Vitae
General Information
Full Name | Dimitrios Mallis, PhD |
malldimi1 [at] gmail [dot] com | |
Github | github.com/dimitrismallis |
linkedin.com/in/dimitrismallis | |
Location | Luxembourg |
Experience
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2023-present
Posdoctoral Researcher (3D Computer Vision)
SnT • University of Luxembourg (Luxembourg)
- Member of the Computer Vision, Imaging & Machine Intelligence Research Group (CVI²) at SnT, University of Luxembourg.
- Working in close collaboration with our industrial partner Artec3D.
- My research focus is on reverse engineering of CAD models from 3D scans, recovery of construction history and capturing of design intent.
- Organizer for the SHARP2023 Challenge, organized in conjunction with the ICCV 2023 and the SHARP Workshop.
- Group Head: Dr. Djamila Aouada
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Projects
- Deep Learning of 3D Scanned Data [Project Page]
- CASCADES, Constrained Sequence modelling of CAD for reverse Engineering from 3d Scans [Project Page]
- FREE-3D, Feature Reverse Engineering Of 3D Scans [Project Page]
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Research areas
- Reverse Engineering from 3D Scans
- Reverse Engineering of Parametric CAD Sketches
- Self-Supervised Learning
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2022-2023
Senior Machine Learning Engineer (Recommender Systems)
Taboola • DeepLab (Athens, Greece)
- Part of DeepLab's dedicated team of Taboolars.
- I aqured experience with developing and deploying ML solutions at scale, for Taboola's massive recommender system service.
- Our work on incremental learning for efficient Click-Through-Rate (CTR) prediction, was presented on the industrial track of RecSys in 2022.
- I supervised two bachelor students and one master student along the lines of DeepLab's collaboration with the National Technical University of Athens.
- Manager: Dr. Stefanos Angelidis
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Research areas
- Deep Learning for Recommender Systems
- Click-Through-Rate (CTR) prediction
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2020-2021
Research Intern (Computer Vision)
Samsung AI Centre Cambridge (SAIC-C) (Cambridge, UK)
- Six-month PhD Internshp, extended to a part-time position.
- Manager: Dr. Yiorgos Tzimiropoulos
- I developed a framework for adapting pretrained pose estimation models on new target domains. Significant performance increase was reported on internal company benchmarks, with direct application on various pipelines within Samsung.
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Research areas
- Multiperson Human Pose Estimation
- 3D Pose Estimation
- Semi-Supervised Learning
- Self-Training
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2016 - 2017
Software Engineer
Singular Logic (Athens, Greece)
- Designing custom solution, applications and services for organisations of the Greek public sector.
- Main focus on server-side applications, middle-wares and APIs, using .NET and C#.
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Technologies
- C#, .NET Core, ASP.NET Web Api 2, ASP.NET Core, LINQ, Ninject, TFS, ADO.NET, Async Programming.
Education
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2018-2022
PhD in Computer Vision
University of Nottingham (Nottingham, UK)
- Advisor: Dr. Yiorgos Tzimiropoulos
- Member of the Computer Vision Laboratory (CVL) of the University of Nottingham.
- My PhD thesis was on Unsupervised Landmark Discovery via Self-Training Correspondence.
- My research on self-supervised representation learning for landmark correspondence recovery lead to prestigious publications at the Conference on Neural Information Processing Systems (NeurIPS) in 2020 and IEEE's Transactions on Pattern Analysis and Machine Intelligence (TPAMI) in 2023.
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Research areas
- Unsupervised Landmark Discovery
- Self-Supervised Learning
- Self-Training
- Learning under label noise
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2010-2015
Diploma in Electrical and Computer Engineering
Democritus University of Thrace (D.U.Th) (Xanthi, Greece)
- Program Duration: 5 years
- A diploma is the Greek equivelant to BSc + MSc.
- My diploma thesis was on Sound Source Separation in Real Room Environment.
- Research conducted for my thesis has been partially published in [AIAI2016] and later [EvolvingSystems2018].
- Our work on sentiment analysis of Greek Tweets lead to publications in [PCI2015] and [JSIT2018].
- Graduated with the 4th highest grade on my cohord.
- Advisor: Dr. Nikos Mitianoudis
Teaching
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2022 - present
Master/Undergrad students (collaboration with Deeplab).
- Through my ongoing collaboration with Deeplab, I participate in the supervision master/undergrad student's, towards either the completion of their thesis or paper submissions.
- Part of Deeplabs collaboration with the National Technical University of Athens (NTUA).
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Student Projects
- Maria Parelli's work on Interpretable Visual Question Answering Via Reasoning Supervision, presented at ICIP 2023 as a lecture.
- Zacharias Anastasaki's diploma thesis on Self-Supervised Visual Relationship Detection, also partially presented at WAVC 2023 as a poster.
- Danai Brilli's diploma thesis on Scene Graph Guided Visual Question Answering (ongoing).
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2023 - present
CVIA lectures
- Guess lecturer for the Computer Vision & Image Analysis (CVIA) Course.
- Part of the Interdisciplinary Space Master (ISM) / Master is Information and Computer Science (MICS) of SnT, Univesity of Luxembourg.
- Lecture on Deep Learning.
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2018-2021
Teaching Assistant
- During my PhD, I served as a teaching assistant for multiple undergraduate modules of the School of Computer Science (University of Nottingham).
- My duties included lab tutoring, coursework marking and running tutorials.
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Modules
- Computer Fundamentals
- C++ Programming
- Mobile Developments
- Image Processing
Reviewer
- I have served as reviewer for the following journals and conferences:
- ECCV, BMVC, NeurIPS(W), ICIP, ICMLA, CVPR, ICCV(W), WACV.
Awards and Disntinctions
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2018
- I was awarded a full funded PhD scholarship by the University of Nottingham and The Douglas Bomford Trust.
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2015
- I graduated with the 4th highest grade of my university cohord (DUTH).
Open Source Repositories
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ICCV 2023 - SHARP CHALLENGE
- SHARP 2023 workshop and challenge organised by the CVI² group of the University of Luxembourg and Artec3D, in conjunction with ICCV 2023.
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KeypointsToLandmarks
- Code for our TPAMI paper From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery.
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UnsupervisedLandmarks
- Code NeurIPS 2020 paper, Unsupervised Learning of Object Landmarks via Self-Training Correspondence.