencies as well as many industry sponsors. He is a Fellow of IEEE and the American Association for the Advancement of Science.
Julia Hirschberg
Percy K. and Vida LW Hudson Professor of Computer Science at Columbia University
Julia Hirschberg does research in prosody, spoken dialogue systems, and emotional and deceptive speech. She received her PhD in Computer Science from the University of Pennsylvania in 1985. She worked at Bell Laboratories and AT&T Laboratories -- Research from 1985-2003 as a Member of Technical Staff and as a Department Head, creating the Human-Computer Interface Research Department at Bell Labs and moving with it to AT&T Labs. She served as editor-in-chief of Computational Linguistics from 1993-2003 and as an editor-in-chief of Speech Communication from 2003-2006. She is on the Editorial Board of Speech Communication and of the Journal of Pragmatics. She was on the Executive Board of the Association for Computational Linguistics (ACL) from 1993-2003, have been on the Permanent Council of International Conference on Spoken Language Processing (ICSLP) since 1996, and served on the board of the International Speech Communication Association (ISCA) from 1999-2007 (as President 2005-2007). She is currently the chair of the ISCA Distinguished Lecturers selection committee. She is on the IEEE SLTC, the executive board of the North American chapter of the Association for Computational Linguistics, the CRA Board of Directors, and the board of the CRA-W. She has been active in working for diversity at AT&T and at Columbia. She has been a fellow of the American Association for Artificial Intelligence since 1994, an ISCA Fellow since 2008, and became an ACL Fellow in the founding group in 2012. She received a Columbia Engineering School Alumni Association (CESAA) Distinguished Faculty Teaching Award in 2009, received an honorary doctorate (hedersdoktor) from KTH in 2007, is the 2011 recipient of the IEEE James L. Flanagan Speech and Audio Processing Award and, also received the ISCA Medal for Scientific Achievement in the same year.
