Niki Martinel Email and Phone Number
I am an Associate Professor of Computer Vision (CV) and Machine Learning (ML) with a strong passion for proposing novel solutions to real-world problems. With an unwavering commitment to bridging the gap between theory and practice, I strive to make a tangible impact by transforming cutting-edge research into practical applications. My expertise lies in object detection and segmentation, visual tracking, target re-identification as well as inverse computer vision problems like super-resolution and automatic colorization applied to different contexts. I'm constantly pushing the boundaries of what is possible in the field.Throughout my career, I have spearheaded numerous research projects in CV, resulting in significant improvements in accuracy and efficiency. My work has been published extensively in top-tier journals and conferences, contributing to the advancement of knowledge in the field. As a mentor and supervisor, I have guided a diverse group of graduate students, empowering them to become experts in the domain.In addition to my academic pursuits, I actively collaborate with industry partners to translate research findings into innovative solutions that solve real-world challenges. By fostering strong relationships and leveraging cutting-edge technologies, I have successfully driven forward practical applications of computer vision and machine learning.As an educator, I have taught advanced courses on ML and CV, equipping students with the skills necessary to tackle complex problems in the field. Moreover, I have led research initiatives focused on developing state-of-the-art algorithms for skier tracking, person and vehicle re-identification, and super-resolution and automatic colorization of natural (underwater) images, resulting in remarkable performance improvements.I hold a Ph.D. in Industrial and Information Engineering from the University of Udine, and I continuously engage in additional coursework and certifications to stay at the forefront of this rapidly evolving field. My commitment to excellence has been recognized through awards and honors, highlighting my significant contributions to the field.If you are passionate about cutting-edge research, driving technological advancements, or collaborating on real-world projects, I would be delighted to connect and explore new opportunities with you.
-
Associate Professor Of Computer Vision And Machine LearningUniversità Degli Studi Di UdineUdine, It -
Associate Professor Of Computer Vision And Machine LearningUniversità Degli Studi Di Udine Dec 2021 - PresentUdineI have achieved significant accomplishments that have contributed to my expertise as an Associate Professor of Computer Vision and Machine Learning. These accomplishments include:Teaching and Mentoring Experience:- Taught diverse courses at undergraduate, graduate, and PhD levels. Subjects including Computer Vision, Data Processing, and IoT sensors/networks- Received positive feedback for dynamic learning environment and effective communication of complex concepts (top 5% teachers in courses)- Foster an inclusive and dynamic learning environment that promotes critical thinking and hands-on experience- Mentor and guide more than 10 PhDs students and Post-Doctoral associates, encouraging their growth as independent researchers and problem solvers in the fieldGrants and Funding:- Acquired grants from esteemed institutions like the Office of Naval Research (ONR), Italian Ministries, and EU frameworks- Team member, Co-PI or PI for grants that brought in more than 1.5M fundings supporting cutting-edge research and innovative solutions- Demonstrated ability to propose and execute successful research projectsResearch Publications:- Published more than 50 papers in top-tier journals and conferences- Contributions in the fields of Computer Vision and Machine Learning by actively working on associations of researchers in the field- Recognized for novelty, technical rigor, and industry impactAwards:- Received recognition from the community as a to-ranked reviewer for prestigious international conferences (e.g., ECCV and CVPR)- Best paper awards at international conferences -
Assistant Professor Of Computer Vision And Machine Learning, Iot Sensor/NetworksUniversità Degli Studi Di Udine May 2018 - Dec 2021Udine, ItaliaMain activities:- Teaching undergraduate and graduate courses in computer vision, machine learning, and IoT, ensuring a comprehensive understanding of these subjects among students.- Mentoring and supervising graduate students, guiding them in their research projects related to computer vision, IoT, and sensor networks.- Applying for grants and funding opportunities to support research activities. Notably, I secured a relevant grant from the Office of Naval Research (ONR) for research on re-identification under cloth-changing scenarios.- Collaborating with industry partners and other academic institutions to foster research collaborations and leverage resources for impactful research outcomes.- Publishing research papers in top-tier conferences and journals, disseminating knowledge, and contributing to the advancement of computer vision and machine learning.
-
Postdoctoral FellowUniversità Degli Studi Di Udine Apr 2014 - May 2018UdineMain activities:- Supporting ongoing projects related to vision and perception, collaborating with teams from different universities, specifically contributing to a bilateral project between the University of Udine (UNIUD) and the National University of Singapore (NUS).- Conducting cutting-edge research on integrating vision and perception systems, exploring methods to bridge the gap between visual sensing and higher-level interpretation.- Collaborating with interdisciplinary teams to develop novel algorithms and models that enhance the understanding and interpretation of visual data.- Designing and conducting experiments to evaluate the performance of vision and perception systems, analyzing results, and drawing meaningful conclusions.- Publishing research findings in reputable conferences and journals, contributing to the academic community, and showcasing the impact of our work in merging vision and perception.
