Research and TA / CA Opportunities
Zoran Kostic, Professor of Professional Practice, zk2172(at)columbia.edu
Electrical Engineering Department, Data Sciences Institute, Columbia University in the City of New York
Postdoctoral position opening link.
Current opportunities for research and teaching TA/CAs, for Columbia University students. To express interest/apply - see below.
Deep Learning Projects
AI for Smart Cities and Digital Twins
Applications to project COSMOS -> link, link, link, link
Cloud-connected vehicles
Smart city intersections
Smart-city navigation
Real time
Object Detection and Tracking
Medical applications - Peripheral edema detection
Medical applications - Using speech and language to identify patients at risk for hospitalizations and emergency department visits in homecare
Medical applications - AI in surgery
IoT Projects
Physical data analytics: developing algorithms based on Amazon AWS, python and Google tools
Course development: Intel Edison or Raspberry PI - deployment of new use cases.
High resolution indoor localization
Medical applications
Parallel Computing - GPU and Heterogeneous Computing Projects
Implementation and optimization of algorithms used in internet of things and deep learning
Using Nvidia processors and OpenCL and CUDA languages.
Current opportunities for research of TA/CAs, for Columbia University students.
Announced at -> link (lionmail account required).
Instructions how to apply/express interest in doing a research project or taking a TA/CA position.
Do the following two things:
Populate the following questionnaire ->: Student Interest in Research or TA / CA with Prof. Kostic
Send email to zk2172@columbia.edu with this subject: Student Interest in Research or TA / CA with Prof. Kostic.
(a) Attach CV, transcripts from BS degrees, and grades at Columbia University
(b) Copy the following questions and answer them
Last Name:
First Name:
CUID/UNI (as in zk2172):
Major at Columbia (EE, CS, ...):
Degree pursuing and semester (as in BS, MS, PhD, 1, 2, 3rd semester):
Columbia graduate-level GPA:
Undergraduate school, major and GPA: (as in Rutgers university, EE, 3.88/4)
What course did you take with Prof. Kostic, which grade did you get (Example: 6765, A-)
Enter research projects that you are interested in:
Are you interested in course assistant position (Yes/No + course name):
Number of credits taking this semester (3,6,9,12, other), outside of this activity:
Teaching and Course Assistant (TA/CA) Opportunities
Deep Learning on the Edge (EECS E6692 TPC - Topics in Data-driven Analysis and Computation)
Advanced Deep Learning (EECS E6691 TPC - Topics in Data-driven Analysis and Computation)
Heterogeneous Computing for Signal and Data Processing (EECS E4750)
Internet of Things - Systems and Physical Data Analytics (EECS E6765)
Internet of Things - Engineering Innovations and Commercialization (EECS E6766)
Digital Communications(ELEN E4702)
Electronic Circuits (ELEN E3331)