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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Student Achievements
    The Next Generation of IP Multimedia Communications co authors Henning Schulzrinne Srisakul Thakolsri Wolfgang Kellerer advisor Henning Schulzrinne Charles Shen Best Student Paper Award 2008 IPTComm Conference SIP Server Overload Control Design and Evaluation co author Henning Schulzrinne advisor Henning Schulzrinne Matei Ciocarlie Best Student Paper Award 2007 IEEE Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems Soft Finger Model with Adaptive Contact Geometry for Grasping and Manipulation Tasks co authors C Lackner and Peter Allen advisor Peter Allen Sean White CHI Best Note Award 2007 ACM CHI Conference Designing a mobile user interface for automated species identification co authors Dominic Marino and Steven Feiner advisor Steven Feiner Alp Atici Mathematics Dept E M Gold Award for Best Student Paper 2006 Conference on Algorithmic Learning Theory ALT 06 Learning Unions of ω 1 Dimensional Rectangles co author Rocco Servedio advisor Rocco Servedio Seung Geol Choi Best Student Paper Award 2006 International Workshop on Security IWSEC 06 Short Traceable Signatures Based on Bilinear Pairings co authors Kunsoo Park and Yung Moti advisor Tal Malkin Alex Haubold Best Poster Award 2006 IEEE International Conference and Multimedia Expo ICME 06 Semantic Multimedia Retrieval using Lexical Query Expansion and Model Based Reranking Advisor John R Kender Homin K Lee Andrew Wan Mark Fulk award for Best Student Paper 2006 Conference on Learning Theory COLT 06 DNF are Teachable in the Average Case co author Rocco Servedio co advisors Tal Malkin and Rocco Servedio Cristian Soviani Best Paper Award 2006 Design Automation and Test in Europe DATE 06 Optimizing Sequential Cycles through Shannon Decomposition and Retiming co authors Olivier Tardieu Stephen A Edwards advisor Stephen A Edwards Panagiotis Ipeirotis Best Paper Award 2005 21st IEEE International Conference on Data Engineering ICDE 05 Modeling and Managing Content Changes in Text Databases co authors Alexandros Ntoulas Junghoo Cho Luis Gravano advisor Luis Gravano Ricardo Barratto Shaya Potter Gong Su MobiCom Best Student Paper Award 2004 ACM International Conference on Mobile Computing and Networking MobiCom 04 MobiDesk Mobile Virtual Desktop Computing co author Jason Nieh advisor Jason Nieh Vlad Branzoi Best Paper Award 2004 IEEE Conference on Computer Vision and Pattern Recognition Programmable Imaging using a Digital Micromirror Array co authors Shree K Nayar Terry E Boult advisor Shree Nayar Eugene Agichtein Best Student Paper Award 2003 19th IEEE International Conference on Data Engineering ICDE 03 Querying Text Databases for Efficient Information Extraction co author Luis Gravano advisor Luis Gravano Risi Kondor Best Student Paper Award 2003 International Conference on Machine Learning ICML 03 A Kernel Between Sets of Vectors co author Tony Jebara advisor Tony Jebara Andrew T Miller Best Manipulation Paper Award 2003 IEEE International Conference on Robotics and Automation Automatic Grasp Planning using Shape Primitives co authors Steffen Knoop Henrik I Christensen and Peter K Allen advisor Peter Allen Blaine Bell Tobias Hoellerer Best Student Paper Award 2001 Proceedings of UIST ACM Symposium on User Interface Software and Technology UIST 01 View Management for Virtual and Augmented Reality co author Steven Feiner advisor