-
Member Of Rtg Ist-169 Robustness And Accountability In Machine Learning Systems GroupNato Science & Technology Organization Aug 2018 - PresentAs a member of the NATO Research Task Group (RTG) on Robustness and Accountability in Machine Learning Systems, I had the privilege to contribute to cutting-edge research in the field of machine learning and its applications in military operations. Our RTG, IST-169 (AI2S), operated under the IST panel and focused on addressing the challenges of creating robust and accountable machine learning systems.During my involvement in this task group, we aimed to determine the state-of-the-art in robustness and accountability of machine learning systems, with a particular emphasis on deep learning systems with complex and large models. We explored methodologies to verify the compliance of commercial machine learning systems, including cloud-based systems, with a set of criteria. Our objective was to ensure the integrity and reliability of these systems in a military setting.I am proud to share that our research efforts were recognized at the IST-190 Research Symposium on AI, ML, and BD for Hybrid Military Operations (AI4HMO). Our team received the Best Paper Award for our groundbreaking work in the field. This achievement highlights the significance of our research and its potential impact on enhancing the effectiveness and trustworthiness of machine learning systems in military operations.Working alongside esteemed colleagues and experts in the field, I gained invaluable insights into the challenges and opportunities associated with machine learning systems. Our research not only focused on technical aspects but also emphasized the importance of accountability in decision-making processes. We explored ways to document decisions made by machine learning systems at the time of events, ensuring verifiability and transparency.Being part of this NATO RTG has been a rewarding experience, allowing me to contribute to the advancement of machine learning systems. I am grateful for the opportunity to collaborate with talented individuals and make a meaningful impact in this field. -
Deputy Chief For The Neural Networks And Deep Learning Technical CommitteeInternational Association Of Pattern Recognition - Italian Chapter Sep 2017 - PresentLeadership and Strategic Direction:- Provide strategic direction and leadership to the committee, setting goals and objectives aligned with the mission and vision of the association- Collaborate with the President and other committee members to develop and implement initiatives that promote the advancement of neural networks and deep learning in Italy- Foster opportunities for knowledge sharing, networking, and collaboration among researchers, practitioners, and industry professionals in the fieldTechnical Expertise and Knowledge Dissemination:- Stay up-to-date with the latest advancements and research trends in neural networks and deep learningCommittee Engagement and Membership Development:- Engage and collaborate with committee members to foster a vibrant and inclusive community- Facilitate the recruitment of new members and promote the benefits of joining the technical committee and the association
-
Advisory Board MemberEye-Tech Srl Nov 2014 - PresentStrategic Guidance:- Provided valuable strategic guidance and insights to the company's leadership team, leveraging my expertise in the fields of multimedia, computer vision, and AI- Contributed to the formulation and execution of the company's research and development roadmap, ensuring alignment with industry trends and technological advancements- Offered recommendations on potential areas of research and innovation, helping the company stay at the forefront of emerging technologies and market demandsResearch Collaboration:- Collaborated closely with the company's research and development teams, fostering a culture of innovation and scientific excellence- Shared my domain knowledge and expertise to drive the development of cutting-edge algorithms and methodologies in multimedia, computer vision, and AI- Participated in brainstorming sessions, contributing ideas and insights to address complex technical challenges and improve the company's products and solutionsTechnical Evaluation and Validation:- Conducted thorough technical evaluations and assessments of research proposals, projects, and prototypes, ensuring their scientific rigor and feasibility- Provided critical feedback and guidance on research methodologies, experimental design, and data analysis techniques, enhancing the overall quality of the company's research endeavors- Collaborated with cross-functional teams to validate and benchmark the performance of developed algorithms and models, ensuring they meet the highest standards of accuracy, efficiency, and scalability
-
Visiting ScientistUniversity Of California, Riverside Jan 2016 - Apr 2016United StatesResearch and Development:- Conducted in-depth research on active learning techniques for person re-identification, exploring innovative approaches to improve the accuracy and efficiency of the process- Collaborated closely with team members from various universities, leveraging their expertise and insights to enhance the research outcomes- Developed and implemented novel algorithms and methodologies, employing cutting-edge computer vision techniques to address the challenges in person re-identificationExperimentation and Evaluation:- Designed and conducted rigorous experiments to evaluate the performance of the developed active learning techniques- Analyzed experimental results and drew meaningful conclusions, identifying the strengths and limitations of the proposed techniquesPublication and Achievements:- Compiled the research findings into a high-quality manuscript for submission to the European Conference on Computer Vision (ECCV), showcasing the impact and recognition of our work within the academic community- Collaborated with team members to refine and improve the manuscript, ensuring its technical rigor and clarity- Demonstrated that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%Collaboration and Knowledge Exchange:- Participated in regular meetings, discussions, and knowledge-sharing sessions to exchange ideas, insights, and best practices -
