Teaching

Courses Taught

• • Machine Learning

  • Machine Intelligence

  • Deep Learning and Artificial Intelligence

  • Artificial Intelligence and Big Data

  • Introduction to Data Analytics

  • Advanced Data Structures and Algorithms

  • Data Structures and Object-Oriented Programming

  • Data Structures, Algorithms, and Discrete Mathematics

  • Programming and Problem Solving

Supervised Student Capstone/Thesis 

(UG) - Undergraduate Student/(G) - Graduate Student, Graduation Time, Capstone/Thesis Title

1.     Esha Gavali (G), TBD

2.     Sugam Jaiswal (G), TBD

3.     Saurav Jayakumar (G), TBD

4.     Chloe Ma (G), TBD

5.     Remya Mavila (G), Summer 2023, “iCare - A Virtual Assistant for Mental Health”

6.     Aditya Duggirala (UG), Summer 2023, “Deep Tracer 3.0: A Proof of Concept”

7.     Amlak Takele (UG), Summer 2023, “Writing a Script to Remove Old Files from the Production Server”

8.     Chunyang Lu (UG), Spring 2023, “Protein-Ligand Binding Site Prediction and de Novo Ligand Generation from Cryo-EM Maps”

9.     Jason Chen (G), Spring 2023, “Protein Structure Refinement via DeepTracer and AlphaFold2”

10. Raghav Naswa (G), Spring 2023, “Conversational AI to Deliver Family Intervention Training for Mental Health Caregivers”

11. Jonathan Lee (G), Autumn 2022, “Psychosis iREACH: Reach for Psychosis Treatment using Artificial Intelligence”

12. Andrew Nakamura (G), Summer 2022, “Macromolecular Modeling: Integrating DNA/RNA into DeepTracer's Prediction Pipeline”

13. Luca Chang (UG), Spring 2022, “DeepTracer-ID Methods Development”

14. Kiernan Connolly (UG), Spring 2022, “DeepTracer-ID System Development”

15. Victor Suciu (UG), Spring 2022, “Macromolecular Segmentation, Testing and Research from Cryo-EM Images”

16. Skye Tran (UG), Spring 2022, “Psychosis iREACH Development”

17. Diem To (G), Winter 2022, “Traveler's Next Activity Prediction with Location-Based Social Network Data”

18. Rahil Mehta (G), Winter 2022, “CT Metal Artifact Reduction using Unpaired Image-to-Image Translation”

19. Nuoya Wang (G), Summer 2021, “Developing A Health Therapy Chatbot using Natural Language Processing”

20. Martin Sheung Him Chow (UG), Summer 2021, “Website Development for DeepTracer”

21. Nathan Ranno (G), Spring 2021, “Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation”

22. Ploypaphat Saltz (G), Spring 2021, “Dementia Detection using Transformer-Based Deep Learning and Natural Language Processing”

23. Navjodh Singh Dhillon (G), Winter 2021, “A Raspberry Pi Based Traumatic Brain Injury Detection System Using Machine Learning”

24. Agustinus Sutandi (G), Autumn 2020, “Detection of Traumatic Brain Injury Using Single Channel Electroencephalogram in Mice”

25. Tung Dinh (UG), Autumn 2020, "Mobile Development for Cocobot Health Care Empathy Chat Application"

26. Jonas Pfab (G), Summer 2020, “Deciphering Protein Complex Structure from Three-dimentional Cryo-electron Microscopy using Deep Learning”

27. Jerad Broc Hardman (UG), Summer 2020, “Data Collection and Filtering for DeepTracer”

28. Jayden Stipek (UG), Summer 2020, “Virtual Reality and Computer Vision at Vision 13”

29. Austin Landas (UG), Spring 2020, “Sleep AI on Parent Data”

30. Noah McMichael (UG), Spring 2020, “Iterative Method for CT Reconstruction with a Learned Regularization Term”

31. Nodira Povey (UG), Spring 2020, “Applying U-Net Model to Improve the Quality of Low Dose ​and Sparse-View CT Scans”

32. Cuong Vo (UG), Spring 2020, “Sleep AI: Machine Learning for Predicting Sleep Parameters”

33. Daniel Gallo (UG), Spring 2020, “Web Application Development for JIA Imaging Project”

34. Alan Burnett (G), Spring 2020, “Applications of Machine Learning to Aviation Accident Data”

35. Ruiwen Xing (G), Winter 2020, “Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images”

36. Safina Chaudhry (G), Winter 2020, “Automated Cognitive Decline Analysis Using Voice Features and Clinical Test Results”