    Original URL path: http://www.cs.columbia.edu/research/achievements/students (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Application Information
    is required For IELTS 7 is the minimum score for admission My TOEFL IELTS and or GRE scores will expire right around the time of MS application deadline Do I need to retake the exam We highly recommend you to retake the test as your test scores must be valid for the admissions review How long are my TOEFL IELTS and or GRE scores valid for TOEFL and IELTS scores are valid from two years from the date the test was taken GRE scores are valid for five years I have entered my TOEFL IELTS and GRE test scores on my online application Do I still have to submit an official score report to Columbia Yes you must report your scores on your application and must request ETS or IELTS to send official scores directly to Columbia University I have sent my official TOEFL IELTS and GRE test scores to the specified address Do I still have to report the scores on my online application Yes you must complete the test score sections of the online application Transcript My transcripts are not in English What should I do Your transcripts need to be translated by an official and notarized transcription agency This is your responsibility and the CS department cannot provide referrals My course grades on my undergraduate transcript are based on a different scale from Columbia s What can I do You must have your transcript converted to the GPA scale by an appropriate agency GPA is on a 0 4 scale before sending it to the SEAS Graduate Student Services It is your responsibility to find an agency that can do this conversion for you The CS department cannot provide referrals Recommendation Letters My recommenders cannot submit their letters of recommendation electronically Can I have them sent as hard copies via mail We require electronic submission of recommendations Can my recommenders send letters of recommendation from their non institutional email addresses e g Gmail Hotmail Yahoo The email address should correspond to the main institution e g university or company with which the recommendation provider is affiliated Please avoid entering email addresses from providers such as Yahoo Hotmail Gmail etc Financial Support Document Do I need to submit the financial document along with my application You will be asked to submit the financial statement after you are accepted into the program So there is no need for you to submit it before the decision is made Technical Problems I m having problems entering data and or uploading documents in the online application system what can I do Make sure your internet browser is the most up to date version as possible older versions can cause problems with the system Try working on a different computer if your problems persist Make sure you are not attempting to upload non supported file formats If you still have a problem please notify the Being forwarded to the MS application pool from the PhD application pool I applied to the PhD program

    Original URL path: http://www.cs.columbia.edu/education/ms/appfaq (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Computational Biology
    GPA in order to be eligible for the MS degree in Computer Science Computational Biology track requires Breadth courses Required Track courses 6pts Track Electives 6pts General Electives 6pts 2 required courses 6 points COMS W4761 Computational Genomics and either COMS W4771 or SIEO W4150 6 elective points at the 6000 level at least 3 of these 6000 level points must be selected from the list of Elective Track Courses 6 credits of general elective graduate courses at 4000 level or above at least 3 of these points must be CS graduate courses At least 3 elective points must be selected from courses in biological departments Students who waive track requirements using previous courses may complete the 30 graduate credits by expanding their electives selected from a the list of required track courses b the list of elective track courses or c other graduate courses Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breadth requirement page for more information 2 Required Track Courses Students are required to complete the following courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title COMS W4761 Computational Genomics Students are required to complete 1 of the following courses Course ID Title COMS W4771 Machine Learning SIEO W4150 Probability and Statistic 3 Elective Track Courses Students are required to take 2 courses from the following list at least one of which must be a 6000 level course Other courses on this list may be used as general electives or waiver replacements when the student has received a waiver Course ID Title COMS W4111 Introduction to Databases COMS W4252 Introduction to Computational Learning Theory COMS W4772 E6772 Advanced Machine Learning COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track COMS E6111 Advanced Database Systems COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track BIOC W4512 Molecular Biology BIOL W4031 Genetics I BIOL W4032 Genetics II BIOL W4034 Biotechnology BIOL W4037 Bioinformatics of Gene Expression BIOL W4041 Cell Biology BIOL W4070 The Biology and Physics of Single Molecules BIOL W4300 Drugs and Disease BIOL W4073 Cellular and Molecular Immunology BIOL W4400 Biological Networks BIOL W4510 Molecular Systems Biology I BCHM G4026 Biochemistry of Nucleic and Protein Synthesis BCHM G4250 Biochemistry and Molecular Biophysics BCHM G6300 Biochemistry and Molecular Biology of Eukaryotes I BCHM G6301 Biochemistry and Molecular Biology of Eukaryotes II BMEN E6480 Computational Neural Modeling and Neuroengineering GEND G4050 Advanced Eukaryotic Molecular Genetics STAT G6101 Statistical Modeling and Data Analysis APMA E4400 Introduction to Biophysical Modeling BINF G4006 Translational Bioinformatics BINF G4014 Computational Biology I Functional and Integrative Genomics BINF G4015 Computational Biology II Proteins Networks Function EECS E6894 Deep Learning for Computer Vision and Natural Language Processing 4 General Electives Students are required