Junior SpecialistUniversity Of California, Riverside Sep 2012 - Apr 2013RiversideResearch and Experimentation:- Conducted extensive research on modeling novel image features for person re-identification, aiming to enhance accuracy and robustness across different cameras- Explored and applied various machine learning techniques to learn transformations of features, facilitating effective cross-camera matching- Designed and executed comprehensive experiments to evaluate the performance and effectiveness of the proposed models and techniques, utilizing diverse datasets and realistic scenarios.Collaboration with Local Team Members:- Actively collaborated with the local team members of the Vision Computing Group@UCR leveraging their expertise and insights to enhance the research outcomes- Engaged in regular meetings, discussions, and brainstorming sessions to exchange ideas, share progress, and address challenges collaboratively- Fostered a supportive and collaborative environment, promoting effective teamwork and leveraging the collective intelligence of the research groupManuscript Preparation and Review:- Compiled the research findings, methodologies, and experimental results into a high-quality manuscript suitable for publication in the IEEE Transactions on Pattern Analysis and Machine Intelligence showcasing the superior performance of the proposed approach over state-of-the-art person re-identification methods- Worked closely with the local team members to refine the manuscript, ensuring its technical rigor, clarity, and adherence to journal guidelines- Celebrated the accomplishment of having our research accepted and published in the journal, acknowledging the recognition and impact of our work within the academic community (TPAMI IF: 23.6)
-
Analyst And DeveloperMediastudio S.R.L. Apr 2009 - Dec 2010Application Development:- Collaborated with a team of software engineers and designers to develop the CAD-based application from inception to completion- Utilized programming languages and software development tools to build a user-friendly interface and ensure smooth functionality- Integrated cutting-edge CAD technologies to enable users to draw precise 3D kitchen designs, incorporating various kitchen components and appliances.3D Modeling and Simulation:- Implemented sophisticated algorithms and techniques to generate realistic and accurate 3D models of kitchens, appliances, and other elements- Developed a simulation environment that allowed users to visualize how the kitchen design would look and feel in a virtual setting- Iteratively improved the rendering and simulation capabilities to create a seamless and immersive experience for usersProduction-Ready Outputs:- Implemented features that enabled the application to generate production-ready 3D models of the designed kitchens and appliances- Ensured that the generated models met the necessary specifications and standards required for manufacturing and production processes- Collaborated closely with kitchen producers to understand their requirements and incorporate them into the application's output generation capabilitiesTroubleshooting and Bug Fixing:- Actively participated in debugging and troubleshooting sessions to identify and resolve software issues, ensuring a smooth user experience.- Collaborated with the Quality Assurance team to test and validate the application's functionality, addressing any identified bugs or usability concerns- Iteratively improved the software based on user feedback and evolving industry standards, ensuring continuous enhancement and customer satisfactionCollaboration and Teamwork:- Actively participated in team meetings, providing insights and suggestions to enhance the application's functionality and user experience
Niki Martinel Education Details
-
Machine Learning
-
Computer Vision/Multimedia
-
Multimedia Communication
-
Multimedia Science And Technology
-
Itis Kennedy
Frequently Asked Questions about Niki Martinel
What company does Niki Martinel work for?
Niki Martinel works for Università Degli Studi Di Udine
What is Niki Martinel's role at the current company?
Niki Martinel's current role is Associate Professor of Computer Vision and Machine Learning.
What schools did Niki Martinel attend?
Niki Martinel attended Università Degli Studi Di Udine, Università Degli Studi Di Udine, Università Degli Studi Di Udine, Università Degli Studi Di Udine, Itis Kennedy.
Who are Niki Martinel's colleagues?
Niki Martinel's colleagues are Silvia Gabrielli, Giulia Bianchet, Raffaella Faggionato, Paola De Monte, Sonia Bosero, Matteo Balestrieri, Claudia Di Sciacca.
Free Chrome Extension
Find emails, phones & company data instantly
Aero Online
Your AI prospecting assistant
Select data to include:
0 records × $0.02 per record
Download 750 million emails and 100 million phone numbers
Access emails and phone numbers of over 750 million business users. Instantly download verified profiles using 20+ filters, including location, job title, company, function, and industry.
Start your free trial