37. Yue Chang (UG), Winter 2020, “Cross-platform Mobile App for JIA research project”

38. Bereket Habte (UG), Summer 2019, “Networking Technology”

39. Ryan Harlich (UG), Summer 2019, “3D Cryo-EM Data Mining and Deep Learning”

40. Rizky Ramdhani (G), Spring 2019, “Microservice-based Architecture Design and Deployment for Juvenile Idiopathic Arthritis Screening Service”

41. Spencer Moritz (G), Winter 2019, “Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps”

42. Todor Avramov (G), Winter 2019, “Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-Electron Microscopy Images”

43. Sean Coulter (UG), Winter 2019, “A Neural Network Approach to Denoise CT Images using U-Net”

44. Orpal Nagra (UG), Winter 2019, “TechX at T-Mobile”

45. Austin Abeyta (UG), Fall 2018, “Rythmgan - AI Music Composition”

46. Jeremiah Morse (UG), Fall 2018, “Software Engineering in the BioTech field”

47. Steven Whitham (G), Summer 2018, “Automated Heartbeat Arrythmia Detection in Zebrafish”

48. Jingjing Yang (G), Summar 2018, “EMNets: A Convolutional Autoencoder for Protein Surface Retrieval Based on Cryo-Electron Microscopy Imaging”

49. Kay Phan (UG), Summer 2018, “Identification of Depression with Machine Learning”

50. Matthew Simms (UG), Summer 2018, “Using Convolutional Neural Networks to Denoise Low Dose CT Images”

51. Albert Ng (G), Spring 2018, “Detection of Beta-Barrels from Medium Resolution Cryo-electron Microscopy Density Maps”

52. Danny Ly (UG), winter 2018, “Exploration of Genetic Algorithms”

53. Michael Nissenson (UG), spring 2017, “Automatic Protein Chain Isolation from 3D Cryo-EM Data”

54. Joe Ma (UG), spring 2017, “Android Application Development”

Supervised Student Posters / Presentations

1.     Mingjia Cai. "Deep Learning for CT Image Reconstruction". UW Undergraduate Research Symposium, Seattle, May 2020. (poster)

2.     Nodira Povey. "Applying U-Net model to improve the quality of low dose and sparse-view CT scans". 2nd Biennial Meeting of SIAM Pacific Northwest Section, Seattle, WA, October 2019. (poster)

3.     Noah McMichael and Pedro Mokarzel. "Iterative method for computed tomography reconstruction with learned regularization term". 2nd Biennial Meeting of SIAM Pacific Northwest Section, Seattle, WA, October 2019. (poster / short oral presentation)

Awards/Honors to Supervised Students

1.     Kristin Ding. Mary Gates Undergraduate Research Scholarship, UW 2023.

2.     Isabel Amaya, Award for Aspirations in Computing, NCWIT 2023.

3.     Kiran Mitra, Award for Aspirations in Computing, NCWIT 2023.

4.     Haowen Guan, IEEE BIBM Student Travel Award, IEEE 2022.

5.     Jade Liang. Mary Gates Undergraduate Research Scholarship, UW 2022.

6.     Yinzhou Wang. Mary Gates Undergraduate Research Scholarship, UW 2022.

7.     Jenny Rong. Mary Gates Undergraduate Research Scholarship, UW 2021.

8.     Alan Burnett. Best Presentation Award, ICCDA-ACM 2017.

9.     Michael Nissenson. ACM-SIGBIO Outstanding Undergraduate Research, ACM 2017.

Supervised K-12 Students

1.     Isabel Amaya. Inglemoor High School. 2023 Winter - present. Enrolled at UW in 2023. Awardee of 2023 NCWIT Aspirations in Computing

2.     Kiran Mitra. The Overlake School. 2021 summer - present. Enrolled at Cornell in 2023. Awardee of 2023 NCWIT Aspirations in Computing

3.     Anika Mahesh, Willows Preparatory School. 2022 Autumn - present.

4.     Albert Luo, The Overlake School. 2022 summer - present.

5.     Kaustav Mitra, The Overlake School. 2022 summer - present.

6.     Leo Tian. Interlake High School. 2021 summer - 2023 summer. Enrolled at UW in 2023.

7.     Andy Yang, The Overlake School. 2022 summer - 2023 summer. Enrolled at UC Berkeley in 2023.

8.     Eric An, Lakeside High School. 2022 summer.

9.     Adrian Avram. The Overlake School. 2020 summer - 2021 Spring. Enrolled at UW in 2021.