SCHEDULING YOUR DEFENSE

Thesis Defenses are open to the public and must be scheduled in advance to ensure they meet all administrative requirements for graduation. 
 
STEP 1 – IDENTIFY THESIS DATE & TIME
At least five weeks (5) before your defense, work with your committee to identify a date and time everyone is available for your thesis defense. 
 
STEP 2 – SCHEDULING REQUEST
As soon as possible, but no later than two (2) weeks prior to your defense, please complete this form with the information listed in the format demonstrated by the example below.
 
STEP 3 – CONFIRMATION & NEXT STEPS
Staff from the department will email you back with instructions and confirmation of a reserved room for your thesis. With the information provided, they will also post public announcements and send you and your committee all necessary forms to be completed for your thesis defense.
 
Current Deadlines for Master’s Theses can be found here.
Any specific questions can be sent to grad@calpoly.edu. 

To be more transparent in what the CSSE department does during a student’s thesis proposal, we offer a general overview to the stages of the process: what you do and what the CSSE Office does on your behalf.
If at any point you have questions, feel free to email us at computer-science@calpoly.edu or see us in our office 14-254.

 Stage 1: Choosing a Date/Time and Room Request

1) Student: Reach out to your committee and find a date and time that works for everyone for your thesis proposal presentation.  

2) Student: Fill out the Thesis Defense Scheduling form on the CSSE website to request the date and time discussed for your defense. The form requires all necessary information to move you forward through the process.  

  • Schedule no later than 2 weeks before your desired thesis defense date so we can prioritize a room’s availablity for you.  
  • Make sure your Committee Chair is listed first in the form’s entry field. 

3) Office: The CSSE office staff will reach out via email with your approved reserved date and time with a room and location.    

4) Student: We will also provide a link to the Culminating Experience Form adobe sign when scheduling your defense.  

  • This form will be completed FOLLOWING your thesis defense, but PRIOR to submitting your thesis.
Stage 2: Prep Time 

1) Office: We create a flyer for you using a template with your name, thesis title, abstract, date and time, location, and your committee members.  

2) During this time leading up to your presentation day, if any changes need to be made, reach out to us as soon as possible.
  

Stage 3 – One Week Before Defense  

1) Office + Committee: CSSE Staff will email your thesis defense flyer and relevant forms to be completed by committee members to your committee group. 

2) Office: We will post your event flyers on all CSSE building bulletin boards.   

3) Office: We will send an email with your flyer to all CSSE grad students, the CSSE department staff and faculty, the Dean’s office, and your committee members outside the CSSE department. 

– We also send out another reminder email the day before!  
 
Stage 4 – Thesis Defense Day 

1) Your requested room should be unlocked, prepped, and arranged for your proposal start time.

  • Please see the office staff if there are any difficulties accessing your reserved space. 
  • If no classes are in session, you may access the room early for set up needed.
Stage 5 – Completed Defense 

1) Student: Once your thesis defense is finished, you must complete and submit the Culminating Experience Approval form in our previous emails. This will be submitted prior to submitting your thesis.

🎉 Congrats, you did it! 🎉

Example Formatting for Thesis Defense Information

Preferred Name: Jane Mustang
Thesis date: 05/27/27
Requested Start Time: 12pm
End Time: 2pm
Committee Members: Dr. Khosmood, Dr. Kurfess, Dr. Gonzalez-Sanchez
Thesis Location: Need a room for thesis / Do not need a room for thesis 
Zoom link (if applicable): paste zoom link here, or leave blank
 
Thesis Title: Feature-Selected Gradient Boosting Outperforms Parametric Baselines for Genomic Prediction of Mastitis Susceptibility
Abstract:  
Predicting complex disease traits, such as mastitis, from high-dimensional genomic 
data is a significant challenge in modern dairy cattle breeding. Traditional genomic selection models, including mixed linear models and Bayesian approaches, are industry standards but may not fully capture complex, non-linear interactions within the genome. This study investigates the potential of machine learning models, particularly Transformer and tree-based architectures, to improve prediction accuracy. Using a covariate-residualized feature-selection pipeline, we compare Transformer, Random Forest, and LightGBM models against GBLUP and BayesR in 1,860 first-lactation cows (93 clinical mastitis cases) genotyped at 624,300 SNPs…(shortened for this example email).