    Original URL path: http://www.cs.columbia.edu/education/ms/computationalBiology (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | New Computer Security
    pts selected from the list of Elective Track Courses at least 1 of these courses must be a 6000 level CS course 1 general elective graduate CS course 3 pts at 4000 level or above Must have 6 points at the 6000 level at least 3 of these 6000 level points must be selected from the list of Elective Track Courses Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breadth requirement page for more information 2 Required Track Courses Students are required to complete the following 5 courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title COMS W4118 Operating Systems COMS W4156 Adv Software Engineering COMS W4180 Network Security COMS W4187 Security Architecture and Engineering Either COMS W4261 or COMS E6185 Introduction to Cryptography or Intrusion Detection 3 Elective Track Courses Students are required to complete 2 courses out of the following list at least one course must be 6000 level Please note that courses with are offered alternate years Course ID Title COMS W4115 Programming Languages and Translators COMS W4119 Computer Networks COMS W4261 Introduction to Cryptography COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track COMS E6118 Operating Systems II COMS E6181 Advanced Internet Services COMS E6183 Security COMS E6184 Privacy Anonymity COMS E6185 Intrusion and Anomaly Detection Systems COMS E6261 Advanced Cryptography COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track CSEE W4824 Computer Architecture ELEN E4703 Wireless Communications ELEN E6761 Computer Communication Networks ELEN E6886 Topics in Multimedia Security ELEN E6950 Wireless Mobile

    Original URL path: http://www.cs.columbia.edu/education/ms/newcomputerSecurity (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Foundations
    qualifying graduate course 4000 and 6000 level Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breadth requirement page for more information 2 Required Track Courses Students are required to complete the following courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title CSOR W4231 Analysis of Algorithms I COMS W4236 Intro to Computational Complexity 3a Track Program Electives I Students are required to complete 1 of the following courses Course ID Title COMS W4203 Graph Theory COMS W4205 Combinatorial Theory COMS W4241 Numerical Algorithms and Complexity COMS W4252 Introduction to Computational Learning Theory COMS W4261 Introduction to Cryptography COMS W4281 Introduction to Quantum Computing 3b Track Program Electives II Students are required to complete 9 points out of the following list excluding the course already taken at least 6 points must be at the 6000 level Course ID Title COMS W4203 Graph Theory COMS W4205 Combinatorial Theory COMS W4241 Numerical Algorithms and Complexity COMS W4252 Introduction to Computational Learning Theory COMS W4261 Introduction to Cryptography COMS W4281 Introduction to Quantum Computing CSEE E6180 Performance Analysis COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track COMS E6204 Topics in Graph Theory COMS E6232 Analysis of Algorithms II COMS E6253 Computational Learning Theory II COMS E6261 Advanced Cryptography COMS E6291 Theoretical Topics in C S COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track CSPH G4802 Incompleteness Results in Logic SIEO W4150 Intro to Probability and Statistics IEOR E4407 Game Theoretic Models of Operation IEOR E6400 Scheduling Deterministic Models IEOR

    Original URL path: http://www.cs.columbia.edu/education/ms/foundationsOfCS (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Machine Learning
    courses or c other graduate courses Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breath requirement page for more information 2 Required Track Courses Students are required to complete 2 of the following courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title COMS W4252 Introduction to Computational Learning Theory COMS W4771 or COMS W4721 Machine Learning Machine Learning for Data Science COMS W4772 Advanced Machine Learning COMS STAT G6509 Foundations of Graphical Models This course is an advanced course but MS students may register for it with instructor approval Due to significant overlap students can receive credits for only one of these courses either COMS W4771 Machine Learning or COMS W4721 Machine Learning for Data Science 3 Elective Track Courses Students are required to take 2 courses from the following list at least one of which must be a 6000 level course Other courses on this list may be used as General Electives or to replace required track courses when the student has received a waiver Course ID Title COMS W4111 Introduction to Databases COMS W4252 Introduction to Computational Learning Theory CSOR W4246 Algorithms for Data Science COMS W4705 Intro to Natural Language Processing COMS W4731 Computer Vision COMS W4733 Computational Aspects of Robotics COMS W4737 Biometrics COMS W4761 Computational Genomics COMS W4771 or COMS W4721 Machine Learning Machine Learning for Data Science COMS W4772 Advanced Machine Learning COMS W4776 Machine Learning for Data Science COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track COMS E6111 Advanced Database Systems COMS E6232 Analysis of Algorithms II COMS E6253 Advanced Topics in Computational Learning Theory COMS E6717 ELEN E6717 Information Theory COMS E6735 Visual Databases COMS E6737 Biometrics COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track CSEE E6892 Bayesian Models in Machine Learning CSEE E6898 Large Scale Machine Learning CSEE E6898 Sparse Signal Modeling APMA E4990 Modeling Social Data BINF G4006 Translational Bioinformatics EEBM E6040 Neural Networks and Deep Learning EECS E6870 Speech Recognition EECS E6893 Big Data Analytics EECS E6895 Topic Adv Big Data Analytics EECS E6894 Deep Learning for Computer Vision and Natural Language Processing IEOR E6613 Optimization I IEOR E8100 Optimization Methods in Machine Learning IEOR E8100 Big Data Machine Learning MECS E6615 Advanced Robotic Manipulation SIEO 4150 or STAT W4201 Probability and Statistics Advanced Data Analysis STAT W4240 Data Mining STAT W4249 Applied Data Science STAT G4400 Statistical Machine Learning STAT W4640 Bayesian Statistics STAT W4700 Probability and Statistics STAT G6101 Statistical Modeling and Data Analysis I STAT G6104 Computational Statistics Due to a significant overlap in course material students in the Machine Learning track can only take 1 of the following courses ELEN 4903 IEOR 4525 STAT 4240 STAT 4400 as a track

