For Prospective Students,
We are looking for highly motivated students with responsibility and decency who are interested in Finance and Business Analytics with an emphasis on
Natural Language Processing
A student with the following undergraduate degree will be considered with priority:
Mathematics or Statistics (w/ programming skills in Python)
Computer Science and Engineering
「2023 Fall Admission」
One opening for Ph.D. or MS-PhD degree program
One opening for an M.Sc. degree program
An applicant must simultaneously satisfy the following two conditions to join the lab as a graduate student.
An applicant must receive permission to join the lab from the director before applying the graduate school.
Self-evaluate his/her eligibility based on the requirements below
Send an e-mail with a CV(w/ Github repo) and transcript to the director (jwsong at hanyang.ac.kr)
Deadline: One month before the beginning of each application process
Take an appointed interview with the director (no interview for non-eligible students)
Receive permission to join the lab via e-mail (permission does not guarantee admission)
Applicants must receive admission to the graduate school (industrial engineering).
Apply for the industrial engineering program at the graduate school of Hanyang University
Pass the oral exam
Receive admission to join the graduate school
Note: Students with higher scores and willingness to join the lab will have priority in case of an opening shortage.
① Applicants must have the undergraduate and graduate(if any) GPAs of
3.5(/4.5)* or above for the Ph.D. or MS-PhD degree program
3.75(/4.5)** or above for the M.Sc. or BS-MS degree program
② Applicants must have studied the following topics (or equivalent) during the (under)graduate coursework w/ B+ or above:
Probability & Statistics
Calculus & Linear algebra
Data structures & Algorithms
Database System (w/ Query)
Programming-related class (C(++), Java, or Python)
Stochastic Process (INE3080)
Investment Science & Portfolio Theory (INE2076)
Financial Engineering (INE3083)
Time-series Analysis & Forecasting (INE3098)
Data Mining & Analytics (INE5008, INE4108)
An undergraduate student who satisfies any of the following conditions is eligible for the undergraduate internship:
Admitted to the BS-MS program.
Assigned to a task for a specified period by the director.
Due to the limited capacity, the office space in the lab is not guaranteed for undergraduate interns.
Undergraduate interns can join the lab meeting and can present/discuss the progress of their tasks.
A stipend is only guaranteed for undergraduate interns in the BS-MS program.
Compensation is rewarded for the undergraduate interns engaged in projects.
[Basic Guidelines & Requirements]
Before graduation, a candidate must take following the classes (see the course details on THIS PAGE).
General requirements for all candidates:
INE3083 - Introduction to Financial Engineering (waiving possible)
INE6055 - Financial Engineering & Risk Management (waiving possible)
INE9102 - Stochastic Process
INE6056 - Advanced Time-series Analysis & Forecasting
Additional requirements for non-B.Sc in Industrial Engineering degree holder:
INE3079 - MSOR 1 (Optimization)
An individual-specific curriculum must be discussed w/ the director at the beginning of the degree program.
For more details, please check this [link]
PhD: 37 credits (w/ MS coursework & at least 17 credits from IE major classes)
MS-PhD: 58 credits (at least 26 credits from major courses)
Quals: Four topics from IE major classes (must be completed at least a semester before the Proposal)
Dissertation Requirements (pre-conditions for each phase)
Proposal: ① Quals passed, ② At least two articles accepted in SCIE/SSCI journal as a first author
Defense: ① Dissertation draft completed, ② Satisfy the research performance requirement of the College of Engineering (200%)
M.Sc./BS-MS: 26 credits (at least 11 credits from IE major classes)
Quals: Three topics from IE major classes (must be completed a semester before graduation)
① Quals passed, ② At least one article accepted in SCIE/SSCI journal as a first author before the department's thesis review date
Note that the published paper substitutes a master's thesis
「Code of Conduct」
Obligation to show regard and respect to other lab members
Any violence will not be tolerated
Flexible working time
Individual discussion regarding the base schedule at the beginning of the semester
Please be responsible for the assigned tasks (if any) and enjoy your self-managed free time!
Members in alternative military service (전문연구요원) must follow the rules in the Military Manpower Administration
Collaborative working environment
Notion - Task management & Wiki
Google Chat - Communications
Shared Google Drive - Main Database
Bi-Weekly Lab Meeting
The day of the week will be decided at the beginning of each semester and vacation.
Participation is mandatory!
[Stipends & Incentives]
The modest amount will be guaranteed as a base stipend based on research grants (e.g., NRF, BK, RA, TA, etc.)
Students engaged in projects will be compensated in proportion to their contributions and participation rates