WDSW Program

Sunday, June 9, 2019

Events on Sunday are in the Klaus Advanced Computing Building,
located at 266 Ferst Drive NW.

8:00–9:00: Continental Breakfast (Atrium)
9:00–9:15: Introductions (Atrium)
9:15–9:50: Fireside Chats (1116 E & W)
    • Moderator: Dana Randall
    • 9:15–9:35: Lakshmi V. Kalluri (Anthem)
    • 9:35–9:50: Brandeis Marshall (Spelman College)
10:00–11:00: Keynote Talk—Lo Li (CTO at Equifax) (1116 E & W)
11:15–12:15: Brief Overview Talks and Discussions (1116 E & W)
    • 11:15–11:30 + 15 min discussion: Ellen Zegura (GT)
    • 11:45–12:00 + 15 min discussion: Jennifer Priestley (KSU)
12:15–1:30: Lunch (Atrium)
1:30–2:30: Lightning Talks by Ph.D. Students (1116 E & W)
    •  Marissa Connor (Georgia Tech)
    •  Lili Zhang (Kennesaw)
    •  Yuliia Lut (Georgia Tech)
    •  Jie Hao, (Kennesaw)
    •  Tess Hellebrekers (CMU)
    •  Neda Tavakoli (Georgia Tech)
2:30–3:00: Break (Atrium)
3:00–5:00: Parallel Short Courses
    • Introduction to Bayesian Analysis by Yao Xie Chen (Classroom Wing, 2447) 
    • Introduction to Deep Neural Networks by Zsolt Kira (Classroom Wing, 2456)
​    • Machine Learning with TensorFlow by Rasmi Elasmar (Classroom Wing, 2443)

Monday, June 10, 2019

All events are in the Georgia Tech Hotel and Conference Center, located at 800 Spring Street NW, except the Monday night reception, which is in the Atrium of the Klaus Advanced Computing Building, located at 266 Ferst Drive NW.

8:00–9:00: Continental Breakfast (Conference Room 6)
9:00–1:00: Hackathon (Conference Rooms 6 & 7)

6:00–7:00: Reception (Klaus Advanced Computing Atrium)

MLSE Program

(Click here to view the detailed program, including track sessions.)

»Video recordings of plenary talks are available online.

Sunday, June 9, 2019

Events on Sunday are in the Klaus Advanced Computing Building,
located at 266 Ferst Drive NW.

3:00–5:00: Parallel Short Courses 
    • Introduction to Bayesian Analysis by Yao Xie Chen (Georgia Tech) (Classroom Wing, 2447) 
    • Introduction to Deep Neural Networks by Zsolt Kira (Georgia Tech) (Classroom Wing, 2456)
    • Machine Learning with TensorFlow by Rasmi Elasmar (Google) (Classroom Wing, 2443)

Monday, June 10, 2019

All events for MLSE are in the Georgia Tech Hotel and Conference Center, located at 800 Spring Street NW, except the Monday night reception, which is in the Atrium of the Klaus Advanced Computing Building, located at 266 Ferst Drive NW.

7:30: Registration (Second Foor, Open Area Outside Business Center—Located at Top of Main Stairs/Elevator)
8:00–9:00: Continental Breakfast (Grand Ballroom, Salon 3 & 4)

9:00–12:00: Parallel Sessions
12:00
–1:15: Lunch (Grand Ballroom, Salon 3 & 4)
    
• 12:10: Welcome & Introductions
        
• Dana Randall (Georgia Tech)
        • 
Chaouki Abdallah (Executive VP of Research, Georgia Tech) 
    
 • 12:15: Plenary Talk byJennifer Neville (Purdue)
—“Towards Relational AI: The Good, the Bad, and the Ugly of Learning over Networks”
1:15–2:00: Poster Session 
(Conference Room A)
2:00–3:30: Parallel Sessions (Various Locations)

3:30–4:00: Break

4:00–5:30: Parallel Sessions
(Various Locations)
6:00–7:00: Reception (Klaus Advanced Computing Building, Atrium)

Tuesday, June 11, 2019

7:30: Registration (Second Foor, Open Area Outside Business Center—Located at Top of Main Stairs/Elevator)
8:00–9:00: Continental Breakfast (Grand Ballroom, Salon 3 & 4)

9:00–12:00: Parallel Sessions (Various Locations)

12:15–1:15: Lunch with Plenary Talk—Eliu Antonio Huerta Escudero (UIUC) (Grand Ballroom, Salon 3 & 4)
1:15–2:00: Poster Session (Conference Room A)

2:00–3:30: Parallel Sessions (Various Locations)

3:30–4:00: Break

4:00–5:30: Parallel Sessions (Various Locations)

Wednesday, June 12, 2019

7:30: Registration (Second Foor, Open Area Outside Business Center—Located at Top of Main Stairs/Elevator)
8:00–9:00: Continental Breakfast (Grand Ballroom, Salon 3 & 4)
9:00–10:00: Plenary Talk by Daniel Neill (NYU)—“Machine Learning and Event Detection for Population Health” (Grand Ballroom, Salon 3 & 4)

10:00–11:00: Plenary Talk by John McDonald (GT)—“The Potential of Machine Learning for Improved Diagnostics and Treatment” (Grand Ballroom, Salon 3 & 4)
11:00–12:00: Crosscutting Parallel Discussions 

    •  Data Management (Grand Ballroom, Salon 3 & 4)

    •  Reproducibility in Machine Learning, Science, and Engineering (Conference Room A)
12:00–2:00: Lunch on Your Own
2:00–3:00: Plenary Talk by Ross Thomson (Google)—“Tools and Methods for Machine Learning” (Grand Ballroom, Salon 3 & 4)
3:00: Informal Discussions and Adjourn (Grand Ballroom, Salon 3 & 4)