    Original URL path: http://www.cs.columbia.edu/education/ms/machineLearning (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Network Systems
    of Elective Track Courses at least 2 of these courses must be 6000 level CS courses 1 general elective One Columbia Computer Science graduate course 3 points at 4000 level or above Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breadth requirement page for more information 2 Required Track Courses Students are required to complete the following courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title CSEE W4119 Computer Networks COMS W4118 Operating Systems COMS W4115 Programming Languages and Translators 3 Elective Track Courses Students are required to complete 4 courses out of the following list at least 2 courses must be 6000 level CS courses Course ID Title CSEE W4140 Networking Laboratory COMS W4180 Intro to Network Security COMS W4261 Intro to Cryptography COMS W4737 Biometrics COMS W4995 Visit the topics courses page to see which COMS 4995 courses apply to this track COMS E6118 Operating Systems II COMS E6125 Web enhanced Info Management Whim COMS E6180 Modeling Performance COMS E6181 Advanced Internet Services COMS E6184 Anonymity and Privacy COMS E6185 Intrusion and Anomaly Detection Systems COMS E6717 ELEN E6717 Information Theory COMS E6737 Biometrics COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply to this track ELEN E4703 Wireless Communications ELEN E6761 Computer Communication Networks ELEN E6770 Next Generation IP Networks ELEN E6771 Next Generation Networks ELEN E6950 Wireless Mobile Nets I ELEN E6951 Wireless Mobile Nets II SIEO STAT W4606 Elementary Stochastic Processes or substitute with IEOR W4106 IEOR E6704 Queueing Theory and Applications IEOR E6801 Monte Carlo Discrete Event Simulation IEOR E4406 Facilities Location

    Original URL path: http://www.cs.columbia.edu/education/ms/networkSystems (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | NLP
    points at 4000 level or above Please use the Degree Progress Check to keep track of your requirements 1 Breadth Requirement Visit the breadth requirement page for more information 2 Required Track Courses Students are required to complete the following 3 courses Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead Course ID Title COMS W4705 Natural Language Processing COMS W4706 Spoken Language Processing COMS E6998 Topic courses that focus on NLP 3 Elective Track Courses Students are required to complete 2 courses out of the following list at least 1 course must be a 6000 level CS course Since other departments vary their offerings considerably from year to year it is possible to count such courses toward the MS degree please propose courses you think might be suitable to the track advisor Course ID Title COMS W4170 User Interface Design COMS W4172 3D User Interfaces COMS W4252 Introduction to Computational Learning Theory COMS W4771 or W4721 Machine Learning or Machine Learning for Data Science COMS W4772 Advanced Machine Learning COMS E6901 Projects in Computer Science COMS E6998 Visit the topics courses page to see which COMS 6998 courses apply as electives for this track SIEO W4150 Probability and Statistics ECBM E6040 Neural Networks and Deep Learning EECS E6894 Deep Learning for Computer Vision and Natural Language Processing ELEN E4810 Digital Signal Processing ELEN E6829 Speech Audio Processing Recognition PSYC G4232 Production and Perception of Language PSYC G4275 Contemporary Topics in Language and Communication PSYC G4205 Models of Cognition PSYC G4470 Psychology and Neuropsychology of Language PSYC G6006 Introduction to Statistical Modeling in Psychology Due to significant overlap students can receive credits for only one of these courses either COMS W4771 Machine

    Original URL path: http://www.cs.columbia.edu/education/ms/nlp (2016-02-17)
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