Background
I am a Computing and Information Sciences Ph.D. student at Rochester Institute of Technology, working with Professor Cecilia O. Alm in the Computational Linguistics and Speech Processing Lab (CLaSP). My research focuses on interactive machine learning and federated learning for multimodal affective computing.
Research Interests
My research interests include multimodal machine learning, interactive machine learning, affective computing, natural language/speech processing, personalized federated learning, and Reinforcement Learning for human behavioral modeling.
News
- (02/2024): Paper accepted at LREC-COLING 2024
- (07/2023): Demo accepted to ACII 2023
- (11/2022): Poster accepted to SIGCSE 2023
- (08/2022): Accepted to the ACII 2022 Doctoral Consortium
- (07/2022): Workshop paper accepted at 2nd HCI+NLP Workshop (at NAACL 2022)
- (05/2022): Passed Research Potential Assessment (RPA)
- (03/2022): Demo paper accepted at EmoCHI’22
Education
Ph.D. in Computing and Information Sciences(2021 - in progress)
Rochester Institute of TechnologyRochester, NY, USA
Bachelor in Computer Engineering(2013 - 2017)
Pulchowk Campus, Institute of EngineeringLalitpur, Nepal
Work Experience
Graduate Research Assistant(August 2021 - Present)
Computational Linguistics and Speech Processing Lab, RITRochester, NY, USA
- Conducted an IRB-approved multimodal data collection experiment using several human tasks to study the subtleness of emotion expressions.
- Investigated the benefits and trade-offs of interactive machine learning approaches, including active learning and machine teaching, for advancing affective computing.
- Exploring federated learning and interactive machine learning to enhance the personalization and generalization of behavioral models representing extremely diverse human behavioral expressions and perceptions.
Graduate Teaching Assistant(August 2023 - December 2023)
Foundations of Artificial Intelligence, RITRochester, NY, USA
- Co-prepared problem sets reflecting various concepts in Artificial Intelligence
- Created video tutorials on transfer learning, large multimodal models (LMMs), large language models (LLMs), and fine-tuning techniques for LLMs.
- Grader for technical problem sets and reading assignments (written critiques of published research papers)
- TA office hours
Visiting Researcher(October 2023 - November 2023)
ML-LabsDublin, Ireland
- Conducting research and co-authored dissemination with collaborators at University College Dublin (UCD), Dublin City University (DCU), and Technological University Dublin (TUD).
- Using generative LLMs to investigate psychological vulnerabilities in phishing emails
Machine Learning Engineer(July 2018 - July 2021)
Fusemachines NepalKathmandu, Nepal
- Led a team on Zendesk-based automated reply system
- Co-led a team on a information retrieval system for a construction project leads and analytic company
- Prepared NLP, RL, and CS course materials for Fusemachines Nanodegree
Publications
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Rajesh Titung and Cecilia O. Alm. Forthcoming (2024). FUSE - FrUstration and Surprise Expressions: A Subtle Emotional Multimodal Language Corpus. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING). [pdf]
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Isabelle Arthur, Jordan Quinn, Rajesh Titung, Cecilia O. Alm, and Reynold Bailey. 2023. MDE - Multimodal Data Explorer for Flexible Visualization of Multiple Data Streams. (demo). ACII 2023: 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). [pdf]
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Cecilia O. Alm, Rajesh Titung, and Reynold Bailey. 2023. Pandemic Impacts on Assessment of Undergraduate Research. (poster). SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education. [pdf]
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Rajesh Titung. 2022. Interactive Machine Learning for Multimodal Affective Computing. In Proceedings of the Doctoral Consortium of 10th International Conference on Affective Computing Intelligent Interaction (ACII 2022). [pdf]
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Rajesh Titung and Cecilia O. Alm. 2022. Teaching interactively to learn emotions in natural language. In Proceedings of the Second Workshop on Bridging Human–Computer Interaction and Natural Language Processing, pages 40–46, Seattle, Washington. Association for Computational Linguistics. [pdf]
Extended Abstracts without Proceedings
- Cecilia O. Alm and Rajesh Titung. 2022. Engaging human interactions to learn emotions. EmoCHI’22.
Technical Skills
- Languages: English, Nepali, Tamang, Hindi
- Programming Languages: Python, Java, C/C++, SQL (Postgres),MongoDB
- Libraries: Scikit-learn, Tensorflow, Keras, Pytorch, OpenAI Gym, nltk, spacy, transformers, peft
- Tools: Pandas, Matplotlib, NumPy, Seaborn, Matlab, Jupyter Notebook, conda, pipenv, cookiecutter, FLask
- Developer Tools: Git, Docker, Atom, AWS, Jira
- Hardware/Sensory Equipments: Pupil Labs Pupil Core Eye tracker, SMI screen-based eye tracker, Tascam audio/speech recorders, GSR Shimmer3 wearable sensors
- Softwares: iMotions, Praat